tag:blogger.com,1999:blog-52040925918762110472024-03-05T10:00:39.704-05:00Advanced NFL Stats CommunityAn open collaborative site for NFL statistics enthusiasts.Unknownnoreply@blogger.comBlogger132125tag:blogger.com,1999:blog-5204092591876211047.post-52845297884662971312014-06-08T08:08:00.001-04:002014-06-08T08:08:37.455-04:00Infinite Field Football<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi9hxdvsJ_9nTG0Yq8C-iF7ATHa96nGvkhjULljp4TmUkMBMFXiyVqwhwjwDpEEpT4dz-dObqLoefcQ9hhdJOfTdqe05Aq18Ju_8F2vCCp5-vZPRwD4Iw4NhmBjcUD_kPkmsLQtsOLMm_w5/s1600/mirror.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi9hxdvsJ_9nTG0Yq8C-iF7ATHa96nGvkhjULljp4TmUkMBMFXiyVqwhwjwDpEEpT4dz-dObqLoefcQ9hhdJOfTdqe05Aq18Ju_8F2vCCp5-vZPRwD4Iw4NhmBjcUD_kPkmsLQtsOLMm_w5/s1600/mirror.jpg" /></a></div>
by Michael Nahas<br />
<br />
<br />
Physicists are always talking about ideal environments, like infinite planes with zero friction. What if we extended that to football and had teams play on an infinite field with an infinite clock?<br />
<br />
How would it work? One team would start with the ball, drive some number of yards down field, and then turn the ball over to the other team. At that point, the other team would take the ball, drive some amount of yards in the other direction, before turning the ball over to the first team. And so on.<br />
<br />
They would go back and forth, except for one strange exception. That exception is when the ball carrier is the fastest guy on the field and he gets through the defense. Can he run for infinity? The short answer is yes. But, for the moment, let's assume that doesn't happen and, later, I'll tell how to handle when it does.<br />
<br />
It's pretty obvious that "winning" on the infinite field means that your team, when it possesses the ball, moves the ball further than when the other team possesses it. So, the thing we want to compute is the expected length of a drive.<br />
<br />
The most informative way to calculate that is to break the drive into series of downs. Each series either ends in a new first down or a turnover. So let's define:<br />
P = probability of a series ending in a new first down<br />
D1 = expected length of series that ends in a new first down<br />
D4 = expected length of a series that doesn't end in a first down<br />
<br />
Now, we can build an equation for the expected length of a drive by looking at the number of first downs that occurred in it. <br />
<br />
Exactly 0 first downs occurs (1-P) of the time <br />
Exactly 1 first downs occurs P*(1-P) of the time<br />
Exactly 2 first downs occurs P*P*(1-P) of the time <br />
...<br />
Exactly N first downs occurs P^N*(1-P) of the time <br />
<br />
In probability, this is the geometric distribution. The Wikipedia page gives us the mean: P/(1-P). (NOTE: if you check the Wikipedia page, they're answer is (1-p)/p. This because their p is equal to my 1-P.) Now, knowing the number of first downs, we can write the expected length of a drive:<br />
<br />
Expected length of a drive = (P/(1-P))*D1 + D4<br />
<br />
Now, suddenly, P becomes very interesting. As it gets bigger, the length of the drive grows faster than linear.<br />
<br />
P=.75 ---> Expected first downs = 3<br />
P=.80 ---> Expected first downs = 4<br />
P=.85 ---> Expected first downs = 5.666<br />
<br />
Regarding the other factors, I don't expect the "expected distance to a new first down" to vary much between teams. Team with better offenses will produce more yards but some of those yards will go to reaching the first down in fewer downs. The "expected distance without a first down" will probably only differ between teams that punt after 3 downs and those who "go for it" on fourth.<br />
<br />
When should a team "go for it"? Well, there we need to know the chance of making a first down. If that times the expected length of drive is longer than your punt, the team should go for it. Teams that "go for it" on fourth will have a larger probability of getting a first down, which we saw above, is the key metric in infinite field football.<br />
<br />
<b>What does this mean to finite field football?</b><br />
The first conclusion to draw is that first down percentage and drive length are key stats to look at. We all knew they were important before, but I think they are worth considering as _the_ team metrics to look at. Likewise, for defenses, their affect on first down percentage is important.<br />
<br />
My second conclusion is that first down percentage has a non-linear affect on drive length. A lot of analysis techniques assume linear relationships between terms. We need to be careful about how we apply those techniques.<br />
<br />
My third conclusion is actually a supposition. I believe that EPA by field position is based on the Ps of the two teams. <a href="http://www.advancedfootballanalytics.com/2010/01/expected-points-ep-and-expected-points.html" target="_blank">Brian Burke in 2008 said it wasn't linear.</a> The graph he produced was based on data for all teams, but he also said "Another complication is that various teams have different curves." I think with Ps, we can determine what EPA by field position should look like from a theoretic point of view.<br />
<br />
<b>What no data?</b><br />
This post doesn't have any data. I spend my days programming, so that muscle is exhausted when I have time off. So, if you like the idea, I'd love to see data too.<br />
<br />
If we took a team's downs between their own 10 and the opponent's 20, I think we'd see some clear trends. Monte carlo techniques at the series-of-downs level (or at the down-by-down level) could be used to estimate the length of drives. Long plays that resulted in touchdowns (that is, those infinite runs on the infinite length field) could be sidestepped by computing the median length of drive rather than the expected. I'll be interested to see if the data is significant enough to measure differences.<br />
<br />
Another important thing to measure is the finite field aspects. How well does an estimate of performance on an infinite field predict performance inside your own 10 and inside their 20? Brian Burke in 2008 said that <a href="http://www.advancedfootballanalytics.com/2008/01/is-red-zone-performance-real.html" target="_blank">QBs weren't statistically significantly better (or worse) inside the red zone.</a> Good outside was good inside. Is that true for the whole offense? If so, I think the infinite field model is worth keeping around.Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-66873242919149330422014-01-07T00:58:00.000-05:002014-01-07T00:58:03.815-05:00How does weather affect a QB's QBR<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEieH33NKKTQdiQ9Xlf9D9NvBxR5Pc2t6QF_i9MUkzDq7QlFrX7oYRq4v6FEwEwc50R_7embw9ckLkoCabmMY_qPHcEyvaIW6SPpXFEfiw7CgoHJ1TbRi7uvR929EczoxIiqz0ISM92S_SlN/s1600/icebowl.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEieH33NKKTQdiQ9Xlf9D9NvBxR5Pc2t6QF_i9MUkzDq7QlFrX7oYRq4v6FEwEwc50R_7embw9ckLkoCabmMY_qPHcEyvaIW6SPpXFEfiw7CgoHJ1TbRi7uvR929EczoxIiqz0ISM92S_SlN/s400/icebowl.jpg" /></a></div>By Krishna Narsu<br />
<br />
A few years ago when I interned with ESPN, I had the pleasure of meeting the ESPN Analytics team. This was back when <a href="http://espn.go.com/nfl/story/_/id/9634173/nfl-total-qbr-updates-2013">Total QBR</a> was first being rolled out. After listening to a presentation the team gave on QBR, I became a fan of the metric. One of the things I was curious about was how weather impacted QBR. Does QBR go up in domes? Does QBR go down when it’s really cold? Dean Oliver, one of the creators of the statistic, was nice enough to send me the QBR data and I obtained the weather data by scraping the NFL gamebooks. I completed the study a few years ago but never thought of posting the results. Now, with the Green Bay-SF game expected to be bone-chillingly cold, I'm putting this post out. <br />
<br />
When I conducted the study, I used an <a href="https://en.wikipedia.org/wiki/Analysis_of_variance">ANOVA</a> to test if two samples of different weather data were significantly different. For example, one of the tests was rain <br />
vs. no rain. I looked at a number of different categories: rain, hot/cold, wind, wind chill, domes, etc. Here were the results:<br />
<a name='more'></a><br />
<style type="text/css">.nobrtable br { display: none }</style><br />
<div class="nobrtable"><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"; white-space: nowrap;></col></colgroup><thead>
<tr><th></th><th>QBR</th><th>Count</th></tr>
</thead>
<tr><td style="text-align: center;"> Rain</td><td>42.19</td><td>42</td></tr>
<tr><td style="text-align: center;"> No Rain</td><td>50.79</td><td>2074</td></tr>
<tr><td style="text-align: center;"> Dome</td><td>51.74</td><td>326</td></tr>
<tr><td style="text-align: center;"> Outside</td><td>49.67</td><td>1524</td></tr>
<tr><td style="text-align: center;"> Road Dome</td><td>52.12</td><td>163</td></tr>
<tr><td style="text-align: center;"> wind less than 20 mph</td><td>50.76</td><td>2016</td></tr>
<tr><td style="text-align: center;"> wind greater than 20 mph</td><td>48.27</td><td>74</td></tr>
<tr><td style="text-align: center;"> wind greater than 25 mph</td><td>44.53</td><td>28</td></tr>
<tr><td style="text-align: center;"> wind greater than 30 mph</td><td>43.04</td><td>16</td></tr>
<tr><td style="text-align: center;"> temp less than 32°</td><td>49.5</td><td>140</td></tr>
<tr><td style="text-align: center;"> temp less than 32° home</td><td>49.6</td><td>70</td></tr>
<tr><td style="text-align: center;"> temp less than 32° road</td><td>49.39</td><td>70</td></tr>
<tr><td style="text-align: center;"> wind chill less than 32°</td><td>49.34</td><td>244</td></tr>
<tr><td style="text-align: center;"> wind chill less than 20°</td><td>49.31</td><td>88</td></tr>
<tr><td style="text-align: center;"> wind chill less than 10°</td><td>45.6</td><td>38</td></tr>
<tr><td style="text-align: center;"> wind chill less than 0°</td><td>54.59</td><td>14</td></tr>
<tr><td style="text-align: center;"> temp greater than 80°</td><td>52.8</td><td>140</td></tr>
<tr><td style="text-align: center;"> temp greater than 80° Home</td><td>51.69</td><td>70</td></tr>
<tr><td style="text-align: center;"> temp greater than 80° Road</td><td>53.9</td><td>70</td></tr>
</tbody></table></div></div>The first column is the weather type, then the average QBR and the Count is the number of games in that type of weather. I’ve highlighted the only types of weather that had statistically significant differences in average QBR and that was rain versus no rain.<br />
<br />
What determines the drop in QBR in Rain? I summed up the <a href="http://www.advancednflstats.com/2010/01/expected-points-ep-and-expected-points.html">EPA</a> (Expected Points Added) for INTs, sacks, fumbles, etc. and divided that by the number of games to get an average EPA per game for INTs, sacks, etc. (not sure if there's a better way to look at this). I found that there was a more negative <a href="http://espn.go.com/nfl/qbr/_/stats/expanded">YAC EPA lost</a>, a higher sack EPA lost per game and a higher Fumble EPA lost per game but less EPA lost due to INTs in rain. I would guess that when it’s raining, QBs become more conservative (by trying to lower the amount of INTs they throw by taking less chances) and take sacks instead, which may lead to more fumbles. Also, I would imagine that offenses throw shorter passes in the rain, maybe explaining the more YAC gained for WRs.<br />
<br />
A few more comments: When I looked at dome QBR vs. outside QBR, I noticed there was no statistically significant difference but considering a lot of the games played in domes were biased because Matt Ryan and Drew Brees play all their home games in a dome, I decided to look at road dome QBR vs. outside QBR. It turns out that the average QBR for QBs playing on the road in domes was actually higher than it was for QBs playing at home. However, the difference was still not statistically significant. Furthermore, there are no advantages for the QB at home in a dome as road QBs actually had higher QBRs than home QBs.<br />
<br />
We also see that playing in hot weather can help QBR and while it wasn’t statistically significant, it was very close (<a href="https://en.wikipedia.org/wiki/Statistical_hypothesis_testing">hypothesis test:</a> 80+ degree mean QBR > than control group mean QBR, <a href="https://en.wikipedia.org/wiki/One-tailed_test">one-tailed test,</a> p=.18). If we remove dome QBR from our control group and look at just games outside where the temperature was >80 degrees versus <80 degrees, we find that the differences in means are statistically significant at the alpha level of .10 (p=.09).
Another interesting aspect of the study was that if you look at QBR as wind increases, we can see a noticeable difference. Unfortunately, when we get up to wind more than 30 mph, we only have 8 games where that took place. None of the categories for wind were statistically significant but for winds >25 mph and 30 mph, it was close (p=.13). While games played in high wind conditions don’t happen very often, I think it’s safe to say that high winds do have an effect on QBR. <br />
<br />
Also, I’m sure we all noticed that when the wind chill is less than 0 degrees, the average QBR is almost 55. This is an excellent example of a case where we don’t have a large enough sample size (7 games in total, 14 observations including home and road QBR). Perhaps including the last two years of data would help with this specific case but more likely, we’d need about 10+ years’ worth of data because games where the wind chill is under zero degrees simply don’t happen very often.<br />
<br />
However, those of you who are keeping tabs on the weather in the upcoming 49ers-Packers game are probably aware that the game is supposed to have wind chills under zero degrees, with a game time temperature under zero degrees as well. So with that in mind, what kind of QBRs can we expect for Aaron Rodgers and Colin Kaepernick given the last seven games where the wind chill was at or below zero degrees? Below is a list of those games with their weather conditions based on the official NFL gamebooks:<br />
<br />
<style type="text/css">.nobrtable br { display: none }</style><br />
<div class="nobrtable"><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"; white-space: nowrap;></col></colgroup><thead>
<tr><th>Game</th><th>Date</th><th>Time Est</th><th>Temp</th><th>Wind Speed</th><th>Wind Chill</th><th>Direction</th><th>Home QBR</th><th>Road QBR</th><th>Weather</th></tr>
</thead>
<tr><td style="text-align: center;"> GB@Chi</td><td>12/22/08</td><td>8:40</td><td>2</td><td>9</td><td>-13</td><td>WSW</td><td>13.7</td><td>72.99</td><td>Cloudy</td></tr>
<tr><td style="text-align: center;"> Mia@KC</td><td>12/21/08</td><td>1:00</td><td>10</td><td>20</td><td>-12</td><td>NNW</td><td>67.36</td><td>81.68</td><td>Sunny, Breezy</td></tr>
<tr><td style="text-align: center;"> Pitt@Cle</td><td>12/10/09</td><td>8:21</td><td>15</td><td>25-48</td><td>-6</td><td>W-SW</td><td>59.23</td><td>8.59</td><td>Cold</td></tr>
<tr><td style="text-align: center;"> Hou@GB</td><td>12/7/08</td><td>1:02</td><td>3</td><td>3</td><td>-3</td><td>SOUTH</td><td>70.74</td><td>94.65</td><td>Mostly Cloudy</td></tr>
<tr><td style="text-align: center;"> Ind@Buf</td><td>1/3/10</td><td>1:02</td><td>12</td><td>12</td><td>-2</td><td>WNW</td><td>73.89</td><td>14.31</td><td>Snow, 4-6 inches possible, Winds gusting to 25-30 MPH</td></tr>
<tr><td style="text-align: center;"> Jax@Cle</td><td>1/3/2010</td><td>1:03</td><td>16</td><td>20</td><td>-1</td><td>WEST</td><td>65.04</td><td>46.59</td><td>Snow Showers</td></tr>
<tr><td style="text-align: center;"> Cin@Cle</td><td>12/21/08</td><td>1:03</td><td>18</td><td>26</td><td>0</td><td>SW</td><td>0.7</td><td>94.82</td><td>Sunny/Cold</td></tr>
</tbody></table></div></div><br />
Rodgers has actually played in a pair of these games back in 2008. As we see in the table, his QBR was around the low 70s (if the QBR is slightly different from the ESPN game logs, keep in mind QBR has gone through some <a href="https://en.wikipedia.org/wiki/One-tailed_test">adjustments</a> over the years since I completed this study). Still, two games certainly aren’t enough to tell us what Rodgers will do. And ultimately, neither are 7 games. However, it is expected to be fairly windy and we do know that high winds have an effect on QBR. Given that, it’s likely both Kaepernick and Rodgers won’t perform up to their usual standards on Sunday.<br />
<br />
<i><span style="font-size: 12.0pt; line-height: 115%;">I will eventually update the study to<br />
include the last two years of data but I don’t anticipate any significant<br />
changes in the results since the sample of data I was originally working with<br />
was more than adequate in terms of sample size (2008-2011).<o:p></o:p></span></i><!--80--><br />
<div class="MsoNormal"><i><span style="font-size: 12.0pt; line-height: 115%;"><br />
</span></i></div><div class="MsoNormal"></div><div class="MsoNormal"><i><span style="font-size: 12.0pt; line-height: 115%;">Feel free to send any questions or<br />
comments about this to me on twitter @knarsu3<o:p></o:p></span></i></div><span style="font-size: 12.0pt; line-height: 115%;"><br />
</span> <br />
<br />
<div class="MsoNormal"><br />
</div>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-54651290015961486042013-12-09T08:05:00.003-05:002013-12-09T08:26:32.712-05:00EP forfeited<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiGTptSY-cx11-b6HHzFezZNMoeIxPtk9xcOizt2DazGj6n5SGuqfaz9iqD-iyXLcXyIQ2mKmiXufV7DpeEQDFvleLbgci76u5_UV2I5qEGVUfFA6suK6YFIvR5Z7Y1qnKwpElyC4NyxeKM/s1600/dunce.jpg" imageanchor="1" style="clear: right; float: right; margin-bottom: 1em; margin-left: 1em;"><img border="0" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiGTptSY-cx11-b6HHzFezZNMoeIxPtk9xcOizt2DazGj6n5SGuqfaz9iqD-iyXLcXyIQ2mKmiXufV7DpeEQDFvleLbgci76u5_UV2I5qEGVUfFA6suK6YFIvR5Z7Y1qnKwpElyC4NyxeKM/s400/dunce.jpg" width="300" /></a></div>Picture the scene. It’s February 2, 2014. We’re at the MetLife Stadium for Superbowl XLVIII. The opening kickoff has just gone for a touchback and out trots the offense. It’s first-and-ten. Here’s the snap and….<br />
<br />
What the heck? The QB just spiked it. What a bizarre play call from the coach. It’s now second-and-ten. What is going on? Is the coach deliberately trying to lose this game?<br />
<br />
Some time not much later in the game, with the score still tied, the coach faces fourth-and-two from the opponents 25. Out trots the field goal unit to attempt to give them the lead. “The field goal here is the right call”, proclaims Aikman. “You need to get points on the board. You don’t want to risk going for it and not coming away with something”<br />
<br />
I’m sure you know where this is going. The opening spike, which would have been rightly called as crazy by everyone watching, cost the team 0.48 expected points. The field goal attempt, which would have been hailed as a no-brainer by the standard voices, cost them an almost identical 0.49 EP over going for it. <a name='more'></a><br />
<br />
I got thinking about this after seeing a response to this tweet from the 4th Down Bot<br />
<br />
<blockquote class="twitter-tweet" data-cards="hidden" data-conversation="none" lang="en-gb"><a href="https://twitter.com/conorsen">@conorsen</a> I think it cost them about 0.3 points. <a href="http://t.co/BDqKt95QGY">http://t.co/BDqKt95QGY</a><br />
— NYT 4th Down Bot (@NYT4thDownBot) <a href="https://twitter.com/NYT4thDownBot/statuses/409790869848334336">December 8, 2013</a></blockquote><script async="" charset="utf-8" src="//platform.twitter.com/widgets.js"></script><br />
<br />
In reply, @MattSantaMaria confidently stated that fractional points aren’t possible. Please go away and try again.<br />
<br />
To be fair to him, he’s not wrong. Stating that a team cost themselves half a point is almost meaningless to someone who doesn’t have a grasp of probability. Explaining that attempting the field goal is as damaging to a team’s chances of winning as spiking the ball on the opening play of the game, however, might be more comprehensible.<br />
<br />
Some other ‘crazy decision’ EP equivalents<br />
<br />
<ul><li>Taking a deliberate delay-of-game penalty on third-and-five costs around 0.4 EP</li>
<li>Accepting an offside penalty when you’ve just gained 15 yards on a first-and-twenty play costs around 0.2 EP</li>
<li>Taking a knee on a second-and-five would cost around 0.65 EP</li>
</ul>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-64877940646635213462013-11-05T07:08:00.000-05:002013-11-05T07:08:02.956-05:00Should Colts have gone for 2by Ian Simcox<br />
So there I am, browsing my Twitter feed and I see this<br />
<br />
<blockquote class="twitter-tweet">Re HOU FG scenario: IND should still have gone for 2. Failed att means being down 15, which still gives 2 more bites at the 2-pt apple.<br />
— Brian Burke (@Adv_NFL_Stats) <a href="https://twitter.com/Adv_NFL_Stats/statuses/397217144775000064">November 4, 2013</a></blockquote><script async="" charset="utf-8" src="//platform.twitter.com/widgets.js"></script><br />
<br />
Predictably the replies featured people as sure of the value of kicking the XP as Brian was of going for the 2.<br />
<br />
At a 45% success rate on the 2-pts, the WP calculator says Indy have a 0.10WP if they kick the XP, comparing favourably to 0.09WP if they go for it (0.12 on success, 0.07 on failure). So, marginally the XPers have it. I must admit though, I plugged starting the 4th qtr down 10, 11 and 12 on 1st down into the calculator, to simplify the second part of this article.<br />
<br />
What really interests me is the uncertainty around these numbers, which is always important on these tight calls. The XPers may have it on the WP calculator, but if those numbers are +/- 0.03WP then it’s impossible to say which is right.<br />
<a name='more'></a><br />
<br />
To analyse these binary W-L uncertainties, I like to use my (admittedly basic) understanding of Bayesian probability. To test whether coach should go for 2, kick the XP, or just flip a coin because you can’t be certain, I used PFRs game play finder to find all plays since 1999 where a team led by 10, 11 and 12 at the start of the 4th quarter with the ball between their own goalline and 30 on 1st down (this is where my simplification earlier comes in, more samples here).<br />
<br />
From the Colts point of view then, the win-loss numbers are<br />
<table class="tableizer-table"></table><table align="center"><tbody>
<tr class="tableizer-firstrow"><th>Score</th><th> </th><th>W</th><th>L</th></tr>
<tr><td>Down 10 </td> <td></td><td>14 </td><td>128 </td></tr>
<tr><td>Down 11 </td> <td></td><td>3 </td><td>58 </td></tr>
<tr><td>Down 12 </td> <td></td><td>1 </td><td>29 </td></tr>
</tbody></table><br />
Assuming I know nothing about the probability of winning outside of this information (technically, using a uniform distribution on (0, 1) for my prior), Bayes’ rule gives me a posterior probability distribution for the chance of winning in each of the three scenarios. As we have more data for the down 10 case, we have greater certainty of the probability of winning than the other cases, but all of them feature some degree of uncertainty (the 95% CI for down 10 is 0.06-0.16WP, but for down 12 it is 0.01-0.17WP). Taking some liberties by assuming a 45% success rate on the two-point try, it’s a case of running a monte-carlo on the posterior distributions and analysing the results.<br />
<br />
With these numbers, going for it results in a 0.08WP for the Colts and kicking the XP a 0.06WP. So the 2-pters have it on the average. However a coach doesn’t have an average, he can only make the call once and I was looking for uncertainty. It turns out that by about 2-to-1, going for the two results in a higher WP.<br />
<br />
So what should a coach do? Well 2-to-1 are good odds, but it’s hardly statistically significant. You can’t say with any certainty that he would have been wrong to kick the XP.<br />
<br />
Ultimately we arrive at the unsatisfactory conclusion that you can’t say what the right call is. One thing we do know for sure though. Tweeters will continue to disagree about these calls and both sides will be 100% certain they are right. Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-4687873333561438362013-11-02T05:48:00.000-04:002013-11-02T05:48:11.207-04:00The Colts and their New “Run-Heavy” Offense<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTpSzoAT4AvbR3ameg8OV_SnmhNtUUi_pPBxUStx2BzkBPz9wyymLJ8-h7lTHpmT0THbza6oT8qaUiCuT5lNZQPkH6d3GSAJmeucdj_jUP0wxcnKCOKC9A1NbftR99lagf1LFzvAeJsmHe/s1600/andrew_luck.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTpSzoAT4AvbR3ameg8OV_SnmhNtUUi_pPBxUStx2BzkBPz9wyymLJ8-h7lTHpmT0THbza6oT8qaUiCuT5lNZQPkH6d3GSAJmeucdj_jUP0wxcnKCOKC9A1NbftR99lagf1LFzvAeJsmHe/s320/andrew_luck.jpg" /></a></div>By Sal Cacciatore<br />
<br />
When the Indianapolis Colts hired Pep Hamilton to be their offensive coordinator in January, the team’s buzzword this past offseason was “balance,” with coaches stressing the need to run the ball to win.<br />
<br />
While that may be cringe-worthy for anyone familiar with this site and Brian’s work on the topic, the Colts stand at 5-2, so there is a sentiment of vindication for Hamilton and head coach Chuck Pagano’s conservative coaching. <a href="http://espn.go.com/blog/indianapolis-colts/post/_/id/1641/colts-twitter-mailbag">Mike Wells of ESPN.com, formerly of the Indianapolis Star, went as far as to say the team “got their record by being a run-first team.”</a> <br />
<br />
Leaving aside how foolish molding a team led by prodigal quarterback Andrew Luck into a “run-first” club seems, we can use numbers to assess if Wells’ statement and <a href="http://www.indystar.com/article/20130922/SPORTS15/309220043/?gcheck=1">others like it</a> are true. <br />
<br />
Are the Colts actually a run-based team and are they winning because of a newfound emphasis on running?<a name='more'></a><br />
<br />
<b>A Run-Heavy Team?</b><br />
<br />
The Colts have passed on about 55% of their plays (this figure counts pass attempts and sacks as pass plays, but does not include quarterback scrambles), which is below the league-average of 59%.<br />
<br />
On its own, this figure really does not tell us anything substantive. Indianapolis has called a high frequency of running plays, but they have also been winning a lot this season. It stands to reason at least some of this running is a product of attempting to control the clock late in games.<br />
<br />
Winning teams run, and <a href="http://www.footballperspective.com/game-scripts-part-ii-analyzing-team-seasons/">as Chase Stuart notes, this is why teams like the 2007 Patriots had a league-average pass/run ratio despite being remembered as a wildly pass-happy team.</a> <br />
<br />
To truly find out whether a team is predominately run or pass oriented, we can use Stuart’s useful “Game Scripts” as a tool. <br />
<br />
<a href="http://www.footballperspective.com/introducing-game-scripts-part-i/">Game scripts measure a team’s average lead over the course of a game to give a better indication of how close the contest may have been.</a><br />
<br />
The metric is reached by taking each different scoring margin of a game and multiplying it by its duration, and after adding each product, dividing by 60 produces the game script.<br />
<br />
To use a simple example, if a game is scoreless for 59 minutes and a team then scores a touchdown with a minute to go, we get a game script of 0.12 (the formula would be (0*59 + 7*1)/60). This implies a very close game, as the average margin was just slightly above zero.<br />
<br />
Using a real example shows this metric’s utility. Consider Super Bowl XLIV, where the Saints beat the Colts by 14. We remember the game as a close affair that was not decided until Tracy Porter’s fateful interception, but had someone not watched the game, you could excuse him for assuming it was a comfortable Saints victory based on the final margin.<br />
<br />
Game script paints a more accurate picture, depicting the game as the close contest it was. In fact, the New Orleans game script was -1.9, meaning the Colts actually held a slim average lead for the game.<br />
<br />
Applying this to the matter at hand, we can also use game scripts to see which teams pass or run more than they would be expected to.<br />
<br />
<a href="http://www.footballperspective.com/game-scripts-part-iii-2012-results/">Stuart did this during the 2012 season by normalizing both a team’s average game script for the season and its pass/run rate on a scale where 100 is average.</a> By adding the two normalized stats together, we can see which teams are truly “pass-oriented” and which simply have high pass/run ratios because they find themselves behind frequently (Stuart calls this final number “pass identity”). <br />
<br />
Applying <a href="http://www.footballperspective.com/game-scripts-the-best-teams-of-2012/">Stuart’s formula</a> to the 2013 Colts, we find that while the Colts run the ball frequently, it seems this is largely a function of the team winning.<br />
<br />
As mentioned, Indianapolis passes roughly 55% of the time, which translates to a normalized pass/run ratio (“pass index”) of about 88. Since a pass index of 100 represents the league-average ratio, we see that the Colts have passed at a lower than average rate this season.<br />
<br />
By then bringing game scripts into the equation, we can put Indianapolis’ pass/run ratio into proper context, and see that it is a result of often playing with a lead. The 2013 Colts have an average game script of +2.8, which translates to a 112 game script index.<br />
<br />
Subtracting each index by 100 and then adding them together, we arrive at the Colts’ pass identity, which is 0. This means the team has run and passed at an average frequency when taking the score into account.<br />
<br />
Thus, while Indianapolis is running frequently, any perceived “run-first identity” is really just a product of the team playing to the score.<br />
<br />
<b>Winning Because of the Run?</b><br />
<br />
<a href="http://www.advancednflstats.com/2010/08/passing-winning.html">ANS has overwhelmingly proven that passing success is much more important than rushing success in the NFL,</a> and based on this alone, claims like the one made by Wells and others in the media do not hold much water.<br />
<br />
Beyond evidence like how passing efficiency correlates with winning more than rushing efficiency, there are other reasons why attributing the Colts’ success to their new focus on the run makes little sense.<br />
<br />
As previously mentioned, the Colts are even not truly a run-oriented team, but a squad that plays to the scoreboard in terms of pass/run ratio. They are running because they are winning, not winning because they are running.<br />
<br />
Hamilton’s supporters may still point to how this year’s Colts are more “balanced” than the 2012 team, <a href="http://www.footballperspective.com/game-scripts-the-best-teams-of-2012/">which posted a 108.6 pass index and +3.8 pass identity.</a> <br />
<br />
Recent seasons, though, seem to refute the idea that a balanced offense is preferable to a pass-heavy one.<br />
<br />
Stuart has posted pass identity numbers for both the <a href="http://www.footballperspective.com/game-scripts-part-ii-analyzing-team-seasons/">2011</a> and <a href="http://www.footballperspective.com/game-scripts-the-best-teams-of-2012/">2012 seasons</a>. During this span, pass identity correlated with team wins at 0.57. This suggests that teams built around the pass have generally been more successful recently than those with more judicious pass/run splits.<br />
<br />
Considering this, the theory “balanced” playcalling has helped the Colts earn their record is unsatisfactory.<br />
<br />
Andrew Luck, <a href="http://wp.advancednflstats.com/playerstats.php?pos=QB">with his 50.5 EPA and 50.2% success rate</a>, is a much more plausible catalyst.<br />
<br />
There is also an even greater and probably fatal flaw in the argument that running is fueling the Colts’ winning: Indianapolis may not even be a very good running team.<br />
<br />
The Colts are averaging 4.5 yards per carry, <a href="http://www.coltsauthority.com/2013-articles/october/the-bp-watch-the-colts-are-not-5-2-because-they-are-run-first.html">but as Kyle Rodriguez of Colts Authority (who ironically was also writing in response to Wells’ ESPN piece) notes, this figure is deceiving.</a><br />
<br />
Rodriguez explains this 4.5 average is heavily based on Luck’s scrambles and production from running backs Vick Ballard and Ahmad Bradshaw, both of whom are on IR (Ballard only played in Week 1 and Bradshaw last appeared in week 3). Discounting these players, the Colts average just over four yards per carry, <a href="http://www.pro-football-reference.com/years/2013/">which is the league average.</a><br />
<br />
Also, Trent Richardson, who leads the team in carries, is averaging three yards per rush, <a href="http://wp.advancednflstats.com/playerstats.php?year=2013&pos=RB&season=all">while posting -0.03 EPA and a 33.3% success rate (the latter puts him at 60th in the league among running backs.)</a><br />
<br />
Considering this, it is simply incorrect to praise the Colts for becoming a run-based offense or to attribute the team’s success to its running game over the feats of Andrew Luck.Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-1712269925645277462013-10-18T07:20:00.000-04:002013-10-18T07:20:18.183-04:00NFL Team snapshots - Week 6by Tom McDermott<br />
<i>(This submission of a repost and can be found at its original home <a href="http://nflrearwindow.blogspot.com/2013/10/nfl-team-snapshots-week-6.html">here</a>. ED)</i><br />
<br />
<span style="line-height: 1.6;">I've added a few more things to the Snapshots this week, namely, correlation values. I thought it might be interesting to see how the various Expected Points totals correlate with Margin of Victory and Win Percentage. For those of you unfamiliar with correlation (I know I was until I started getting into all this stat stuff): a correlation of 1.0 is perfect correlation, a correlation of 0.0 is no relationship. As far as Win Percentage, it makes sense that the offense and defense EPA correlations are the same - the way EPA works, for every point gained on offense, there is a point lost on defense (or vice versa). But I was surprised to see the higher Special Teams correlation. I'm not sure this means anything yet - the numbers will most likely regress as the season goes on. But it is interesting to note that the top three teams in terms of Margin of Victory - Denver, Kansas City, and Seattle - also have the top three special teams EPA scores.</span><br />
<a name='more'></a><br />
The following table shows EPA values per game through Week 6. Click on the table headers to sort. Enjoy.<br />
<u><b>KEY</b>:</u><br />
<b>MOV:</b> Margin of Victory ([points scored - points allowed]/games played)<br />
<b>EPA:</b> Total Expected Points Added (offense + defense + special teams + penalties)<br />
<b>OFF:</b> Offensive EPA (not including penalties)<br />
<b>DEF:</b> Defensive EPA (not including penalties)<br />
<b>SPT:</b> Special Teams EPA (kicking, punting and field goal plays)<br />
<b>PNLTY:</b> Penalties EPA (penalties for - penalties against)<br />
<b>WIN COR:</b> Correlation to W/L percentage<br />
<b>MOV COR:</b> Correlation to Margin of Victory<br />
<script src="https://dl.dropboxusercontent.com/u/57199593/SortTable/sorttable.js"></script><br />
<table class="sortable"><style type="text/css">
table thead td{
cursor:pointer;
border-collapse:collapse;
padding:2px 2px 2px 2px;
}
tr.border_bottom td {
border-bottom:1pt solid black;
}
tr.border_top td {
border-top:1pt solid black;
}
table.sortable tbody tr:nth-child(2n) td {
background: #E6E6E6;
}
table.sortable tbody tr:nth-child(2n+1) td {
background: #FFFFFF;
}
</style> <thead>
<tr> <td
style="text-align: left; font-weight: bold; background-color: rgb(51, 102, 102); color: white; width: 80px;">TEAM</td> <td
style="text-align: center; background-color: rgb(51, 102, 102); color: white; width: 46px; font-weight: bold;">W/L%</td> <td
style="font-weight: bold; text-align: center; background-color: rgb(51, 102, 102); color: white; width: 46px;">MOV</td> <td
style="font-weight: bold; text-align: center; background-color: rgb(51, 102, 102); color: white; width: 46px;">EPA</td> <td
style="font-weight: bold; text-align: center; background-color: rgb(51, 102, 102); color: white; width: 46px;">OFF</td> <td
style="font-weight: bold; text-align: center; background-color: rgb(51, 102, 102); color: white; width: 46px;">DEF</td> <td
style="font-weight: bold; text-align: center; background-color: rgb(51, 102, 102); color: white; width: 46px;">SPT</td> <td
style="font-weight: bold; text-align: center; background-color: rgb(51, 102, 102); color: white; width: 57px;">PNLTY</td> </tr>
</thead><tbody>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">ARI</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">-2.7</td> <td style="text-align: right; width: 46px;">-1.9</td> <td style="text-align: right; width: 46px;">-5.1</td> <td style="text-align: right; width: 46px;">2.1</td> <td style="text-align: right; width: 46px;">1.6</td> <td style="text-align: right; width: 57px;">-0.4</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">ATL*</td> <td style="width: 46px; text-align: right;">0.200</td> <td style="text-align: right; width: 46px;">-2.4</td> <td style="text-align: right; width: 46px;">-1.2</td> <td style="text-align: right; width: 46px;">10.2</td> <td style="text-align: right; width: 46px;">-10.3</td> <td style="text-align: right; width: 46px;">-2.2</td> <td style="text-align: right; width: 57px;">1.1</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">BAL</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">0.8</td> <td style="text-align: right; width: 46px;">0.7</td> <td style="text-align: right; width: 46px;">-3.2</td> <td style="text-align: right; width: 46px;">0.9</td> <td style="text-align: right; width: 46px;">1.0</td> <td style="text-align: right; width: 57px;">2.0</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">BUF</td> <td style="width: 46px; text-align: right;">0.333</td> <td style="text-align: right; width: 46px;">-3.5</td> <td style="text-align: right; width: 46px;">-4.1</td> <td style="text-align: right; width: 46px;">-3.4</td> <td style="text-align: right; width: 46px;">0.4</td> <td style="text-align: right; width: 46px;">-2.2</td> <td style="text-align: right; width: 57px;">1.1</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">CAR*</td> <td style="width: 46px; text-align: right;">0.400</td> <td style="text-align: right; width: 46px;">8.2</td> <td style="text-align: right; width: 46px;">8.2</td> <td style="text-align: right; width: 46px;">4.6</td> <td style="text-align: right; width: 46px;">3.1</td> <td style="text-align: right; width: 46px;">-0.3</td> <td style="text-align: right; width: 57px;">0.8</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">CHI</td> <td style="width: 46px; text-align: right;">0.667</td> <td style="text-align: right; width: 46px;">1.8</td> <td style="text-align: right; width: 46px;">3.7</td> <td style="text-align: right; width: 46px;">4.8</td> <td style="text-align: right; width: 46px;">1.8</td> <td style="text-align: right; width: 46px;">-0.7</td> <td style="text-align: right; width: 57px;">-2.3</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">CIN</td> <td style="width: 46px; text-align: right;">0.667</td> <td style="text-align: right; width: 46px;">1.7</td> <td style="text-align: right; width: 46px;">0.2</td> <td style="text-align: right; width: 46px;">0.5</td> <td style="text-align: right; width: 46px;">1.6</td> <td style="text-align: right; width: 46px;">-1.6</td> <td style="text-align: right; width: 57px;">-0.3</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">CLE</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">-1.2</td> <td style="text-align: right; width: 46px;">-0.6</td> <td style="text-align: right; width: 46px;">-0.2</td> <td style="text-align: right; width: 46px;">2.7</td> <td style="text-align: right; width: 46px;">-0.3</td> <td style="text-align: right; width: 57px;">-2.8</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">DAL</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">5.2</td> <td style="text-align: right; width: 46px;">4.9</td> <td style="text-align: right; width: 46px;">7.3</td> <td style="text-align: right; width: 46px;">-3.8</td> <td style="text-align: right; width: 46px;">2.6</td> <td style="text-align: right; width: 57px;">-1.2</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">DEN</td> <td style="width: 46px; text-align: right;">1.000</td> <td style="text-align: right; width: 46px;">17.8</td> <td style="text-align: right; width: 46px;">19.7</td> <td style="text-align: right; width: 46px;">20.1</td> <td style="text-align: right; width: 46px;">-4.6</td> <td style="text-align: right; width: 46px;">4.4</td> <td style="text-align: right; width: 57px;">-0.2</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">DET</td> <td style="width: 46px; text-align: right;">0.667</td> <td style="text-align: right; width: 46px;">3.7</td> <td style="text-align: right; width: 46px;">2.4</td> <td style="text-align: right; width: 46px;">4.1</td> <td style="text-align: right; width: 46px;">-1.6</td> <td style="text-align: right; width: 46px;">-0.2</td> <td style="text-align: right; width: 57px;">0.1</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">GB*</td> <td style="width: 46px; text-align: right;">0.600</td> <td style="text-align: right; width: 46px;">4.6</td> <td style="text-align: right; width: 46px;">6.6</td> <td style="text-align: right; width: 46px;">9.2</td> <td style="text-align: right; width: 46px;">-4.9</td> <td style="text-align: right; width: 46px;">1.0</td> <td style="text-align: right; width: 57px;">1.3</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">HOU</td> <td style="width: 46px; text-align: right;">0.333</td> <td style="text-align: right; width: 46px;">-11.8</td> <td style="text-align: right; width: 46px;">-11.6</td> <td style="text-align: right; width: 46px;">-5.2</td> <td style="text-align: right; width: 46px;">-2.7</td> <td style="text-align: right; width: 46px;">-3.4</td> <td style="text-align: right; width: 57px;">-0.2</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">IND</td> <td style="width: 46px; text-align: right;">0.667</td> <td style="text-align: right; width: 46px;">8.3</td> <td style="text-align: right; width: 46px;">8.1</td> <td style="text-align: right; width: 46px;">7.1</td> <td style="text-align: right; width: 46px;">-1.2</td> <td style="text-align: right; width: 46px;">0.2</td> <td style="text-align: right; width: 57px;">1.9</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">JAC</td> <td style="width: 46px; text-align: right;">0.000</td> <td style="text-align: right; width: 46px;">-21.3</td> <td style="text-align: right; width: 46px;">-22.0</td> <td style="text-align: right; width: 46px;">-12.6</td> <td style="text-align: right; width: 46px;">-7.4</td> <td style="text-align: right; width: 46px;">0.3</td> <td style="text-align: right; width: 57px;">-2.2</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">KC</td> <td style="width: 46px; text-align: right;">1.000</td> <td style="text-align: right; width: 46px;">14.5</td> <td style="text-align: right; width: 46px;">14.6</td> <td style="text-align: right; width: 46px;">-1.8</td> <td style="text-align: right; width: 46px;">10.2</td> <td style="text-align: right; width: 46px;">5.8</td> <td style="text-align: right; width: 57px;">0.4</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">MIA*</td> <td style="width: 46px; text-align: right;">0.600</td> <td style="text-align: right; width: 46px;">-0.6</td> <td style="text-align: right; width: 46px;">-0.3</td> <td style="text-align: right; width: 46px;">1.0</td> <td style="text-align: right; width: 46px;">-4.6</td> <td style="text-align: right; width: 46px;">3.0</td> <td style="text-align: right; width: 57px;">0.3</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">MIN*</td> <td style="width: 46px; text-align: right;">0.200</td> <td style="text-align: right; width: 46px;">-6.6</td> <td style="text-align: right; width: 46px;">-7.6</td> <td style="text-align: right; width: 46px;">1.0</td> <td style="text-align: right; width: 46px;">-8.3</td> <td style="text-align: right; width: 46px;">-0.3</td> <td style="text-align: right; width: 57px;">0.0</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">NE</td> <td style="width: 46px; text-align: right;">0.833</td> <td style="text-align: right; width: 46px;">4.7</td> <td style="text-align: right; width: 46px;">5.4</td> <td style="text-align: right; width: 46px;">-2.0</td> <td style="text-align: right; width: 46px;">2.0</td> <td style="text-align: right; width: 46px;">2.5</td> <td style="text-align: right; width: 57px;">2.9</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">NO</td> <td style="width: 46px; text-align: right;">0.833</td> <td style="text-align: right; width: 46px;">9.7</td> <td style="text-align: right; width: 46px;">10.8</td> <td style="text-align: right; width: 46px;">8.9</td> <td style="text-align: right; width: 46px;">0.7</td> <td style="text-align: right; width: 46px;">1.6</td> <td style="text-align: right; width: 57px;">-0.4</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">NYG</td> <td style="width: 46px; text-align: right;">0.000</td> <td style="text-align: right; width: 46px;">-17.7</td> <td style="text-align: right; width: 46px;">-19.6</td> <td style="text-align: right; width: 46px;">-8.4</td> <td style="text-align: right; width: 46px;">-7.4</td> <td style="text-align: right; width: 46px;">-5.3</td> <td style="text-align: right; width: 57px;">1.6</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">NYJ</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">-5.2</td> <td style="text-align: right; width: 46px;">-7.0</td> <td style="text-align: right; width: 46px;">-3.7</td> <td style="text-align: right; width: 46px;">0.9</td> <td style="text-align: right; width: 46px;">-0.9</td> <td style="text-align: right; width: 57px;">-3.3</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">OAK</td> <td style="width: 46px; text-align: right;">0.333</td> <td style="text-align: right; width: 46px;">-4.5</td> <td style="text-align: right; width: 46px;">-4.9</td> <td style="text-align: right; width: 46px;">-0.6</td> <td style="text-align: right; width: 46px;">-2.5</td> <td style="text-align: right; width: 46px;">0.0</td> <td style="text-align: right; width: 57px;">-1.8</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">PHI</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">-2.2</td> <td style="text-align: right; width: 46px;">-2.8</td> <td style="text-align: right; width: 46px;">9.7</td> <td style="text-align: right; width: 46px;">-4.3</td> <td style="text-align: right; width: 46px;">-3.8</td> <td style="text-align: right; width: 57px;">-0.8</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">PIT*</td> <td style="width: 46px; text-align: right;">0.200</td> <td style="text-align: right; width: 46px;">-5.6</td> <td style="text-align: right; width: 46px;">-6.8</td> <td style="text-align: right; width: 46px;">-2.6</td> <td style="text-align: right; width: 46px;">-4.3</td> <td style="text-align: right; width: 46px;">-1.4</td> <td style="text-align: right; width: 57px;">1.4</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">SAD</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">1.0</td> <td style="text-align: right; width: 46px;">-0.8</td> <td style="text-align: right; width: 46px;">7.8</td> <td style="text-align: right; width: 46px;">-9.1</td> <td style="text-align: right; width: 46px;">1.0</td> <td style="text-align: right; width: 57px;">1.1</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">SAF</td> <td style="width: 46px; text-align: right;">0.667</td> <td style="text-align: right; width: 46px;">4.5</td> <td style="text-align: right; width: 46px;">4.1</td> <td style="text-align: right; width: 46px;">1.5</td> <td style="text-align: right; width: 46px;">2.7</td> <td style="text-align: right; width: 46px;">0.3</td> <td style="text-align: right; width: 57px;">-0.4</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">SEA</td> <td style="width: 46px; text-align: right;">0.833</td> <td style="text-align: right; width: 46px;">10.5</td> <td style="text-align: right; width: 46px;">12.7</td> <td style="text-align: right; width: 46px;">4.8</td> <td style="text-align: right; width: 46px;">5.9</td> <td style="text-align: right; width: 46px;">3.8</td> <td style="text-align: right; width: 57px;">-1.8</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">STL</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">-2.2</td> <td style="text-align: right; width: 46px;">-1.8</td> <td style="text-align: right; width: 46px;">-1.4</td> <td style="text-align: right; width: 46px;">-5.5</td> <td style="text-align: right; width: 46px;">1.6</td> <td style="text-align: right; width: 57px;">3.6</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">TB*</td> <td style="width: 46px; text-align: right;">0.000</td> <td style="text-align: right; width: 46px;">-7.4</td> <td style="text-align: right; width: 46px;">-8.2</td> <td style="text-align: right; width: 46px;">-5.5</td> <td style="text-align: right; width: 46px;">0.5</td> <td style="text-align: right; width: 46px;">-2.1</td> <td style="text-align: right; width: 57px;">-1.1</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">TEN</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">2.2</td> <td style="text-align: right; width: 46px;">2.9</td> <td style="text-align: right; width: 46px;">1.3</td> <td style="text-align: right; width: 46px;">2.6</td> <td style="text-align: right; width: 46px;">-1.2</td> <td style="text-align: right; width: 57px;">0.2</td> </tr>
<tr> <td style="text-align: left; font-weight: bold; width: 80px;">WAS*</td> <td style="width: 46px; text-align: right;">0.200</td> <td style="text-align: right; width: 46px;">-7.2</td> <td style="text-align: right; width: 46px;">-8.4</td> <td style="text-align: right; width: 46px;">3.5</td> <td style="text-align: right; width: 46px;">-5.7</td> <td style="text-align: right; width: 46px;">-6.2</td> <td style="text-align: right; width: 57px;">0.0</td> </tr>
</tbody><tfoot>
<tr class="border_top"> <td style="text-align: left; font-weight: bold; width: 80px;">AVG</td> <td style="width: 46px; text-align: right;">0.500</td> <td style="text-align: right; width: 46px;">-0.1</td> <td style="text-align: right; width: 46px;">-0.1</td> <td style="text-align: right; width: 46px;">1.6</td> <td style="text-align: right; width: 46px;">-1.7</td> <td style="text-align: right; width: 46px;">0.0</td> <td style="text-align: right; width: 57px;">0.0</td> </tr>
<tr> <td style="width: 80px;"><span
style="font-weight: bold;">WIN COR</span></td> <td style="width: 46px; text-align: right;"></td> <td style="width: 46px; text-align: right;">0.88</td> <td style="width: 46px; text-align: right;">0.88</td> <td style="width: 46px; text-align: right;">0.53</td> <td style="width: 46px; text-align: right;">0.53</td> <td style="width: 46px; text-align: right;">0.71</td> <td style="width: 57px; text-align: right;">0.05</td> </tr>
<tr> <td style="width: 80px;"><span
style="font-weight: bold;">MOV COR</span></td> <td style="width: 46px; text-align: right;"></td> <td style="width: 46px;"></td> <td style="width: 46px;"></td> <td style="width: 46px; text-align: right;">0.71</td> <td style="width: 46px; text-align: right;">0.50</td> <td style="width: 46px; text-align: right;">0.67</td> <td style="width: 57px; text-align: right;">0.13</td> </tr>
</tfoot> </table></body><br />
<br />
<br />
<i>* Denotes teams that have had their bye and have played one less game than the week number. For explanations of Expected Points see <a href="http://www.advancednflstats.com/2010/01/expected-points-ep-and-expected-points.html">here</a>. For my methodology notes (boring stuff), see <a href="http://nflrearwindow.blogspot.com/p/methodology-notes.html">here</a>.</i><br />
</html>Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-62355663076101853302013-10-18T06:34:00.000-04:002013-10-18T06:34:31.732-04:00Conversion percentage VS win percentage<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjG9j9Xv4GHozaPXt8QUgDys79aci3SpBpgnwht9_B4N35MiXm2YCzc06gz5wEaKmQ2FkfHLceFJqhN43JxMdnUyDCmEQOTsrTJ4FjtgxlQKuJSyYgvqWo8l1A0sQoU9X1iNGCxxxfklbba/s1600/conversion.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjG9j9Xv4GHozaPXt8QUgDys79aci3SpBpgnwht9_B4N35MiXm2YCzc06gz5wEaKmQ2FkfHLceFJqhN43JxMdnUyDCmEQOTsrTJ4FjtgxlQKuJSyYgvqWo8l1A0sQoU9X1iNGCxxxfklbba/s400/conversion.jpg" /></a></div>by Andy Steiner<br />
<br />
<br />
The intent of this study is to see how much more likely strong teams are to convert third or fourth downs compared to weak teams.<br />
<br />
In this study I plot various conversion probabilities of 3rd and 4th downs, as a function of team strength (and distance to go). The measure of team strength that I use is the offense’s end of season winning percentage minus the defense’s end of season winning percentage. For the purpose of this study offensive conversion percentage is the number of times a team coverts a third and fourth down divided by the number of attempts to make that conversion. And of course the defensive conversion percentage is the number of times the defense holds on third and fourth down divided by the number of attempts.<br />
So my X and Y variables are:<br />
<br />
X =(Offense end of season winning percentage) – (Defense end of season winning percentage)<br />
<br />
Y = 1 (successful conversion or TD), 0 (failed conversion)<br />
<br />
I know there are much better ways to measure how good an offense or defense is than the end of season winning percentage; but I think this is a good first step. I also think it’s accessible. If a coach wants to get a better idea of how likely they might be to convert in a certain situation the win-loss records might be the first thing they think of. It’s probably how they think of their team strength – “we are a 12 and 4 team”. <br />
I then plot a linear fit from all the 1 and 0 y data points. This means I am assuming that the “true” probability of conversion is a linear function of team W-L record. <br />
<br />
I use data from 2002 to 2011 (regular season plus playoffs). I use most of the “normal football” assumptions, but not all. I was slightly more aggressive with time, allowing the 2nd quarter to be counted all the way up to 7 minutes left. The 4th quarter is excluded; all of the 1st and 3rd quarters are included. The plays are only included if the line of scrimmage is between a team’s own 25 and the opponents 20. The score differential is limited to 10 points. <a name='more'></a><br />
<br />
Below are the plots for 3rd and 4th down, for 1, 2, and 3 yards to go. (Note that the plots show win fraction instead of percentage). <br />
<br />
<b>4th and 1:</b><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBIKh0uHGKHLMHKEUBg14k5UImpHYcGNJLQH7c9ZYG5ZdYeg1RGjbIrAhPkT3-BOfDJD5hgWMcGACnA24XAZN0ShzvFPYezzBkI5U6slN9P-ZhKRkbzqsBh76WtWEVPXTLZ8_Bbl-XOkmj/s1600/4th1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBIKh0uHGKHLMHKEUBg14k5UImpHYcGNJLQH7c9ZYG5ZdYeg1RGjbIrAhPkT3-BOfDJD5hgWMcGACnA24XAZN0ShzvFPYezzBkI5U6slN9P-ZhKRkbzqsBh76WtWEVPXTLZ8_Bbl-XOkmj/s400/4th1.jpg" /></a></div><br />
<b>3rd and 1:</b><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1MoJzvt_CHnCfgi6yU-B2yyx05krELKz5WMlT0ELOdkzY75HSD0I-RhMXjybl-weisbN5E2n6smqv1mlTiOFyDRYZDlENcQvZGuIXAytXI10GDIEyJAGNDEjDr0lhZdRQryEh6miqPdve/s1600/3rd1.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1MoJzvt_CHnCfgi6yU-B2yyx05krELKz5WMlT0ELOdkzY75HSD0I-RhMXjybl-weisbN5E2n6smqv1mlTiOFyDRYZDlENcQvZGuIXAytXI10GDIEyJAGNDEjDr0lhZdRQryEh6miqPdve/s400/3rd1.jpg" /></a></div><br />
<b>4th and 2:</b><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEidSK7HDvzOf6mdCcYLFKH9mpJrvmn4Yq19T-IlnttYzDgEK2kic3Kszah9seyI8ys04kgrEaCJ6NF4Eg7cp_n8S0gGx9emgG0U-5Fh_O083IPSxLw0cziVPscG34fpIzh5dXVYb8JWBXXi/s1600/4th2.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEidSK7HDvzOf6mdCcYLFKH9mpJrvmn4Yq19T-IlnttYzDgEK2kic3Kszah9seyI8ys04kgrEaCJ6NF4Eg7cp_n8S0gGx9emgG0U-5Fh_O083IPSxLw0cziVPscG34fpIzh5dXVYb8JWBXXi/s400/4th2.jpg" /></a></div><br />
<b>3rd and 2:</b><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhavo5baJXyPmdeVNT0zaT7tJwS4YWbDlZTpGlrATIuHgf8UuvwbhGd8FzDs5vVlYiMeX-JfyUjXIkdwpL-iewqRxBJPsngCIjxAoJkMTF2oSaB0DBTpsc9fVk6_RTowT8EW1HXmANPPXxs/s1600/3rd10.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhavo5baJXyPmdeVNT0zaT7tJwS4YWbDlZTpGlrATIuHgf8UuvwbhGd8FzDs5vVlYiMeX-JfyUjXIkdwpL-iewqRxBJPsngCIjxAoJkMTF2oSaB0DBTpsc9fVk6_RTowT8EW1HXmANPPXxs/s400/3rd10.jpg" /></a></div><br />
<br />
<b>4th and 3:</b><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj6FCciLmDjmKOH9LUJPSj3-jatiKMr9L1gyBKE87CBxJ9xa-lpLKGnETBj3cQUh2uXQzpMe-Zfox0nsWOQFxRTHvR1CCsGf3U3flK_RI6jXPyLSNfQ4HCeRTniWTImrn954oiaoeiv20Aw/s1600/4th3.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj6FCciLmDjmKOH9LUJPSj3-jatiKMr9L1gyBKE87CBxJ9xa-lpLKGnETBj3cQUh2uXQzpMe-Zfox0nsWOQFxRTHvR1CCsGf3U3flK_RI6jXPyLSNfQ4HCeRTniWTImrn954oiaoeiv20Aw/s400/4th3.jpg" /></a></div><br />
<b>3rd and 3:</b><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi5JPoduRfrcPL9YJ1azTyjp9rqezSilvp8-68S2gzW0KFzYBcLgeUY6ioUjITT_eVDiCVXEeegOd30kn3WQaG1o7RRP_UADtXahS9-k0qDjyc0gOJqbFp2gLr25PTYyknPCp6wGnCPhyphenhyphenVj/s1600/3rd3.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi5JPoduRfrcPL9YJ1azTyjp9rqezSilvp8-68S2gzW0KFzYBcLgeUY6ioUjITT_eVDiCVXEeegOd30kn3WQaG1o7RRP_UADtXahS9-k0qDjyc0gOJqbFp2gLr25PTYyknPCp6wGnCPhyphenhyphenVj/s400/3rd3.jpg" /></a></div><br />
It appears that strong teams do end up converting at better rates…but most of the time not by that much. The most extreme is for 4th and 2, a difference of about 40% from the worst possible offensive record difference to the best possible offensive record difference (although no data has actually come from teams that extreme in record difference, it might be more appropriate to use a logistic fit when extrapolating that far out). 4th and 3 actually has a downward trend (good teams are actually less likely to convert), but lets just say that’s because of sample size. I haven’t tested the significance of that. There is a small bias, since teams that converted on any given conversion are more likely to have won the game, teams that failed are more likely to have lost. Correcting for this effect will only flatten the slope of these curves.<br />
Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-19997274410098859392012-12-31T23:24:00.000-05:002013-01-01T00:17:48.723-05:00Should JJ Watt win the MVP award?<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgovIdY3sOyjBL8StCN66S3tuDZXRcbWCdNVzaickh0SodgYtPXDwecopD-Q6x_dvs5CBip2AUTuxbLDAoBslN00C2BYG83JD5y0C-DQtMNLLoM9Ew1A3nURgI1g7gf5etVVAhvD9YkXnQQ/s1600/J+J+Watt+HHw7MAKm03_m.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="213" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgovIdY3sOyjBL8StCN66S3tuDZXRcbWCdNVzaickh0SodgYtPXDwecopD-Q6x_dvs5CBip2AUTuxbLDAoBslN00C2BYG83JD5y0C-DQtMNLLoM9Ew1A3nURgI1g7gf5etVVAhvD9YkXnQQ/s320/J+J+Watt+HHw7MAKm03_m.jpg" width="320" /></a></div>
by Joe Harris<br />
<h1>
<span class="Apple-style-span" style="font-size: 24px;">DPOY? Hands Down…</span></h1>
<div class="MsoNormal">
<span lang="EN-GB">Followers of ANS are probably likely to agree with the notion that JJ Watt is the run-away DPOY for this season, a large proportion of the mainstream media agree, and there is also a very good chance that he will, in fact, win. His main competitors were Aldon Smith and Von Miller who were both originally competing with Watt for the sacks title, but eventually lost out.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">The ‘conventional’ stats bear out the idea of JJ Watt as the DPOY:<o:p></o:p></span></div>
<table border="1" cellpadding="0" cellspacing="0" class="MsoTableLightShadingAccent1" style="border-collapse: collapse; border: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt; mso-table-layout-alt: fixed; mso-yfti-tbllook: 1184;"><tbody>
<tr style="height: 18.15pt; mso-yfti-firstrow: yes; mso-yfti-irow: -1;"> <td style="border-left: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 5;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Stat<o:p></o:p></span></b></div>
</td> <td colspan="2" style="border-left: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: 1.0pt; mso-border-color-alt: #4F81BD; mso-border-left-alt: .5pt; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-right-alt: .5pt; mso-border-style-alt: solid; mso-border-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: 1.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 97.85pt;" valign="top" width="98"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">JJ Watt (Hou)<o:p></o:p></span></b></div>
</td> <td colspan="2" style="border-left: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: 1.0pt; mso-border-color-alt: #4F81BD; mso-border-left-alt: .5pt; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-right-alt: .5pt; mso-border-style-alt: solid; mso-border-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: 1.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 97.9pt;" valign="top" width="98"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Aldon Smith (SF)<o:p></o:p></span></b></div>
</td> <td colspan="2" style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 97.9pt;" valign="top" width="98"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Von Miller (Den)<o:p></o:p></span></b></div>
</td> </tr>
<tr style="mso-yfti-irow: 0;"> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Sacks<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">20.5<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<sup>st</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">19.5<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">18.5<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3<sup>rd</sup><o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 1;"> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Tackles<o:p></o:p></span></b></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">69<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
</div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">50<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">55<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> </tr>
<tr style="mso-yfti-irow: 2;"> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Passes Defended<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">16<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">10<sup>th</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<br /></div>
<br />
<br /></td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<br /></div>
</td> </tr>
<tr style="mso-yfti-irow: 3;"> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Interceptions<o:p></o:p></span></b></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">0<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> </tr>
<tr style="mso-yfti-irow: 4;"> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Fumbles Forced<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">4<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">10<sup>th</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">22<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">6<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3<sup>rd</sup><o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 5;"> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Yards per Pass Attempt (Team)<o:p></o:p></span></b></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">6.7<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">7<sup>th</sup><o:p></o:p></span></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">6.1<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">6.4<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">5<sup>th</sup><o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 6; mso-yfti-lastrow: yes;"> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 168.45pt;" valign="top" width="168"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Yards per Rush Attempt (Team)<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.9pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">4.0<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">9<sup>th</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3.7<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3<sup>rd</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3.6<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.95pt;" valign="top" width="49"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2<sup>nd</sup><o:p></o:p></span></div>
</td> </tr>
</tbody></table>
<div class="MsoNormal">
<span lang="EN-GB" style="font-size: 9.0pt; line-height: 115%; mso-bidi-font-size: 11.0pt;">* The rank for each player was left blank if they did not come in the top 40 players<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">This shows Watt as a viable contender for DPOY, leading the other two in sacks, tackles and passes defended (where he ranks a ridiculous 10<sup>th</sup> among all defensive players). However, it is not quite clear cut as the other two both lead slightly better defences and Von Miller has more FF and an interception.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">Personally, I think the above table shows Watt as the clear winner when put into the context that he is a DE in a 3-4 scheme whereas the other two are both LBs in schemes designed to give them opportunities to rack up the glamor stats.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">The result starts to become clearer cut when we look at the Advanced Stats:<o:p></o:p></span></div>
<table border="1" cellpadding="0" cellspacing="0" class="MsoTableLightShadingAccent1" style="border-collapse: collapse; border: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt; mso-table-layout-alt: fixed; mso-yfti-tbllook: 1184;"><tbody>
<tr style="height: 18.15pt; mso-yfti-firstrow: yes; mso-yfti-irow: -1;"> <td style="border-left: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 5;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Stat<o:p></o:p></span></b></div>
</td> <td colspan="2" style="border-left: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: 1.0pt; mso-border-color-alt: #4F81BD; mso-border-left-alt: .5pt; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-right-alt: .5pt; mso-border-style-alt: solid; mso-border-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: 1.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 96.05pt;" valign="top" width="96"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">JJ Watt (Hou)<o:p></o:p></span></b></div>
</td> <td colspan="2" style="border-left: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: 1.0pt; mso-border-color-alt: #4F81BD; mso-border-left-alt: .5pt; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-right-alt: .5pt; mso-border-style-alt: solid; mso-border-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: 1.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 96.05pt;" valign="top" width="96"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Aldon Smith (SF)<o:p></o:p></span></b></div>
</td> <td colspan="2" style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 96.05pt;" valign="top" width="96"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Von Miller (Den)<o:p></o:p></span></b></div>
</td> <td style="border-right: none; border: solid #4F81BD 1.0pt; height: 18.15pt; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; mso-border-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">% adv<o:p></o:p></span></b></div>
</td> </tr>
<tr style="mso-yfti-irow: 0;"> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">+WPA<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.96<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<sup>st</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1.04<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<br /></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1.53<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">22<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">25%<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 1;"> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">+EPA<o:p></o:p></span></b></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">122.1<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<sup>st</sup><o:p></o:p></span></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">58.5<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">12<sup>th</sup><o:p></o:p></span></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">74.2<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">65%<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 2;"> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Success Count<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">109<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<sup>st</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">60<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<br /></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">65<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">32<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">4%<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 3;"> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Tackle Factor<o:p></o:p></span></b></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1.36<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">13<sup>th</sup><o:p></o:p></span></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">0.67<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">0.71<o:p></o:p></span></div>
</td> <td style="border-right: solid #4F81BD 1.0pt; border: none; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border: none; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">-13%<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 4;"> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">QB Hits<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">43<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<sup>st</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">24<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">4<sup>th</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">27<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-right: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">5<sup>th</sup><o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">34%<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 5; mso-yfti-lastrow: yes;"> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 135.45pt;" valign="top" width="135"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Defensive GWP (Team)<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">9<sup>th</sup><o:p></o:p></span></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2<sup>nd</sup><o:p></o:p></span></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<br /></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: solid #4F81BD 1.0pt; border-top: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-bottom-themecolor: accent1; mso-border-right-alt: solid #4F81BD .5pt; mso-border-right-themecolor: accent1; mso-border-right-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.05pt;" valign="top" width="48"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1<sup>st</sup><o:p></o:p></span></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; mso-border-left-alt: solid #4F81BD .5pt; mso-border-left-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 38.5pt;" valign="top" width="39"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">-<o:p></o:p></span></div>
</td> </tr>
</tbody></table>
<div class="MsoNormal">
<span lang="EN-GB" style="font-size: 9.0pt; line-height: 115%; mso-bidi-font-size: 11.0pt;">* The rank for each player was left blank if they did not come in the top 40 players<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">Here Watt completely blows away his competition. I also added a final column which shows Watt’s advantage over the second place in each category. For example, he has 65% <i style="mso-bidi-font-style: normal;">more</i> +EPA than the next player (who happens to be Von Miller). That’s insane. </span><br />
<a name='more'></a><span lang="EN-GB"><o:p></o:p></span></div>
<h2 style="margin-bottom: 6.0pt;">
<span lang="EN-GB">MVP? Maybe…<o:p></o:p></span></h2>
<div class="MsoNormal">
<span lang="EN-GB">It is at this point that we broaden our perspective and consider, not whether he should be DPOY (he should be), but whether he should be the MVP.<o:p></o:p></span></div>
<div class="MsoNormal">
<b style="mso-bidi-font-weight: normal;"><span lang="EN-GB">The Contenders: </span></b><span lang="EN-GB">Generally, the winner of the MVP award is either the QB with the most impressive season, a running back who broke 2,000 yards or a wide receiver who has had some sort of record-breaking season. So this season we have Matt Ryan, Adrian Peterson and Calvin Johnson. Matt Ryan may seem like a strange choice but he ranks 2<sup>nd</sup> in both WPA and EPA and is therefore a suitable choice for this analysis. The truth is that I could have easily selected a number of QBs.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">I am going to dismiss Adrian Peterson now. I am not going to argue that what he has done is not impressive. And even without considering his ACL it is extremely impressive: he lines up every week against teams who know he will run and yet he churned out 2,097 yards at 6.0 YPC. Like Watt – insane. But I am going to use the old argument that a great RB does not translate into wins for his team. Until this changes I don’t think a RB can be the ‘<a href="http://www.advancednflstats.com/2011/11/dont-pay-fortay.html" target="_blank">Most Valuable Player</a>’. <o:p></o:p></span></div>
<h4 style="margin-bottom: 6.0pt;">
<span lang="EN-GB">Methodology<o:p></o:p></span></h4>
<div class="MsoNormal">
<span lang="EN-GB">So… back to Ryan, Johnson and Watt. I am going to base my argument based on WPA and EPA only, using the concepts of ‘Above Average’ and ‘Above Replacement’. This compares each player to the average starter and best non-starter respectively. The key is the definition of starter.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">But first, here is how they shape up if we completely ignore their positions:<o:p></o:p></span></div>
<table border="1" cellpadding="0" cellspacing="0" class="MsoTableLightShadingAccent1" style="border-collapse: collapse; border: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt; mso-yfti-tbllook: 1184;"><tbody>
<tr style="mso-yfti-firstrow: yes; mso-yfti-irow: -1;"> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 5;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Player<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">WPA<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">EPA<o:p></o:p></span></b></div>
</td> </tr>
<tr style="mso-yfti-irow: 0;"> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Matt Ryan<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">4.87<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">178.8<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 1;"> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Calvin Johnson<o:p></o:p></span></b></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.71<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">107.3<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 2; mso-yfti-lastrow: yes;"> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">JJ Watt<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.96<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border-bottom: solid #4F81BD 1.0pt; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">122.1<o:p></o:p></span></div>
</td> </tr>
</tbody></table>
<div class="MsoNormal">
<span lang="EN-GB" style="font-size: 9.0pt; line-height: 115%; mso-bidi-font-size: 11.0pt;">* The stats for JJ Watt are +WPA and +EPA which are slightly different but I’ll ignore that for now<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">But of course, we do need to adjust for position. Now for Ryan the definition of starter is easy: the top 32 QBs by either WPA or EPA. The way I did this in practice was to take the top QBs until I had covered 512 (32x16) games played to account for some players getting injured and then replaced with others.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">For Calvin Johnson it is slightly harder, but I am going assume that every team plays with 2 WRs most of the time and so he gets compared to the top 64 WRs.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">For JJ Watt I am going to use two definitions. Firstly, and more restrictive, he should be compared to all DEs that also play in a 3-4 scheme. Secondly, he should be compared to the top 64 DEs (assuming two per team).<o:p></o:p></span></div>
<span lang="EN-GB" style="font-family: Calibri; font-size: 11.0pt; line-height: 115%; mso-ansi-language: EN-GB; mso-ascii-theme-font: minor-latin; mso-bidi-font-family: "Times New Roman"; mso-bidi-language: AR-SA; mso-bidi-theme-font: minor-bidi; mso-fareast-font-family: Calibri; mso-fareast-language: EN-US; mso-fareast-theme-font: minor-latin; mso-hansi-theme-font: minor-latin;"><br clear="all" style="mso-special-character: line-break; page-break-before: always;" /> </span> <br />
<div class="MsoNormal">
<br /></div>
<h4 style="margin-bottom: 6.0pt;">
<span lang="EN-GB">The Results<o:p></o:p></span></h4>
<table border="1" cellpadding="0" cellspacing="0" class="MsoTableLightShadingAccent1" style="border-collapse: collapse; border: none; mso-border-bottom-alt: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-alt: solid #4F81BD 1.0pt; mso-border-top-themecolor: accent1; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt; mso-yfti-tbllook: 1184;"><tbody>
<tr style="mso-yfti-firstrow: yes; mso-yfti-irow: -1;"> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 5;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Player<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">WPAA<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">EPAA<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">WPAR<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border-left: none; border-right: none; border-top: solid #4F81BD 1.0pt; mso-border-bottom-themecolor: accent1; mso-border-top-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 1; text-align: center;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">EPAR<o:p></o:p></span></b></div>
</td> </tr>
<tr style="mso-yfti-irow: 0;"> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Matt Ryan<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3.55<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">130.7<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">7.50<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">241.3<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 1;"> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">Calvin Johnson<o:p></o:p></span></b></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">1.71<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">73.8<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">3.02<o:p></o:p></span></div>
</td> <td style="border: none; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">104.2<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 2;"> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 68;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">JJ Watt vs. 3-4 DEs<o:p></o:p></span></b></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.54<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">107.0<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.95<o:p></o:p></span></div>
</td> <td style="background: #D3DFEE; border: none; mso-background-themecolor: accent1; mso-background-themetint: 63; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 64; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">121.7<o:p></o:p></span></div>
</td> </tr>
<tr style="mso-yfti-irow: 3; mso-yfti-lastrow: yes;"> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 154.0pt;" valign="top" width="154"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; mso-yfti-cnfc: 4;">
<b><span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">JJ Watt vs. all DEs<o:p></o:p></span></b></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.35pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.11<o:p></o:p></span></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">92.9<o:p></o:p></span></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">2.63<o:p></o:p></span></div>
</td> <td style="border-bottom: solid #4F81BD 1.0pt; border: none; mso-border-bottom-themecolor: accent1; padding: 0cm 5.4pt 0cm 5.4pt; width: 60.4pt;" valign="top" width="60"><div align="center" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: center;">
<span lang="EN-GB" style="color: #365f91; mso-themecolor: accent1; mso-themeshade: 191;">110.7<o:p></o:p></span></div>
</td> </tr>
</tbody></table>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">JJ Watt should definitely be in the conversation for MVP. By these numbers, he is ahead of Johnson but quite a long way behind Ryan in, even when we compare him to other 3-4 DEs.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">There are a couple or caveats to this table:<o:p></o:p></span></div>
<div class="MsoListParagraph" style="margin-bottom: 6.0pt; margin-left: 35.7pt; margin-right: 0cm; margin-top: 6.0pt; mso-list: l0 level1 lfo1; text-indent: -17.85pt;">
<!--[if !supportLists]--><span lang="EN-GB" style="mso-bidi-font-family: Calibri; mso-bidi-theme-font: minor-latin;"><span style="mso-list: Ignore;">1)<span style="font: 7.0pt "Times New Roman";"> </span></span></span><!--[endif]--><span lang="EN-GB">The fairest comparison for Watt is probably somewhere between 3-4 DEs and all DEs. When a player is putting up numbers like he is it is fairly safe to assume that the scheme is at least partly designed to allow that player to make big plays. And with a stats like +WPA and +EPA which only count positive contributions, this could make a big impact.<o:p></o:p></span></div>
<div class="MsoListParagraph" style="margin-bottom: 6.0pt; margin-left: 35.7pt; margin-right: 0cm; margin-top: 0cm; mso-list: l0 level1 lfo1; text-indent: -17.85pt;">
<!--[if !supportLists]--><span lang="EN-GB" style="mso-bidi-font-family: Calibri; mso-bidi-theme-font: minor-latin;"><span style="mso-list: Ignore;">2)<span style="font: 7.0pt "Times New Roman";"> </span></span></span><!--[endif]--><span lang="EN-GB">Using +WPA and +EPA is unfair against Watt as it does not allow other players to post negative scores. Ryan and Johnson both get compared to players who are producing negative wins and negative points. In WPAR, Ryan gets compared to Sanchez who managed to produce -2.63 wins.<o:p></o:p></span></div>
<div class="MsoListParagraph" style="margin-bottom: 6.0pt; margin-left: 35.7pt; margin-right: 0cm; margin-top: 0cm; mso-list: l0 level1 lfo1; text-indent: -17.85pt;">
<!--[if !supportLists]--><span lang="EN-GB" style="mso-bidi-font-family: Calibri; mso-bidi-theme-font: minor-latin;"><span style="mso-list: Ignore;">3)<span style="font: 7.0pt "Times New Roman";"> </span></span></span><!--[endif]--><span lang="EN-GB">Teams try to negate the impact of stars on the opposite team: RBs see 8-9 men in the box, WRs and pass rushers get double- or triple-teamed, CBs never have the ball thrown their way. But a QB has so many options, and so many ways to affect the game that it is almost impossible to target him specifically.<o:p></o:p></span></div>
<div class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -18.0pt;">
<!--[if !supportLists]--><span lang="EN-GB" style="mso-bidi-font-family: Calibri; mso-bidi-theme-font: minor-latin;"><span style="mso-list: Ignore;">4<span style="font: 7.0pt "Times New Roman";"> </span></span></span><!--[endif]--><span lang="EN-GB">The stats of offensive players are often complementary and they rely on the contributions of others. For example, a QB relies on the abilities of his receivers. Defensive players, however, are almost in competition with one another for stats as generally only one can make each play.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">Taking these caveats into account, I still come to the conclusion that the MVP should be a quarterback but it is a lot closer (personally, I think Peyton Manning should get it, but that’s another story). Watt should at least be in the conversation. As it currently stands, he is not even certain to win DPOY and nobody in the mainstream media would even consider him for MVP.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">Quarterbacks will always be the MVPs unless we have drastic change to the rulebook. As they touch the ball on almost every single offensive possession, they have the most opportunities to impact the game.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">But if there was ever a season to give a defensive player the MVP award, this is it.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">As an added extra – below are the charts for my calculations of WPAR, EPAA etc. for Ryan, Johnson and both JJ Watt scenarios. <span style="mso-spacerun: yes;"> </span>Watt should be fairly easy to spot.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<br />
<br />
<br />
<br />
<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsdIzuPZ69wUJU-wENSnUgq11eiwcLhHgSTb-JitHaDa_qLdlTWkMX_YzdeCPOVyvzwwih7LrkDS6MlP38vy2tILgdfEndkpJ5mDI9TT_Z6u99mvzDb8VcKbWfRIut6g0N7iqmOx1odWrD/s1600/mryan_wpa.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsdIzuPZ69wUJU-wENSnUgq11eiwcLhHgSTb-JitHaDa_qLdlTWkMX_YzdeCPOVyvzwwih7LrkDS6MlP38vy2tILgdfEndkpJ5mDI9TT_Z6u99mvzDb8VcKbWfRIut6g0N7iqmOx1odWrD/s320/mryan_wpa.jpg" width="320" /></a></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiuaTzXgJNnt6M_FrZ1esCS13ueJpGtqQZnLr90PqOb77OAb7bHwZclFqb8r0OR_4KM0fJTT5dgGsNnUa95UiY3qgNXj1Q5GyL-K0ga6RoR9BV-sVXmDs16XagAJFvWeNRWQrxNLDe6mKPR/s1600/mryan_epa.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiuaTzXgJNnt6M_FrZ1esCS13ueJpGtqQZnLr90PqOb77OAb7bHwZclFqb8r0OR_4KM0fJTT5dgGsNnUa95UiY3qgNXj1Q5GyL-K0ga6RoR9BV-sVXmDs16XagAJFvWeNRWQrxNLDe6mKPR/s320/mryan_epa.jpg" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkyzDNSBewC-EoA8WKAnqnIzzOrirdqsUCUrBPeqhhooaovu8YyvA2s1-IhxU6LlnCeQZrkdgEiFickzvyapDadgP-Alj-p1dCg3tLHniubpYpUwXWaaW75kSZoh5_gD_p0ojnLaLwIbGo/s1600/cjohnson_wpa.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkyzDNSBewC-EoA8WKAnqnIzzOrirdqsUCUrBPeqhhooaovu8YyvA2s1-IhxU6LlnCeQZrkdgEiFickzvyapDadgP-Alj-p1dCg3tLHniubpYpUwXWaaW75kSZoh5_gD_p0ojnLaLwIbGo/s320/cjohnson_wpa.jpg" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgZQPRS1USk83l6BMOSFc4e-F5LXLjGVLKIG8bz1Eioyfy_qwfFK3Eeri4aZGDQUutRH-tuvcp8-wGrqPCe0LEU_6-B7oLkx4UCaQ7qEb8wqadOHwpb9VDhyphenhyphenY6S4_LS-6q3DojyoWlB3sy/s1600/cjohnson_epa.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgZQPRS1USk83l6BMOSFc4e-F5LXLjGVLKIG8bz1Eioyfy_qwfFK3Eeri4aZGDQUutRH-tuvcp8-wGrqPCe0LEU_6-B7oLkx4UCaQ7qEb8wqadOHwpb9VDhyphenhyphenY6S4_LS-6q3DojyoWlB3sy/s320/cjohnson_epa.jpg" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTIO-JB3qOaM8kNdjDrJMRxT2rFgNotJrLrfEUias_NCqy_ZHcSxL0lXs8KHsp80zqiR6Btx6Nam3UXw1oobadYA1P7VHVZxSkkwYzzBeUjJaNwDuEu7rIq4tdZki17j5Pf7b7VBk72k0X/s1600/jjwatt_wpa_34_des.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTIO-JB3qOaM8kNdjDrJMRxT2rFgNotJrLrfEUias_NCqy_ZHcSxL0lXs8KHsp80zqiR6Btx6Nam3UXw1oobadYA1P7VHVZxSkkwYzzBeUjJaNwDuEu7rIq4tdZki17j5Pf7b7VBk72k0X/s320/jjwatt_wpa_34_des.jpg" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6wrhYirRALXuPBY6KV_pr1tVYnQZRSU7-Ltaci3KLXE_FB3zbge6K8-HNmlSw1erAYtJOYtJW4ri0b2AY9hFiEbzbVpKTxLMF3lDtq_EbVBq2H_y11CFnlgKBLpQ6jG6jBiDiWUBAxYts/s1600/jjwatt_epa_34_des.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6wrhYirRALXuPBY6KV_pr1tVYnQZRSU7-Ltaci3KLXE_FB3zbge6K8-HNmlSw1erAYtJOYtJW4ri0b2AY9hFiEbzbVpKTxLMF3lDtq_EbVBq2H_y11CFnlgKBLpQ6jG6jBiDiWUBAxYts/s320/jjwatt_epa_34_des.jpg" width="320" /></a></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj_aVo_i5FTs-XF0E_KO88n2rWanq3HrtV4eNuZrcUOFnxBj936l5tU8Eri0Arv-YkyliZiaPbKUlHE5cZlVcbX3VDta5l4kghiddHhaopyiTJrTezTu5CmfdTMOpcXhIz0isflfpmL6dvA/s1600/jjwatt_wpa_all_des.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj_aVo_i5FTs-XF0E_KO88n2rWanq3HrtV4eNuZrcUOFnxBj936l5tU8Eri0Arv-YkyliZiaPbKUlHE5cZlVcbX3VDta5l4kghiddHhaopyiTJrTezTu5CmfdTMOpcXhIz0isflfpmL6dvA/s320/jjwatt_wpa_all_des.jpg" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhyx9rmPowbFk7aQVZHeamNz6uvXF4436ItJsEQmGaldbcfic_oD3LZecvLeO2_aUcOjZO6iBcnhdam891CtaS2SS6n_C3mCu-JEe5dtrpn0FnG8Vg6Pk33j35cTjq_eeGYnd14eUw_ym7B/s1600/jjwatt_epa_all_des.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhyx9rmPowbFk7aQVZHeamNz6uvXF4436ItJsEQmGaldbcfic_oD3LZecvLeO2_aUcOjZO6iBcnhdam891CtaS2SS6n_C3mCu-JEe5dtrpn0FnG8Vg6Pk33j35cTjq_eeGYnd14eUw_ym7B/s320/jjwatt_epa_all_des.jpg" width="320" /></a></div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<br />
<br />
<!--EndFragment-->Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-62999317018037756072012-12-27T15:54:00.001-05:002012-12-29T01:29:47.971-05:00Wins above average: a statistical nightmareby Clark Heins<br />
<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><br />
<b>Introduction:</b> Davis Wylie (pen name of researcher Neil Paine), after much complicated math resulting in each QB‘s stats being “adjusted“ to 2006 levels (through a process known as “translation“, i.e., normalization without standard deviation, converted everything into a final stat “Wins Above Replacement Player” totals in his "The 100 Greatest QBs of the Modern Era” opus which he used to rank QBs. <br />
<br />
In football, there is no clearly established formula for determining WAR figures, but Football Outsiders originally estimated that a “Replacement Level” QB was some 13.7% less effective (valuable) than an “average” QB. This percentage was later changed to 13.3% and now rests at 12.5%. All these figures were arbitrary and consisted of some educated guesswork and “value judgments” about “players“ who never existed! It would have been much easier if Wylie had simply used the stat “Wins Above Average” which we can all understand instead of an incomprehensible abstract. <br />
<br />
The problem for me was converting these WAR totals to WAA so as to compare with Doug Drinen’s figures in his own WAA opus. <br />
<br />
<a name='more'></a><br />
<br />
Baseball has three recognized conversion formulas, but I could find none for football except a couple vague variations of Bill James‘ Pythagorean Theorem which, as statistician Zach Fein points out, has an error of between 1.2 to 1.4 games per team per season built into it---that‘s a pretty hefty error when dealing with a 16 game season. I reasoned that, at best, all I could do was approximate, but, by what process? <br />
<br />
I’m not a mathematician, but after some experimentation, I came up with a “best fit” equation which I felt, at least, got me in the ballpark---WAR - (11.75% x WAR) = WAA. Although the WAA totals for each QB are going to be infested with some degree of error, the actual statistical rankings of the QBs by Wylie should not change and that is what should really concern us. I’ve included each QB’s WAR totals, my 11.75% subtraction and the resultant approximate WAA totals, then broke down those totals per 16 game seasons. For those QBs who had tie games, I didn’t know what to do, so I’ve included figures with and without the tie games. Wylie’s top 41 QBs were reviewed.<br />
<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th>Wins above average (per 16 games)</th>
<th><br />
</th><th><span class="Apple-style-span" style="font-weight: normal;"></span><br />
<br />
<div style="margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px;"><b>Davis Wylie</b></div><br />
</th><th><br />
</th><th><br />
</th><th><span class="Apple-style-span" style="font-weight: normal;"></span><br />
<div style="text-align: right;"><div style="text-align: left;"><div style="margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px;"><b>Doug Drinen</b></div><br />
<br />
</th><th><br />
</th></tr>
<tr><th>Player</th><th>WAR</th><th>WAA</th><th>Per 16 games</th><th>WAA</th><th>Per 16 games</th></tr>
</thead><tbody>
<tr><td style="text-align: center;">Unitas</td><td>22.24</td><td>19.63</td><td>1.66</td><td>15</td><td>1.27</td></tr>
<tr><td style="text-align: center;">Young</td><td>19.1</td><td>16.86</td><td>1.72</td><td>17</td><td>1.73</td></tr>
<tr><td style="text-align: center;">Tarkenton</td><td>28.29</td><td>24.97</td><td>1.64</td><td>14.8</td><td>0.97</td></tr>
<tr><td style="text-align: center;">Marino</td><td>23.6</td><td>20.83</td><td>1.29</td><td>25.4</td><td>1.58</td></tr>
<tr><td style="text-align: center;">Montana</td><td>20.07</td><td>17.71</td><td>1.52</td><td>23.9</td><td>2.04</td></tr>
<tr><td style="text-align: center;">Staubach</td><td>16.54</td><td>14.6</td><td>1.78</td><td>16.1</td><td>1.97</td></tr>
<tr><td style="text-align: center;">Fouts</td><td>18.9</td><td>16.68</td><td>1.51</td><td>14.9</td><td>1.35</td></tr>
<tr><td style="text-align: center;">Elway</td><td>19.54</td><td>17.24</td><td>1.1</td><td>30.7</td><td>1.96</td></tr>
<tr><td style="text-align: center;">Anderson</td><td>20.07</td><td>17.71</td><td>1.59</td><td>-0.6</td><td>-0.05</td></tr>
<tr><td style="text-align: center;">Favre</td><td>17.69</td><td>15.61</td><td>0.97</td><td>25.7</td><td>1.41</td></tr>
<tr><td style="text-align: center;">Manning (2006)</td><td>15.93</td><td>14.06</td><td>1.43</td><td>35.2</td><td>2.95 (thru 2008)</td></tr>
<tr><td style="text-align: center;">Brady (2006)</td><td>8.17</td><td>7.21</td><td>1.09</td><td>27</td><td>3.38 (thru 2008)</td></tr>
<tr><td style="text-align: center;">Jurgensen</td><td>17.09</td><td>15.09</td><td>1.7</td><td>0.3</td><td>0.03</td></tr>
<tr><td style="text-align: center;">Dawson</td><td>16.54</td><td>14.6</td><td>1.47</td><td>5.6</td><td>0.56</td></tr>
<tr><td style="text-align: center;">Moon</td><td>16.55</td><td>14.61</td><td>1.1</td><td>5.5</td><td>0.41</td></tr>
<tr><td style="text-align: center;">Starr</td><td>14.45</td><td>12.75</td><td>1.26</td><td>4.8</td><td>0.47</td></tr>
<tr><td style="text-align: center;">Van Brocklin</td><td>15.13</td><td>13.35</td><td>2.11</td><td>14.8</td><td>2.34</td></tr>
<tr><td style="text-align: center;">Gabriel</td><td>16.25</td><td>14.34</td><td>1.51</td><td>2.8</td><td>0.29</td></tr>
<tr><td style="text-align: center;">Graham</td><td>10.44</td><td>9.21</td><td>1.89</td><td>9.6</td><td>1.97</td></tr>
<tr><td style="text-align: center;">Tittle</td><td>14.79</td><td>13.05</td><td>1.36</td><td>14.6</td><td>1.52</td></tr>
<tr><td style="text-align: center;">Bradshaw</td><td>12.51</td><td>11.04</td><td>1</td><td>12.9</td><td>1.17</td></tr>
<tr><td style="text-align: center;">Griese</td><td>13.29</td><td>11.73</td><td>1.18</td><td>1.1</td><td>0.11</td></tr>
<tr><td style="text-align: center;">Hadl</td><td>14.24</td><td>12.57</td><td>1.25</td><td>1.6</td><td>0.16</td></tr>
<tr><td style="text-align: center;">Brodie</td><td>13.67</td><td>12.06</td><td>1.21</td><td>7.6</td><td>0.76</td></tr>
<tr><td style="text-align: center;">Cunningham</td><td>13.47</td><td>11.89</td><td>1.33</td><td>15.5</td><td>1.73</td></tr>
<tr><td style="text-align: center;">Brunell 2006</td><td>13.54</td><td>11.95</td><td>1.2</td><td>-0.3</td><td>-.03 (thru 2008)</td></tr>
<tr><td style="text-align: center;">Layne</td><td>12.9</td><td>11.38</td><td>1.35</td><td>8.1</td><td>0.96</td></tr>
<tr><td style="text-align: center;">Morton</td><td>12.66</td><td>11.17</td><td>1.17</td><td>-4</td><td>-0.42</td></tr>
<tr><td style="text-align: center;">Hart</td><td>14.52</td><td>12.81</td><td>1.16</td><td>6</td><td>0.54</td></tr>
<tr><td style="text-align: center;">McNair</td><td>12.84</td><td>11.33</td><td>1.15</td><td>9.2</td><td>0.9</td></tr>
<tr><td style="text-align: center;">Simms</td><td>12.36</td><td>10.91</td><td>1.03</td><td>4.6</td><td>0.44</td></tr>
<tr><td style="text-align: center;">Esiason</td><td>12.75</td><td>11.25</td><td>1.01</td><td>5.1</td><td>0.46</td></tr>
<tr><td style="text-align: center;">Kelly</td><td>12.26</td><td>10.82</td><td>0.98</td><td>17.8</td><td>1.61</td></tr>
<tr><td style="text-align: center;">Namath</td><td>11.8</td><td>10.41</td><td>1.29</td><td>5</td><td>0.62</td></tr>
<tr><td style="text-align: center;">Aikman</td><td>11.03</td><td>9.73</td><td>0.86</td><td>4.4</td><td>0.39</td></tr>
<tr><td style="text-align: center;">Theismann</td><td>10.88</td><td>9.6</td><td>1.16</td><td>9.8</td><td>1.19</td></tr>
<tr><td style="text-align: center;">Stabler</td><td>10.64</td><td>9.39</td><td>0.96</td><td>18.9</td><td>1.93</td></tr>
<tr><td style="text-align: center;">Gannon</td><td>12</td><td>10.59</td><td>1.22</td><td>9.4</td><td>1.08</td></tr>
<tr><td style="text-align: center;">Morrall</td><td>10.38</td><td>9.16</td><td>1.4</td><td>0.9</td><td>0.14</td></tr>
<tr><td style="text-align: center;">Jones</td><td>10.39</td><td>9.17</td><td>1.48</td><td>5</td><td>0.81</td></tr>
<tr><td style="text-align: center;">McNabb (2006)</td><td>10.56</td><td>9.32</td><td>1.36</td><td>6.2</td><td>.70 (thru 2008)</td></tr>
</tbody></table></div></div></div><br />
<b>Conclusions:</b> Wylie and Drinen are the only two researchers to create either “Wins Above Replacement” or “Wins Above Average” totals for all the major QBs, thus a review of their efforts I feel is worthwhile. Obviously, there is quite a disparity between the figures they come up with. Initially, I thought that Wylie’s totals heavily favored the old-time QBs like Unitas, Dawson, Starr and Griese while Drinen’s totals heavily favored the modern QBs like Montana, Marino, Elway and Manning, but the more QBs I examined, the less obvious this trend became. As an example, Wylie’s totals favored modern QBs like McNair, Moon, Simms and Esiason while Drinen’s totals favored old-timers like Staubach, Graham, Tittle and Stabler. <br />
<br />
Then I went back and re-read the comments from readers when Drinen’s list originally came out (March 30, 2009). One blogger (“Brad O.”) seems to have hit the nail right on the head. He wrote, “Good QBs on good teams mostly rank very well. Good QBs on bad teams mostly don’t. Mediocre QBs on good teams do fine. And everyone without a lot of games played is pretty close to the middle.” Brad. O’s comments seem to strike most true with Sonny Jurgensen, Ken Anderson, and Tom Brady. Wylie gives both Jurgensen and Anderson very high totals while Drinen discounts them altogether---even to the extent of giving Anderson a negative total. Meanwhile, Wylie downgrades Brady while Drinen gives him a staggering total---far higher than any other WAA list I have ever seen. The exception to this observation is Mark Brunell who was a good QB on good teams, but is also given a negative total by Drinen.<br />
<br />
Part of the problems with Wylie and Drinen are their chosen methodologies. Wylie used numerous math equations (including those of ESPN’s Sean Lahman) upon numerous stats, to normalize all the QB's stats to 2006 levels. But, whenever you adjust stats, small errors are entered into the equations and those errors multiply like compound interest. Adjusted stats for the old-time QBs become unrealistic and tend to give the old-timers more credit than they deserve. At the same time, the modern QBs get less credit than they deserve as their “real” stats are pitted against undeserved “imaginary” stats. Despite the errors that have crept into Wylie’s research, I regard his overall statistical rankings as pretty decent and his totals certainly within the ballpark: 1. Van Brocklin 2. Graham 3. Staubach 4. Young 5. Jurgensen 6. Unitas 7. Tarkenton 8. Anderson 9. Montana 10. Gabriel 11. Fouts 12. Jones 13. Dawson 14. Manning (through 2006) 15. Morrall. Incredibly, Wylie disregarded his own statistical findings and, instead, based his final rankings on subjectivity! Unitas he ranked No. 1 because of his “historical importance”! Elway he ranked No. 5 despite the fact that, statistically, Elway was tied for 32nd out of the 41 QBs I examined!<br />
<br />
But, whatever the errors that were introduced by Wylie, those errors introduced by Drinen are much worst. Drinen’s entire research is based upon one stat---“increments of points given up on defense“. He utterly ignores offensive points scored and, in doing so, gives us only half the loaf. Worst, if he had chosen to use offensive point totals, their correlation (.73) to winning percentage is greater than are defensive points given up correlation to winning percentage (.71)---(P.S., Brian Burke’s correlation chart has these figures at .74 and .66.) There is also one other gigantic flaw in Drinen’s system. You see, he actually posted two WAA surveys---one for regular season starts (March 25, 2009) and another which included post-season starts (March 30, 2009). However, in his second study, he changed a few of the variables such as points given up on INT returns which he eliminated. To see how these changes in a few variables affected his WAA figures, we need only review those QBs who never started a post-season game. As examples, Sonny Jurgensen was given credit for 3.9 WAA in the first survey and 0.3 WAA in the second survey; Norm Snead was given credit for -9.6 WAA in the first survey and -14.3 WAA in the second; Joey Harrington had -10.2 WAA in the first survey and -12.4 WAA in the second. A few slight changes in variables affected the increments enough to make major changes in WAA! (P.S., I used Drinen’s results from his second survey for this posting so as coincide with Wylie’s inclusion of post-season games in his study. For some strange reason, Wylie actually didn‘t use the stats from post-season games; instead, he added bonus “Points Above Replacement“ which is a simple multiple of WAR, i.e., WAR = PAR/40. However, when you start to add “bonus points“, your equation becomes infused with personal bias). <br />
<br />
<br />
Burke has discounted any attempt to build a wins probability model based upon point spreads (January 21, 2007). He writes, “Models that use points scored or points allowed or variations of either, are no more analytical than Dan Fouts.” He refers to such attempts as the “Fouts Analysis”, i.e., “the team that scores the most points will win the game”. Burke concludes his article by writing: “We already know that the ability to score more points than another team leads to winning. The question is: What enables some teams to score more than others?” <br />
<br />
Drinen has used a reverse “Fouts Analysis”, i.e., “the team that gives up the fewest points will win the game”. As Burke suggests, both methods are predictive, but are not very analytical. The degree of error that Drinen enters into his calculations must be astronomical. Good QBs who played on good teams are too heavily rewarded while good QBs who played on bad teams are not rewarded at all. These are Drinen’s top 15 QBs in WAA: 1. Brady (thru 2008 season) 2. Manning (thru 2008 season) 3. Van Brocklin 4. Montana 5. Staubach 6. Graham 7. Elway 8. Stabler 9. Young 10. Cunningham 11. Kelly 12. Marino 13. Tittle 14. Favre (thru 2008 season) 15. Fouts. Although Drinen and Wylie agree on eight of the top 15 QBs, Drinen’s figures are all over the place with respect to many of the QBs and, often, are utterly illogical. For example, he has Starr, Jurgensen and Anderson totaling a measly 4.5 WAA for their combined careers---they had 12 NFL passing championships between them! Meanwhile, he gives Elway, who is a poster boy for being a slightly above average NFL QB, a staggering 30.7 WAA! <br />
We end this by pointing out one very salient comment that Sean Lahman made when Drinen’s list was first published. Lahman wrote, “I’m wondering if you think this raw data, even though it measures the QB’s team and not the QB himself, is a useful metric?” Drinen never replied.<br />
All football stats, including WAA figures, are the product of the team, not the QB. This, above all, we should remember.<br />
<br />
Footnote: Several years ago, Neil Paine (aka Davis Wylie) admitted that his “100 Greatest QBs” study was a “flawed monstrosity”. Indeed, he pulled it off the Internet. I’ve never agreed with that harsh assessment. Virtually all WAA surveys that I have examined have at least one very serious flaw attached to them---usually using stats like “Yards After Catch” or “Air Yards” which are not very accurate, nor are they officially recognized by the NFL, nor can they be applied universally---or using “Sacks” for which there are no official records before 1969 and, therefore can’t be universally applied to all the QBs throughout NFL history. After all, what is the use of any study that can’t include the likes of Graham, Unitas, Van Brocklin, Starr, Jurgensen and Tittle, etc. To be of any use, WAA models must use stats that are official and universal. Furthermore, they should be stats that relate well to the QB (i.e., Drinen’s “increments of defensive points allowed” stat has virtually nothing to do with the QB; stats like “adjusted yards per attempt” or “adjusted net yards per attempt“ are team oriented efficiency stats which, likewise, have little to do with the QB). Additionally, you would prefer to have a stat that correlates well to winning percentage. As an example, completion percentage has only a moderate correlation (.43) to winning percentage. On the other hand, TD pass percentage does correlate very well with winning percentage (.55), but the problem is that, while the QB has a great deal of control over completion percentage, many other factors, including luck and the skills of the receivers (as Burke points out), have much more influence over TD pass percentage than the QB. The problem, as it has always been, is separating the merits of the QB from the merits of his team---and doing so in an equitable manner. <br />
There are many other problems in creating a WAA model. As Burke illustrates with his August 2007 model which used “Air Yards“, running QBs, like Michael Vick, have a huge advantage if their running ability is factored into the equation (i.e., In Burke’s study of 2006 stats, Vick‘s “Wins Added Per 16 Games“ , based upon his passing stats alone, was -0.10, but when his rushing and fumble stats are included, his “Wins Added“ total zooms to 1.72! A non-running QB, like Tom Brady, saw his “Wins Added“ total precariously drop from .53 to .21. And a QB like Kurt Warner, who was a notorious fumbler, saw his “Wins Added“ total drop off the cliff---from .80 to -.51!). Fortunately, there have been few running QBs in league history like Vick and few fumblers like Warner. Strength of schedule is another factor difficult to account for. Probably the best way to estimate a QB’s career SOS is to review the number of winning teams that he has faced vs. career starts, but how to factor SOS into the equation is always problematic. For instance, in one of Doug Drinen’s SOS lists (March 30, 2009), his figures are seriously flawed because they are simple multiples of his WAA figures which are tragically flawed. <br />
<br />
Researcher Chase Stuart has his own version of SOS (the one used throughout PFR.com), but his SOS figures are based entirely upon two stats---’Average Passing Yards Per Attempt” and “Adjusted Passing Yards Per Attempt” (which has more problems associated with it than passer rating as it is also “weighted“ with bizarre “bonuses“ and “penalties“). Stuart refers to his system as “Morally Accurate”---whatever that means. As far as how to factor in the defenses that a QB faces over the course of his career, Football Outsiders David Lewin has noted that, “The quality of opponents’ defenses tends to even out over the course of a QB‘s career.” Likewise, on a yearly basis, Football Outsiders two passer rating systems (Value Over Average and Defensive VOA), exhibit very little change in overall QB rankings due to defensive factors. Also, football statistician Zach Fein has stated that offensive stats and their corresponding defensive stats have about the same correlation rates when it comes to winning percentage. But, that isn’t quite true because, if you look at Fein’s correlation charts (or those of Burke), virtually all offensive stats correlate better with winning percentage than their corresponding defensive stats. Essentially, defensive stats can be largely ignored while we concentrate our efforts on offensive stats. After all is considered and much discarded, I feel that the two key factors in any WAA model should be simple passing yards per attempt (without any penalties for sacks) and INT percentage as these are the factors that the QB has fairly decent control over, simple passing yards per attempt correlates very well with winning percentage (.58) although INT percentage has only a moderate correlation (.40) with winning percentage, and both of these stats are beneficial as they require no “weights”, no “value judgments”, no “bonuses”, no “penalties” and few “adjustments” other than normalization and standard deviation which must be used if you wish to compare QBs from different eras---which I think most of us do. Sacks and anything pertaining to sacks---such as “turnover ratio”--- should be avoided as the QB has very little control over sacks, data on sacks is sketchy at best, sack percentage has only a modest correlation (.38) to winning percentage and, as Elias warns us, many of the sacks that were counted as sacks in the old days (before 1981) would never be counted as sacks today. Additionally, there is no way of knowing what the QB was thinking when trapped for a loss behind the line of scrimmage---did he intend to pass or run? Sack totals and yards lost via sacks do not differentiate as to intent.<br />
<br />
<br />
As for the inclusion of “yards per attempt” over “completion percentage”, arguments rage on both sides. Yards per attempt correlates much better with winning percentage than completion percentage, but the QB has much more control over completion percentage than he has over yards per attempt. Essentially, it is a case of “pick your poison” as they are simple multiples of each other and, thus, one or the other must be excluded. Since we are most interested in WAA, I lean toward yards per attempt. Famed sports writers Allen Barra and George Ignatin, in their book “Football By The Numbers”, agree, “Passing numbers best correlated with winning are simple yards per pass attempt and INT percentage.” Also, there is another factor here---yards per attempt heavily favors the old-time QBs while INT percentage heavily favors the modern QBs---so a delicate balance is struck and an aspect of “fairness” is achieved. If you choose to use both completion percentage and INT percentage (as Burke does), your equation would be heavily tilted toward the modern QBs.<br />
<br />
Okay. according to the two ingredients of the formula for WAA that I am recommending, who should be the best QBs with respect to WAA? Well here are the top ten QBs of all-time in “Simple Yards Per Attempt“: Luckman, Van Brocklin, Rodgers, Newton, Young, Warner, Romo, Roethlisberger, Ed Brown, and Starr. Here are the top ten QBs of all-time in “INT Percentage“: Rodgers, Brady, O‘Donnell, McNabb, Bradford, Garcia, Flacco, Brunell, Garrard, and Matt Ryan. Clearly, Aaron Rodgers should have a substantial lead over all other QBs. Steve Young and Matt Schaub are the only other QBs who place among the top 20 in both categories. <br />
<br />
But, we immediately run into another problem. Just because Rodgers has the lowest INT percentage in NFL history, it doesn’t mean that he was the best of all-time because his raw stats are not era adjusted. As an example, let’s take a look at Neil O’Donnell who has the lowest INT percentage among retired QBs (2.11%). After era adjusting O’Donnell’s INT percentage relative to league average (3.29%) from 1991-2003, he still finishes in the No. 2 spot (relative to average). Researcher Kiran Rasaretnam. points out that the No. 1 spot belongs to Roman Gabriel who starts out in 68th place in career interception percentage (3.31%), but the league average during his career (1962-77) was a whopping 5.34%---thus jumping Gabriel 67 places to the top spot among retired QBs relative to league averages. What I’m trying to point out is that raw WAA figures are useless unless we are able to unbiasedly adjust them by era. Ditto for “Yards Per Attempt”. However, even that is a problem because, as we have seen with Wylie, the process of “ forward normalization” makes the old-time QBs look a lot better than they actually were. <br />
<br />
As a recent example, researcher Rupert Patrick normalized the passer ratings of all the QBs in an article for the PFRA. His top three in “normalized passer rating” were Graham, Luckman and Baugh. Inexcusably, Patrick included Graham’s bloated AAFC stats--- so Graham can be ignored, but do you really think that Luckman and Baugh were better than Manning and Brady? If we reversed the process---normalized in a backward direction, the old-time QBs would look inept in comparison to the modern QBs. Therefore, normalization is useless without going one step further---standard deviation. Even the innocent looking process of “standard deviation” has a glaring flaw. It depends entirely upon there being tough competition between passers from the same era. The best example would be Sammy Baugh---over his long career, his only competition came from Sid Luckman. Thus, Baugh, in standard deviation studies, is always ranked among the top 5 passers of all-time based upon his extraordinarily high standard deviation of league passer rating means. But it’s a false positive because his nearest and only competition---Luckman, when confronted with standard deviation, dropped like a rock--- and, currently, is ranked outside the top 35 QBs of all-time in this same category!<br />
<br />
One thing we should always be mindful of. Whenever possible, “adjustments” to real stats should be avoided unless they are absolutely necessary. “Adjustments” have become the play things of modern times, but that doesn’t mean that we should trust them. Usually, ”adjustments” are the enemy as they often reflect the “value judgments“ and, thus, the bias of the researcher. Whenever you hear the word “value” in anyone’s ranking system---run for the hills. Regressions are particularly unfaithful as their variables and exponents can be manipulated in any manner which is favorable to the researcher’s desire to embellish whatever argument he is trying to make. It is ratios and percentages of “real” stats that should be embraced in any statistical analysis as they, in contrast to artificially contrived stats like “Wins Above Replacement“, do not discriminate. Failure to realize this is what flawed Davis Wylie’s study and has flawed many similar studies.<br />
<br />
Ref: Barra, Allen & George Ignatin, “Football By The Numbers, 1986, Prentice Hall.<br />
Burke, Brian, “The Fouts Analysis”, Jan. 21, 2006. <br />
Ibid., “QB Wins Added II”, July 23, 2007.<br />
Ibid., “QB Wins Added (With Rushing)”, August 2007.<br />
Drinen, Doug, “Adjusting QB Win-Loss Records, Part I”, PFR.com blog, March 25, 2009.<br />
Ibid., “Ranking the QBs---Schedule & Weather Adjustments’, PFR.com blog, Aug. 12, 2009. <br />
Ibid., “Adjusting QB Win-Loss Records, Part II’, PFR.com blog, March 30, 2009.<br />
Fein, Zach, “”Looking At Win Correlations, Part I”, The Sporting Truth.com. <br />
Ibid., “How NFL Statistics Lead To Wins Part II: Quantifying Player Stats”, Bleacher Reports, March 25, 2009. <br />
Paine, Neil, “If Aikman Was Romo”, PFR.com blog, Aug. 25, 2009. <br />
Ibid., “The 100 Greatest QBs of The Modern Era”, ArmchairQB.com.<br />
Patrick, Rupert, “Normalized Passer Rating”, In “Coffin Corner”, Vol 33, No. 3, PFRA 2011.<br />
Rasaretnam, Kiran, “The Importance of Interceptions (Or Lack Thereof)”, Feb. 6, 2009.<br />
Stuart, Chase, “Rearview Adjusted Yards Per Attempt, PFR.com blog, Aug. 23, 2007.<br />
<br />
Unknownnoreply@blogger.com1tag:blogger.com,1999:blog-5204092591876211047.post-64582586603960037462012-12-20T00:06:00.000-05:002012-12-20T08:59:44.228-05:00Kelly Criterion on 4th down<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgPqjnMF8HaELK7j5Vh4AiOLXw-eCF8VIjKrKUyQubJ4N9XLPmdz93xaXGE3fIFndbC1UgVeBzjQ-G_qCaS_hoAgP7R4oG8xnN6yse-c5FEwPnoXNGcQXBydlzU6sYGSJYaaru2gPNvFe-s/s1600/lottery.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="124" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgPqjnMF8HaELK7j5Vh4AiOLXw-eCF8VIjKrKUyQubJ4N9XLPmdz93xaXGE3fIFndbC1UgVeBzjQ-G_qCaS_hoAgP7R4oG8xnN6yse-c5FEwPnoXNGcQXBydlzU6sYGSJYaaru2gPNvFe-s/s320/lottery.jpg" width="170" /></a></div>
by Tunesmith<br />
It's 4th and 1 from your opponent's 43-yard line. You're up 3 points, and there is 5:16 remaining in the 1st quarter. Should you go for it?<br />
<br />
According to the <a href="http://wp.advancednflstats.com/4thdncalc1.php">4th Down Calculator</a>, the answer appears clear. Based on history, there is an estimated 74% chance of converting a 4th down in that scenario. Success yields 0.68 WPA; punting yields 0.61 WPA, and failure yields 0.55 WPA.<br />
<br />
These odds tell you that on average, it is a good decision to go for it - just the same as on average you'll make money if you take a bet with those odds and that probability of winning. The "Expected Value" (EV) in this scenario is 3.62. This means that on average, you will gain .0362 WPA by going for it.<br />
<br />
However, average doesn't always cut it. Because if it's not certain, you could still lose. <br />
<br />
EV enthusiasts often object to that observation, but let's briefly consider an alternate scenario. Pretend that you come across a certain state lottery. For $1, you have a chance of winning $500,000,000 profit. And your chances of winning are 1 in 350,000,000. (Also pretend, for the sake of argument, that there's a new identical lottery every second, and there can't be multiple winners in a round.) Since 500 > 350, those are good odds. Say you can play only once. Should you buy a ticket? What if you could play multiple times, or buy multiple tickets? Should you spend your $5,000 in hard-earned savings on lottery tickets?<br />
<a name='more'></a>The answer is, of course, no. If you buy one ticket, you'll probably lose. If you spend $5,000 on one lottery, you are still more than 99.99% likely to lose. If you spend five MILLION dollars on lottery tickets, you are still roughly 99% likely to lose. In all those cases, you're very likely to exhaust all your bankroll before you can reach the expected value, unless you are already extremely rich. And this is all true even though the lottery game has an obviously positive EV.<br />
<br />
So clearly, a positive EV isn't enough. What else do we have to factor in if we make a decision based on EV? This illustrates two key points about Expected Value:<br />
• There has to be an expectation of multiple rounds, probably very many.<br />
• You have to be able to afford the ideal bet.<br />
<br />
To calculate the ideal bet, one tool to use is the Kelly Criterion. And in a normal bet, if you bet too big, you might lose enough of your bankroll that you can't bet again in a later round. If you are faced with a +EV scenario, such as a bet with good odds, the Kelly Criterion tells you how much you should bet as a percentage of your bankroll. The Kelly Criterion formula is (pb - q) / b. p and q are the odds of success and failure, respectively. b is the odds. The reason the Kelly Criterion works is because it is mathematically calibrated to maximize one's expected growth rate. It will eventually outperform every other strategy of how to bet when the odds are in your favor.<br />
<br />
So how could this be used for football? Well, a football team wants to maximize their "football dominance", as in their chances of winning. Let's look again at the 4th-and-1 situation described above. Treating the punt as the default, risk-free outcome, the 4th-down calculation is in effect considering a bet, where you bet .06 WPA (failure) for a .07 WPA profit (success). The odds become 7/6.<br />
<br />
The calculation becomes ((0.74 * 7/6) - 0.26) / (7/6) = 51.7% In other words, in a bet with those odds and chances of winning, you should feel comfortable betting 51.7% of your bankroll - or less, to be conservative. But NOT more, because it can exhaust the bankroll too quickly. In fact, if you bet more than the Kelly Criterion suggests, your average expected growth will be negative even when the odds are in your favor!<br />
<br />
So if you're John Fox facing 4th and 1 from Baltimore's 43-yard line, and your Broncos are up 3 points, and there is 5:16 remaining in the 1st quarter, you should feel comfortable betting 51% of your bankroll. But what is a football coach's bankroll?<br />
<br />
That's tougher to gauge. Maybe a bankroll is defined as how many times a coach can make (and fail) a controversial football decision before being fired or losing credibility. That could make sense, because a secure coach would feel more latitude to make risky decisions than one that is on the hot seat. After all, "no one ever got fired for punting on 4th down", as the saying goes.<br />
<br />
But maybe the bankroll is something else. Let's look again at what Expected Value really means. It means that on average, your results will be in line with Expected Value. If you miss some early on, that's okay, because you'll catch up later. It will average out in the long run. However, the long run is cold comfort if you miss while on the verge of the playoffs at 10-6, and "catch up" during a pointless 5-11 season.<br />
<br />
The real rational goal of a football coach is to maximize the chances of winning *each* particular football game. If that is what the coach is trying to maximize, then the bankroll could be described as how much influence a coach has over one particular game. They are trying to convert their influence into WPA. And while EV assumes the presence of a long run, in reality, a coach's influence over a particular game is rather limited. One or two failures might be sufficient to guarantee a loss.<br />
<br />
This gives new insight into why a coach might *justifiably* want to punt the ball even if the EV suggests he should go for it. And it doesn't rely on the common explanations of momentum, or gut feeling, or unquantifiable "context". It shows that if a coach's goal is to use Expected Value to maximize the odds of winning *each game*, the coach's "bankroll" of "coaching decisions" might not be large enough to justify taking the bet. After all, if there might only be one +EV 4th-down scenario in the game, that would be betting 100% of the bankroll. Additionally, to be reasonably sure that it is a safe bet, the coach would have to feel comfortable that they face a high enough number of "rounds" to have a reasonable chance of reaching their EV.<br />
<br />
Even beyond the bankroll, when we're talking about the context of one game, we're starting to run afoul of one of the main requirements in paying attention to EV: The need for multiple rounds.<br />
<br />
Whipping out the old probability calculator, we can see that our 74% bet has a high bar to clear. <br />
• To be 99% sure that you will eventually win a 74% bet, you'd have to face the scenario not once or twice, but four times. And even then, if you lost the first three times and won the fourth, you would still be "under water" in terms of EV.<br />
• To be 99% sure that you will break even in terms of EV (this just means a net positive, not that you will average your EV of 3.62 WPA points), you'd have to face the scenario eight times.<br />
• To be only 90% sure that you will eventually reach cumulative EV (that's 3.62 WPA points for each round), you'd have to face the scenario sixteen times.<br />
<br />
From *our* perspective, as stats admirers and football fans, we are looking at it in the context of many coaches, many plays, many seasons - many rounds. Our "bankroll" is effectively infinite and there is no cost if we're wrong, so we're right that plays should always be called in accordance to EV. But when you're a coach looking at it in terms of 1-2 seasons of employment, or just one game's worth of plays, it really does change the equation in completely valid ways. The next time you see a coach choose to kick on 4th down even when the +EV says otherwise, he might actually be making a probabilistically valid decision.Unknownnoreply@blogger.com7tag:blogger.com,1999:blog-5204092591876211047.post-57240595559937737352012-12-11T11:30:00.004-05:002012-12-11T11:30:46.538-05:001st Down Game Theory: Equilibrium and Exploitable Strategiesby Mike Sommers<br />
<br />
You are faced with a first and 10 on your own 20 yardline, what percentage of the time should you run vs pass? You are on the 40 yardline, what percentage do you run vs pass?<br />
<br />
<b>Equilibrium Strategy</b><br />
This is a problem that is solvable, but it depends upon your objectives. I used average NFL data. The average pass attempt yields about 11.6 yards per catch with a 60.5% completion rate. I rounded this down to 11 yards and 60% completion rate. The average rush attempt yields 4.36 yards (2011 data) I rounded this down to 4 yards. Now if you approach the problem as an “equilibrium” strategy, your goal is actually to reduce the expected effect on the play to no change in score either way. For those familiar with “EP” (expected points), this doesn’t mean that the EP result would be zero, but that over the long run, the EP would not increase or decrease from it’s current levels. That is, no change in expectation of how many points you score, so if your expected points on first and 10 is .34, using an equilibrium strategy, it will remain .34. This is based upon the assumption that in the very long run, the opponents will either adapt or correctly anticipate how to adapt to exploit whatever strategy you come forward with, so the best plan is to just produce “average” results”. I don’t believe this to be true, but the equilibrium strategy is still valid as a “base strategy”.<a name='more'></a><br />
<br />
By taking this approach, your opponent cannot easily exploit you, and if you effectively neutralize the offense and defense on both sides, your chances of winning are based entirely on execution except for the moments of the game that you deviate from the strategy. If you have an average team vs another average team, with this gameplan, and equal “variance” your win percentage will approach 50% over the long run. This means that if a run play puts you in a situation where you expect to lose about 0.05 expected points, and a pass gains .35, you need to run 5 times for every 1 pass or pass 1/6 or 16.667 percent and rush 5/6 or 83.33% of the time. This will “balance everything out” in the sense that the net gain or loss from any play is zero therefore you will not lose or gain, nor will your opponent if he is average. The equilibrium is a base strategy, from which you can occasionally deviate from in order to exploit an edge, but the strategy on its own if run on both offense and defense, would neutralize to give you a 50% chance of winning vs. an average opponent. <br />
<br />
Why would you do this? The GMs and owners would like such a strategy so they can evaluate talent based on a neutral or “average” offense. Your QB should get the league average if the strategy is designed on offense to replicate the strategy. Additionally, if you also neutralize the opponent to “average” on defense and have an offensive strategy that does the same, the game will be close and competitive. A competitive, closely thought game is something the owner wants because it’s good for ticket sales, and allows him to remain competitive for a cheap price. From a coaches perspective, an “equilibrium” strategy is neither good nor bad, but it may serve you well to conceal a more effective higher yielding strategy which you may revert to once you pick up on tendencies or “tells” by your specific opponent that you can exploit. <br />
<br />
In theory, if you pass too often or run too often, your opponent should be able to recognize it and change his strategy on a given down and distance in a given situation. If you try to deviate from “equilibrium” in theory you become exploitable. It’s possible that NFL defenses are far away from equilibrium and unable to adjust effectively, if you believe this to be the case, you should go with a more aggressive “exploitative strategy”.<br />
<br />
<b>Exploitative Strategy</b><br />
The alternative is an “exploitative strategy” where you force the opponent to try to balance out the advantages. Well actually, a pure exploitative strategy would ONLY do either a run play or a pass play in a situation, never a balance. However, this method does use a balance and manages risk by distributing the frequency of the play proportionally by the degree of success. This is more easily approached when BOTH strategy yields positive results. If for example, a pass attempt yielded .30 expected net points and a rush attempt yielded .15, you would pass 2/3rds of the time or .30/.45 or 66.67% and rush .15/.45= 33.33%. If one play was negative that same formula would suggest over 100% of the time and negative a percentage of the time. It would suggest borrowing from your run plays to pass. This is impossible without borrowing from another situation in which the situation is flipped, and impractical.<br />
<br />
Neither of these strategies can be formed accurately 100% of the time based on “average” expectations because sometimes you have positive expectations from either a run or a pass, other times you have negative expectations for either, and sometimes you have positive expectations for both. Equilibrium strategy only works when one is negative, and exploitative strategies only work when both are positive. Otherwise, you will get a number over 100% when running calculation. However, if we take the situation where a run strategy is negative, we can simply only choose to pass if we are using an exploitative strategy. Or we can choose an aggressive balance in situations that suggest more than 100% of either one. I went with a 90% of any one when the data suggests over 100% and 10% to compose the other side.<br />
<br />
I constructed a table. From the tables I constructed graph charts.<br />
Finally I used a weighted average of 50% for each strategy and produced a chart combining the two. Here are the results of the strategy charted by yardline on first down and 10.<br />
<br />
The number on the X axis represent from a player’s own given yardline (with 90 yardline representing opponents 10 yardline)<br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh9o7RXqqdaPEEl-YCH3-qoQR6sMixfkEgAavovSsbqllhLIcmWPFROZVAepwDJ7yIM6lbCqVKS3OAIuQ6NpQl5q6BbMFvj94I7yLZfo2pI-6eVQuCMMoVJXqcvAD6CTODPhPF6FV6shUyw/s1600/strategy+chart.jpg" imageanchor="1" style="margin-left:1em; margin-right:1em"><img border="0" height="356" width="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh9o7RXqqdaPEEl-YCH3-qoQR6sMixfkEgAavovSsbqllhLIcmWPFROZVAepwDJ7yIM6lbCqVKS3OAIuQ6NpQl5q6BbMFvj94I7yLZfo2pI-6eVQuCMMoVJXqcvAD6CTODPhPF6FV6shUyw/s400/strategy+chart.jpg" /></a></div><br />
Near the goal line I took 50% of the value from having the ball on the 99 yardline and 50% of 7 points the value of a touchdown plus extra point.<br />
The real distribution of a play is less predictable than for a pass play, 60% of the time the play results in exactly 11 yards and 40% it results in zero yards… and for a run play 100% of the time it results in a 4 yard gain. It would be a much more complex problem if I wanted to really accurately model it and consider the percentage breakdown and include the probability that the given play lands on each individual yardline and weight the expected points by the probability of the event and add them all up. But theoretically if the 11 yard averages is typically only 5 yards but skewed by a bunch of really long plays for 7 points it could drastically change the expected points per pass attempt and resulting strategy.<br />
<br />
For those wondering, the reason the exploitative and equilibrium strategy are sometimes the same is because for example the expected point gain from a passing attempt might be .02 to a rush attempt of -.2 so you would need 10 passing attempt to equal 1 rushing attempt for equilibrium, but an exploitative strategy would also be a very heavy percentage of pass, if not 100%; so both might be around 90% in this case.<br />
Unknownnoreply@blogger.com3tag:blogger.com,1999:blog-5204092591876211047.post-19739077859030936252012-12-11T11:16:00.000-05:002012-12-11T14:38:12.344-05:00When to sacrifice yards for situationby Mike Sommers<br />
<br />
In "A Response To Brian Burke’s Washington Post Article", I stated that a team would actually be better served coming up short of the first down on 1st down. They would be better off setting up a 2nd and short than 1st and 10, unless they were able to surpass the threshold of 4 yards beyond the first down marker. All of these stats are based on normal teams who typically punt on 4th down. If they planned to go for it more optimally on 4th down, I suspect they would need even more than 4 yards to justify getting a conversion.<br />
Before I go on about the exceptions, I thought it would be useful to get a bit more specific about the situations in which a 1st down conversion is not better than a 2nd and short.<br />
Here is a graph and table of the expected points given the situation. While any 1st and 10 is more favorable than a 2nd and 3, a 2nd and 1 would still be 5 yards better than a 1st and 10. In other words, a 2nd and 1 on your own 29 yard-line is worth more expected points than a 1st and 10 on the 34.<br />
<a name='more'></a><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgpVF6POHcnVxfXnxR8K3iAcR6T81MthvV_USgfHKwD-MOlhSrwh0Y6I7kXvJRa98YgQ_XtMnScOcSqpP7rKCKyIDZwkVkwkUA5QD3HSXgwX2NVKMXgKOwaBcE3hjvcBDepL0_ZmsHVFqcB/s1600/sommers1.jpg" imageanchor="1" style="margin-left:1em; margin-right:1em"><img border="0" height="243" width="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgpVF6POHcnVxfXnxR8K3iAcR6T81MthvV_USgfHKwD-MOlhSrwh0Y6I7kXvJRa98YgQ_XtMnScOcSqpP7rKCKyIDZwkVkwkUA5QD3HSXgwX2NVKMXgKOwaBcE3hjvcBDepL0_ZmsHVFqcB/s400/sommers1.jpg" /></a></div><br />
I personally believe that if teams would go for it more optimally (more often), you would see a near parallel relationship and one that would look something like this (note line in red).<br />
<br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhXnW3FwXigPxLQkAiSrlFyqiMgBZc1uJYBBZok4-oetv4umWhOEiCTYBiNySDnUvglM-mVwG4AbUWgiC3bFii5-5foHhSjH61YbYdDtFahGQLHg-Lqp5w9gDULEU0BT1oqnmfjv8wyMc-p/s1600/sommers2.jpg" imageanchor="1" style="margin-left:1em; margin-right:1em"><img border="0" height="243" width="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhXnW3FwXigPxLQkAiSrlFyqiMgBZc1uJYBBZok4-oetv4umWhOEiCTYBiNySDnUvglM-mVwG4AbUWgiC3bFii5-5foHhSjH61YbYdDtFahGQLHg-Lqp5w9gDULEU0BT1oqnmfjv8wyMc-p/s400/sommers2.jpg" /></a></div><br />
I suspect intentionally going down to make a 2nd and 2 would be worth about 7 yards past the first down marker (for teams that go for it on 4th down). I suspect that a 2nd and 1 would be worth about 10 yards beyond the 1st down.<br />
<br />
The Win Probability model doesn’t match the conclusions of the Expected Points model. I find it strange that a Win Probability could remain the same while the expected points is greater, but maybe the model is based on field position and time left more than anything.<br />
<br />
Another interesting situation I want to look at is around the goal line. Initially I thought that perhaps first and 10 at the 15 yardline was better than a 1st and 10 at the 10. The rational was that they could convert and be left with 4 additional downs, and the defense is less congested allowing wider zones to throw to. While this may be true, in terms of however this EP model was constructed, it is not. However, the slope of the line flattens out. While every yard still increases your value, the rate of its increase decays as you approach the goal line.<br />
<br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj2kozeRMidiUSk3A0e7X_TuXHd1SVQteLm6XrQsuY-S_gl4b1Ex8fuFiZwRN6AUZ6kzzLmVndFi6Yoio_Tt2QfTEDwaiOjPWb7GXiRMv3IAVoVZ6OPvXzD1ARo30sHKVRK65_bYz3Q2NEV/s1600/sommers3.jpg" imageanchor="1" style="margin-left:1em; margin-right:1em"><img border="0" height="168" width="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj2kozeRMidiUSk3A0e7X_TuXHd1SVQteLm6XrQsuY-S_gl4b1Ex8fuFiZwRN6AUZ6kzzLmVndFi6Yoio_Tt2QfTEDwaiOjPWb7GXiRMv3IAVoVZ6OPvXzD1ARo30sHKVRK65_bYz3Q2NEV/s400/sommers3.jpg" /></a></div><br />
When QBs should simply “give up” on converting on 2nd down is what I touched upon briefly and wanted to get into more in depth. I will have to delay that one more post as it will contain a lot of important concepts I want to get into. For now just consider that AFTER the ball is snapped and play develops, all bets are off. As Mike Tyson said “Everyone has a plan, until they get hit”. As a play develops, the odds of conversion change. As information changes, the odds change as well. Statistically these situations are referred to as “variable change” and will be the subject of a future post.<br />
Unknownnoreply@blogger.com2tag:blogger.com,1999:blog-5204092591876211047.post-17360727842385505092012-11-05T12:25:00.000-05:002012-11-05T12:36:44.855-05:00Are punters getting better?<style type="text/css">.nobrtable br { display: none }</style><br />
<div class="nobrtable"><html><br />
<head><br />
<title><br />
Google Visualization API Sample<br />
</title><br />
<script src="http://www.google.com/jsapi" type="text/javascript"></script><br />
<script type="text/javascript">
google.load('visualization', '1', {packages: ['corechart']});
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['season','net','gross'],
['2002',34.4,40.1],
['2003',34.5,40.4],
['2004',35.9,41.3],
['2005',36.6,41.6],
['2006',36.8,42.8],
['2007',36.4,42.3],
['2008',37.2,43.1],
['2009',37.8,43.2],
['2010',37.1,42.8],
['2011',38.2,43.9]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('season')).
draw(data, {curveType: "none",
title: 'Yards Per Punt (Adjusted for Field Position)',
width: 600, height: 400,
vAxis: {minValue: 30, title: 'Yards'},
hAxis: {slantedText: true, title: 'Season'},
legend:{position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','2002-2006','2007-2011'],
[35,22.3,22.0],
[36,22.5,24.6],
[37,25.1,24.7],
[38,25.1,25.7],
[39,26.4,26.1],
[40,26.4,28.1],
[41,27.4,28.3],
[42,27.9,29.7],
[43,29.8,30.3],
[44,30.0,31.3],
[45,31.7,31.6],
[46,31.2,32.3],
[47,31.3,34.1],
[48,33.4,33.5],
[49,33.8,34.8],
[50,33.8,35.2],
[51,34.5,35.3],
[52,35.5,36.7],
[53,36.6,36.8],
[54,35.2,37.5],
[55,37.0,38.1],
[56,38.4,38.0],
[57,37.9,39.2],
[58,37.1,39.1],
[59,37.5,38.8],
[60,37.4,40.2],
[61,38.6,41.4],
[62,38.9,40.4],
[63,38.5,40.2],
[64,37.9,40.1],
[65,37.4,40.5],
[66,37.8,41.8],
[67,38.0,39.9],
[68,38.8,40.9],
[69,38.9,39.6],
[70,39.3,41.2],
[71,38.7,39.5],
[72,38.0,40.6],
[73,38.8,40.8],
[74,39.1,40.3],
[75,39.0,40.6],
[76,38.3,40.4],
[77,39.3,41.4],
[78,40.1,41.0],
[79,38.2,40.6],
[80,38.3,40.6],
[81,38.7,40.7],
[82,39.1,41.8],
[83,37.5,41.1],
[84,38.9,41.3],
[85,40.8,42.3],
[86,40.0,41.5],
[87,41.5,40.4],
[88,40.4,43.4],
[89,38.4,41.3],
[90,41.4,40.7],
[91,39.2,42.6],
[92,39.6,40.0],
[93,37.2,40.4],
[94,41.3,40.6],
[95,42.8,39.3],
[96,38.7,41.2],
[97,37.4,42.9],
[98,35.6,37.4],
[99,39.3,39.5]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('compare')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Net Yards by Field Position 2002-2006 vs. 2007-2011',
vAxis: {minValue: 30, title: 'Net Yards'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['season','net','gross'],
['2002',37.0,42.0],
['2003',36.5,42.1],
['2004',38.0,43.5],
['2005',38.9,43.4],
['2006',39.2,45.0],
['2007',38.8,44.6],
['2008',39.7,45.7],
['2009',40.5,46.0],
['2010',39.2,45.3],
['2011',40.7,47.0]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('season1')).
draw(data, {curveType: "none",
title: 'Yards Per Punt (>65 Yards from Endzone)',
width: 600, height: 400,
vAxis: {minValue: 30, title: 'Yards'},
hAxis: {slantedText: true, title: 'Season'},
legend:{position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['season','net','gross'],
['2002',34.4,40.9],
['2003',34.9,41.3],
['2004',36.9,42.0],
['2005',38.0,43.1],
['2006',38.0,44.0],
['2007',37.4,43.6],
['2008',38.0,44.3],
['2009',38.4,44.0],
['2010',38.2,43.9],
['2011',39.1,44.7]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('season2')).
draw(data, {curveType: "none",
title: 'Yards Per Punt (Between 50 and 65 Yards from Endzone)',
width: 600, height: 400,
vAxis: {minValue: 30, title: 'Yards'},
hAxis: {slantedText: true, title: 'Season'},
legend:{position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['season','net','gross'],
['2002',28.2,34.3],
['2003',29.2,35.3],
['2004',29.3,34.9],
['2005',29.4,35.1],
['2006',29.6,35.7],
['2007',29.3,35.0],
['2008',30.1,35.2],
['2009',30.5,35.3],
['2010',30.5,35.0],
['2011',31.0,35.3]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('season3')).
draw(data, {curveType: "none",
title: 'Yards Per Punt (Between 35 and 50 Yards from Endzone)',
width: 600, height: 400,
vAxis: {minValue: 30, title: 'Yards'},
hAxis: {slantedText: true, title: 'Season'},
legend:{position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','2002-2006 seasons','2007-2011 seasons'],
[35,0.331,0.395],
[36,0.321,0.211],
[37,0.245,0.293],
[38,0.280,0.191],
[39,0.235,0.296],
[40,0.279,0.238],
[41,0.260,0.231],
[42,0.262,0.200],
[43,0.245,0.195],
[44,0.308,0.167],
[45,0.238,0.204],
[46,0.247,0.200],
[47,0.309,0.138],
[48,0.186,0.212],
[49,0.218,0.214],
[50,0.217,0.217],
[51,0.257,0.207],
[52,0.213,0.168],
[53,0.185,0.223],
[54,0.185,0.164],
[55,0.154,0.194],
[56,0.142,0.197],
[57,0.111,0.165],
[58,0.099,0.134],
[59,0.070,0.120],
[60,0.064,0.115],
[61,0.068,0.118],
[62,0.035,0.059],
[63,0.035,0.058],
[64,0.020,0.037],
[65,0.009,0.038],
[66,0.019,0.043],
[67,0.015,0.020],
[68,0.015,0.020],
[69,0.004,0.008],
[70,0.007,0.015],
[71,0.003,0.010],
[72,0.000,0.007],
[73,0.000,0.000],
[74,0.004,0.004],
[75,0.000,0.000],
[76,0.000,0.003],
[77,0.000,0.008],
[78,0.000,0.000],
[79,0.000,0.000],
[80,0.000,0.003],
[81,0.000,0.006],
[82,0.000,0.005],
[83,0.000,0.000],
[84,0.000,0.000],
[85,0.000,0.000],
[86,0.000,0.000],
[87,0.000,0.000],
[88,0.000,0.000],
[89,0.000,0.000],
[90,0.000,0.000],
[91,0.000,0.000],
[92,0.000,0.000],
[93,0.000,0.000],
[94,0.000,0.000],
[95,0.000,0.000],
[96,0.000,0.000],
[97,0.000,0.000],
[98,0.000,0.000],
[99,0.000,0.000]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('touchback')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Touchback Probability by Field Position',
vAxis: {title: '% of Punts', format: '#,###%'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','2002-2006 seasons','2007-2011 seasons'],
[35,0.393,0.368],
[36,0.349,0.247],
[37,0.340,0.318],
[38,0.343,0.280],
[39,0.288,0.264],
[40,0.264,0.300],
[41,0.257,0.230],
[42,0.250,0.280],
[43,0.281,0.184],
[44,0.210,0.215],
[45,0.284,0.207],
[46,0.204,0.167],
[47,0.161,0.251],
[48,0.245,0.147],
[49,0.198,0.179],
[50,0.192,0.174],
[51,0.171,0.142],
[52,0.201,0.198],
[53,0.180,0.160],
[54,0.137,0.176],
[55,0.166,0.132],
[56,0.190,0.137],
[57,0.155,0.151],
[58,0.172,0.169],
[59,0.112,0.072],
[60,0.102,0.137],
[61,0.101,0.126],
[62,0.152,0.135],
[63,0.089,0.128],
[64,0.094,0.120],
[65,0.112,0.089],
[66,0.127,0.095],
[67,0.081,0.082],
[68,0.100,0.075],
[69,0.113,0.113],
[70,0.110,0.129],
[71,0.097,0.105],
[72,0.073,0.123],
[73,0.099,0.138],
[74,0.097,0.096],
[75,0.083,0.124],
[76,0.115,0.090],
[77,0.110,0.070],
[78,0.091,0.108],
[79,0.088,0.122],
[80,0.108,0.123],
[81,0.067,0.112],
[82,0.122,0.133],
[83,0.083,0.082],
[84,0.051,0.114],
[85,0.080,0.068],
[86,0.060,0.071],
[87,0.089,0.062],
[88,0.108,0.110],
[89,0.121,0.105],
[90,0.096,0.075],
[91,0.101,0.147],
[92,0.099,0.058],
[93,0.067,0.076],
[94,0.140,0.163],
[95,0.169,0.040],
[96,0.118,0.000],
[97,0.029,0.043],
[98,0.113,0.174],
[99,0.076,0.106]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('downed')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Downed Probability by Field Position',
vAxis: {title: '% of Punts', format: '#,###%'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','2002-2006 seasons','2007-2011 seasons'],
[35,0.168,0.163],
[36,0.184,0.402],
[37,0.315,0.278],
[38,0.271,0.397],
[39,0.321,0.326],
[40,0.351,0.383],
[41,0.358,0.361],
[42,0.339,0.396],
[43,0.362,0.512],
[44,0.321,0.430],
[45,0.380,0.436],
[46,0.350,0.448],
[47,0.343,0.381],
[48,0.380,0.415],
[49,0.340,0.341],
[50,0.312,0.346],
[51,0.326,0.347],
[52,0.271,0.347],
[53,0.307,0.262],
[54,0.247,0.206],
[55,0.195,0.284],
[56,0.227,0.264],
[57,0.162,0.228],
[58,0.206,0.180],
[59,0.185,0.205],
[60,0.210,0.201],
[61,0.192,0.155],
[62,0.142,0.141],
[63,0.164,0.173],
[64,0.187,0.195],
[65,0.162,0.151],
[66,0.123,0.147],
[67,0.147,0.129],
[68,0.123,0.171],
[69,0.199,0.138],
[70,0.125,0.107],
[71,0.179,0.143],
[72,0.148,0.151],
[73,0.127,0.147],
[74,0.149,0.165],
[75,0.184,0.131],
[76,0.125,0.136],
[77,0.122,0.109],
[78,0.150,0.131],
[79,0.171,0.109],
[80,0.142,0.134],
[81,0.141,0.121],
[82,0.085,0.121],
[83,0.091,0.143],
[84,0.143,0.139],
[85,0.110,0.160],
[86,0.112,0.090],
[87,0.208,0.082],
[88,0.074,0.155],
[89,0.142,0.102],
[90,0.127,0.180],
[91,0.081,0.143],
[92,0.076,0.149],
[93,0.162,0.080],
[94,0.084,0.050],
[95,0.104,0.123],
[96,0.152,0.090],
[97,0.095,0.075],
[98,0.133,0.069],
[99,0.019,0.000]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('faircatch')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Fair Catch Probability by Field Position',
vAxis: {title: '% of Punts', format: '#,###%'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'top'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','% of punts'],
[35,0.362],
[36,0.266],
[37,0.269],
[38,0.235],
[39,0.266],
[40,0.258],
[41,0.246],
[42,0.231],
[43,0.220],
[44,0.238],
[45,0.221],
[46,0.223],
[47,0.223],
[48,0.199],
[49,0.216],
[50,0.217],
[51,0.232],
[52,0.191],
[53,0.204],
[54,0.175],
[55,0.174],
[56,0.170],
[57,0.138],
[58,0.116],
[59,0.095],
[60,0.089],
[61,0.093],
[62,0.047],
[63,0.046],
[64,0.029],
[65,0.023],
[66,0.031],
[67,0.017],
[68,0.017],
[69,0.006],
[70,0.011],
[71,0.007],
[72,0.004],
[73,0.000],
[74,0.004],
[75,0.000],
[76,0.002],
[77,0.004],
[78,0.000],
[79,0.000],
[80,0.001],
[81,0.003],
[82,0.002],
[83,0.000],
[84,0.000],
[85,0.000],
[86,0.000],
[87,0.000],
[88,0.000],
[89,0.000],
[90,0.000],
[91,0.000],
[92,0.000],
[93,0.000],
[94,0.000],
[95,0.000],
[96,0.000],
[97,0.000],
[98,0.000],
[99,0.000]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('touchbacka')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Touchback Probability by Field Position (2002-2011)',
vAxis: {title: '% of Punts', format: '#,###%'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'none'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','% of punts'],
[35,0.381],
[36,0.298],
[37,0.329],
[38,0.311],
[39,0.276],
[40,0.282],
[41,0.243],
[42,0.265],
[43,0.233],
[44,0.212],
[45,0.245],
[46,0.185],
[47,0.206],
[48,0.195],
[49,0.188],
[50,0.183],
[51,0.157],
[52,0.200],
[53,0.170],
[54,0.157],
[55,0.149],
[56,0.164],
[57,0.153],
[58,0.170],
[59,0.092],
[60,0.119],
[61,0.114],
[62,0.143],
[63,0.109],
[64,0.107],
[65,0.100],
[66,0.111],
[67,0.081],
[68,0.088],
[69,0.113],
[70,0.119],
[71,0.101],
[72,0.098],
[73,0.118],
[74,0.096],
[75,0.103],
[76,0.103],
[77,0.090],
[78,0.099],
[79,0.105],
[80,0.115],
[81,0.090],
[82,0.127],
[83,0.083],
[84,0.082],
[85,0.074],
[86,0.065],
[87,0.076],
[88,0.109],
[89,0.113],
[90,0.085],
[91,0.124],
[92,0.078],
[93,0.071],
[94,0.152],
[95,0.106],
[96,0.058],
[97,0.036],
[98,0.144],
[99,0.091]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('downeda')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Downed Probability by Field Position (2002-2011)',
vAxis: {title: '% of Punts', format: '#,###%'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'none'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
<script type="text/javascript">
function drawVisualization() {
// Create and populate the data table.
var data = google.visualization.arrayToDataTable([
['field pos','% of punts'],
[35,0.165],
[36,0.293],
[37,0.296],
[38,0.334],
[39,0.325],
[40,0.367],
[41,0.362],
[42,0.371],
[43,0.440],
[44,0.377],
[45,0.408],
[46,0.400],
[47,0.366],
[48,0.397],
[49,0.341],
[50,0.333],
[51,0.338],
[52,0.312],
[53,0.285],
[54,0.228],
[55,0.242],
[56,0.248],
[57,0.196],
[58,0.194],
[59,0.197],
[60,0.208],
[61,0.174],
[62,0.143],
[63,0.170],
[64,0.192],
[65,0.157],
[66,0.135],
[67,0.139],
[68,0.148],
[69,0.170],
[70,0.116],
[71,0.162],
[72,0.149],
[73,0.138],
[74,0.158],
[75,0.157],
[76,0.131],
[77,0.117],
[78,0.142],
[79,0.141],
[80,0.139],
[81,0.131],
[82,0.103],
[83,0.118],
[84,0.142],
[85,0.135],
[86,0.102],
[87,0.145],
[88,0.115],
[89,0.122],
[90,0.155],
[91,0.113],
[92,0.114],
[93,0.122],
[94,0.067],
[95,0.113],
[96,0.121],
[97,0.085],
[98,0.101],
[99,0.009]
]);
// Create and draw the visualization.
new google.visualization.LineChart(document.getElementById('faircatcha')).
draw(data, {curveType: "none",
width: 600, height: 400,
title: 'Fair Catch Probability by Field Position (2002-2011)',
vAxis: {title: '% of Punts', format: '#,###%'},
hAxis: {slantedText: false, title: 'Yardline (Punted From)',gridlines: {color: 'white'}},
legend: {position: 'none'}}
);
}
google.setOnLoadCallback(drawVisualization);
</script><br />
</head><br />
<body><br />
</body><br />
</html><br />
</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf82qVboPVecQrCDIPpaIdWmaBvIr-9EikNcUB1hEOWBulTUzdqOOebk4VpvQnIfDK3QxhMhFVIskKGiDdd0hpMSFNrCIJ3Uxzps80QquH0-VjC1aW50ye7IOXDuWlK6TbSQCBFJxzNz9K/s1600/punter.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf82qVboPVecQrCDIPpaIdWmaBvIr-9EikNcUB1hEOWBulTUzdqOOebk4VpvQnIfDK3QxhMhFVIskKGiDdd0hpMSFNrCIJ3Uxzps80QquH0-VjC1aW50ye7IOXDuWlK6TbSQCBFJxzNz9K/s320/punter.jpg" width="213" /></a><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf82qVboPVecQrCDIPpaIdWmaBvIr-9EikNcUB1hEOWBulTUzdqOOebk4VpvQnIfDK3QxhMhFVIskKGiDdd0hpMSFNrCIJ3Uxzps80QquH0-VjC1aW50ye7IOXDuWlK6TbSQCBFJxzNz9K/s1600/punter.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><span class="Apple-style-span" style="color: black;"><br />
</span></a></div><span class="Apple-style-span" style="-webkit-text-decorations-in-effect: none; clear: left; color: black; margin-bottom: 1em; margin-right: 1em;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf82qVboPVecQrCDIPpaIdWmaBvIr-9EikNcUB1hEOWBulTUzdqOOebk4VpvQnIfDK3QxhMhFVIskKGiDdd0hpMSFNrCIJ3Uxzps80QquH0-VjC1aW50ye7IOXDuWlK6TbSQCBFJxzNz9K/s1600/punter.jpg" imageanchor="1" style="clear: left; margin-bottom: 1em; margin-right: 1em;">by Michael Beuoy</a></span><br />
<b><span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Punts</span></b><span style="line-height: 1;"><br />
The second most unloved play in the NFL (behind the <a href="http://www.advancednflstats.com/2012/11/the-extra-point-must-go.html">extra point </a>and, possibly, the Blaine Gabbert pass). When they show a punt on DirecTV's Redzone Channel, Andrew Siciliano actually apologizes, as if it were an errant f-bomb that made it past their tape delay.</span><br />
<br />
The purpose of this post is to show some statistical love for this less glamorous element of the game. Much has been made of the <a href="http://www.advancednflstats.com/2012/09/kickers-are-getting-better-and-better.html" target="_blank">improvement in field goal accuracy</a> over the years. Do we see a similar improvement in punting? What I found is that punters <i>are</i> improving, having added about 4 net yards to their punts over the past ten years.<br />
<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Data</span><br />
<span style="line-height: 1;">For this analysis, I used the </span><span class="Apple-style-span" style="font-size: small; font-weight: normal;"><a href="http://www.advancednflstats.com/2010/04/play-by-play-data.html" target="_blank">play by play data</a></span><span class="Apple-style-span" style="font-size: small; font-weight: normal;"> Brian Burke posts on his site, looking at seasons 2002 through 2011. From the fields and the play description, I was able to parse out which plays were punts, as well as the following data fields:</span><br />
<div><ul><li>Field Position (where the team punted from)</li>
<li>Gross Yards (how far the kick went)</li>
<li>Net Yards</li>
<li>Result - Did the play end in a touchback, fair catch, downed by the kicking team, muff, return, or block?</li>
<li>Penalty Yards (if any) assessed on the punt</li>
</ul><div>I only focused on "normal" punts for this analysis, meaning I excluded any punts that were blocked or that somehow resulted in the punting team retaining possession. If a punt had to be rekicked due to penalty, I am only counting the second "official" punt.<a name='more'></a></div><div><br />
</div><div>A note on penalty yards: Net Yards in my analysis below is also net of any penalty yards assessed on the punt. In general, penalties favor the punting team as the most common penalty called is holding on the return team. Average penalty yards in favor of the punting team has actually declined very slightly over the past ten seasons, so it is not a contributor to the increase in net punting yards shown below.<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;"><br />
</span> <span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Net Yards Per Punt</span><span style="line-height: 1.1;"><br />
<span class="Apple-style-span" style="font-size: small; font-weight: normal;">The first stat I looked at was net yards per punt, controlled for field position. Punts 40 yards from the end zone tend to net fewer yards than punts from 80 yards away. If teams have been changing </span><span class="Apple-style-span" style="font-size: small; font-weight: normal;"><i>where</i></span><span class="Apple-style-span" style="font-size: small; font-weight: normal;"> they punt from over time (e.g. punting less when in their opponent's territory), that will show up as an increase in net yards per punt, but doesn't really say much about the punters themselves.</span></span></div></div><div><br />
So, for each season, I took the average net yards from each yardline and weighted them by a common distribution, representing the total distribution of punts by field position from the 2002-2011 seasons. Here are the results:</div><div id="season" style="height: 400px; width: 600px;"></div><div>In 2002, the average punt netted 34.4 yards. By 2011, that had increased to 38.2 yards, where once again, I am controlling for differences in field position (i.e. where teams punted from). Here is another way of looking at the data which doesn't rely on any manipulation:</div><div id="compare" style="height: 400px; width: 600px;"></div><div>As you can see, no matter where punters are kicking from, they appear to be netting more yards now than they have in the past (some statistical noise not withstanding).<br />
<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">From Long Distance</span></div><div>I decided to look more closely at this change in punting yards, with a focus on where the team is punting from. Here are results for punts where the kicking team is greater than 65 yards away from the endzone:</div><div id="season1" style="height: 400px; width: 600px;"></div><div>From this area of the field, there is little risk of a touchback, so punting is more about raw leg strength. At this distance, gross yards per punt have been increasing at a rate of 0.53 yards per season, and net yards have increased by about 0.40 yards per season. So, kickers appear to be getting stronger, but perhaps the slightly lower gain in net yards is due to the phenomenon of "outkicking your coverage"? Time permitting, I would like to take a closer look at this and see of "outkicking your coverage" is a real thing, or just something that gets repeated by NFL announcers.<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;"><br />
</span> <span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Out of your goalpost's shadow</span><br />
What about when you get closer to the endzone? The graph below shows net yards when punting between 50 and 65 yards from the endzone.</div><div id="season2" style="height: 400px; width: 600px;"></div><div>We see a similar improvement from this area of the field as well. Although net yards appear to be slightly outpacing gross yards here, with net yards improving at a rate of 0.44 yards per season, but gross yards improving by 0.40 yards per season.<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;"><br />
</span> <span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Pinning them deep</span></div><div>Inside the 50, punting becomes less about strength, and more about finesse and accuracy. The previous results have clearly established that punters' legs are getting stronger. Are they also getting better at finding that sweet spot between the 20 and the goal line? Here are the results for punts from between 35 and 50 yards from the endzone:</div><div id="season3" style="height: 400px; width: 600px;"></div><div>While gross yards per punt has stayed relatively flat, net yards still shows improvement, at a rate of about 0.26 yards per season. I decided to dig into this a bit more and see what was driving this improvement in net yards.<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;"><br />
</span> <span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Touchback Probability</span></div><div>If punters are improving their net yards when kicking from inside the 50, that probably means they are getting better at avoiding touchbacks. The graph below shows the percentage of punts that resulted in touchbacks by field position, split by the 2002-2006 and 2007-2011 seasons.</div><div id="touchback" style="height: 400px; width: 600px;"></div><div>This graph is telling for two reasons. One, between 40 and 50 yards from the endzone, touchbacks are becoming significantly less likely, which should help explain the improvement in net yards per punt mentioned previously. Secondly, between 55 and 65 yards from the endzone, touchbacks have become <i>more</i> likely, probably as a result of improved leg strength.<br />
<br />
So, if punting teams are avoiding touchbacks more when punting from inside the 50, that must mean they are downing more punts, right? Here is the percentage of punts downed by field position, once again split by the 2002-2006 and 2007-2011 seasons.</div><div id="downed" style="height: 400px; width: 600px;"></div><div>The data is noisy, but there doesn't appear to be any clear shift to more downed punts when punting from inside the 50. If anything, teams appear to be downing punts less often, not more. So, if teams aren't downing the ball more, what else could explain this decrease in touchbacks?<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;"><br />
</span> <span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Fair Catch Probability</span><br />
The graph below shows the percentage of punts resulting in a fair catch, split between seasons 2002-2006 and 2007-2011.</div><div id="faircatch" style="height: 400px; width: 600px;"></div><div>Between 40 and 50 yards, there appears to have been fairly significant increase in how often a fair catch occurs. Which raises an interesting question: Is this because punters are getting better at finding that sweet spot on the field where the returner is forced to fair catch the ball? <i>Or</i> have returners been getting more conservative when making that decision?<br />
<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Conclusion</span><br />
<div>Punters are getting better, most clearly when it comes to leg strength, improving by about a half yard per punt per season since 2002. Punting teams have also gotten better at playing the finesse game inside the 50. My analysis above shows that touchbacks are becoming less frequent and that fair catches are becoming more frequent. But I think this may be an area for further investigation.<br />
<br />
<span class="Apple-style-span" style="font-size: 19px; font-weight: bold;">Appendix</span></div><div>There's no real point behind the following, but I'm sharing because I found it interesting. Here are graphs showing the probability of a touchback, fair catch, and a downed punt by field position (where field position signifies where punting team is kicking from).</div><br />
</div><div id="touchbacka" style="height: 400px; width: 600px;"></div><div id="downeda" style="height: 400px; width: 600px;"></div><div id="faircatcha" style="height: 400px; width: 600px;"><div style="text-align: left;"><br />
</div></div>Unknownnoreply@blogger.com2tag:blogger.com,1999:blog-5204092591876211047.post-54818793681115385562012-10-17T07:11:00.003-04:002012-10-17T07:11:40.136-04:00Response to Brian Burke's Washington Post articleBy Mike Sommers<br />
<br />
<span class="Apple-style-span" style="font-family: tahoma, 'new york', times, serif; font-size: 16px;"></span><br />
<div>
NB: I have also posted this on a site that I own and occasionally like to post to <a href="http://articlezinehub.com/a-response-to-the-brian-burke-washington-post-article/">here</a>.</div>
<div>
<br />
<br />
I recently read Brian Burke’s article describing how <a href="http://www.advancednflstats.com/2012/10/washington-post-manageable-third-downs.html">coaches should avoid the mentality of trying to set up 3rd and short </a>or 2nd and short and instead try to convert the first down.</div>
<div>
<br /></div>
<div>
It is not that I don’t agree with the article, but I wanted to consider several exceptions to that rule, and in the process came up with some interesting conclusions.</div>
<div>
<br /></div>
<div>
I can illustrate several instances where it’s best to NOT convert on first down. On 3rd however I can only think of 1, and it isn’t provable so much as it is intuitive, but I do have a statistical reference, unfortunately we just don’t have enough information to account for changes AS the play develops.</div>
<a name='more'></a><br />
<div>
<br /></div>
<div>
With 15 minutes remaining in the 1st quarter and a tie game, Brian’s EP model shows that 2nd and 3 on own 17 yard line is very close to the same as first and 10 on their own 20 yard line. 2nd and 2 on own 18 and 2nd and 1 on own 19 are BOTH vastly superior than 1st and 10 on 20. But most conversions will be a few yards past it.<br />
<br /></div>
<div>
If 2nd and 2 was average expectation of the following short yardage situation on first down, and average 1st down conversion went 4 yards past (1st and 10 on own 24) you would still be .01 WP better getting 2nd and short. The line in the sand is ROUGHLY “IF” you can get more than 4 yards past the first down marker, you should convert, if not, you should “settle” for 2nd and 2. If a runner is running up free and can easily get the first down and possesses the ability to go down one yard short of the first or less, the runner must be able to get over 6 yards past the first down marker for it to be the correct decision to run past the first down marker!</div>
<div>
<br /></div>
<div>
HOWEVER, if a team is making more optimal decisions on offense (and if they are aware of this information, they likely would be), I would argue that even 5 or 6 yards past the first down isn’t good enough to make up for the advantage of 2nd and short.<br />
<br /></div>
<div>
As I understand the EP model is based upon HISTORY and historically teams do not go for it on 4th down. If they did, I imagine the chances of converting and keeping the drive alive would be much higher, the EP is obviously higher in going for it on 4th and short, and that can only mean that if the team treats it as “4 down territory” that their EP would be even higher than advertised on 2nd and short. It also would be on 1st and 10 as well, but it is much more likely to be left with a 4th and short on 2nd and short than it is to be left with a 4th and short on same set of 4 downs on a 1st and 10. A gameplan to get a big play on 2nd and short, and then leave 3rd and 4th down to try to convert, or to try to convert 3 times in a row would likely boost the WP to the point that setting up 2nd and short is more favorable then perhaps converting AND getting an additional 5, 6, 7 or 8 yards past the first.</div>
<div>
<br /></div>
<div>
I don’t exactly know if there has been a study to determine the EP advantage the average team has if they made ALL of the correct decisions on 4th down, but I imagine over the course of the game the combination of intentionally setting up 2nd and short rather than converting at least often enough to keep defense off balance would significantly boost a team’s advantage, particularly if it was able to also go for it on 4th down more aggressively.<br />
<br /></div>
<div>
Plus, if one is close enough to get first, but just barely, they may resort to taking more risks trying to get the first, such as reaching the ball out, or cutting inward and staying in bounds where fumble is not only possible, but less likely to bounce out of bounds and remain the offense’s ball. That would require even more yards for a first down to be worth giving up the easy to convert 2nd and 3 or less.</div>
<div>
<br /></div>
<div>
Additionally, a team that is heavily positioned themselves to have an advantage over the average team in the pass game, but normally may have a slight disadvantage running would now have the opportunity to vary their play enough to prevent themselves from becoming predictable which can strengthen their passing attack and running attack over the course of a game.<br />
<br /></div>
<div>
The guideline is If you can’t get a big play, get 2nd and short, if you can’t get 2nd and short, get a first down, if you can’t get a first down, get what you can. If you are running towards the first down go out of bounds just short of the marker or go down in bounds unless you can get around 4-8 yards beyond the first down.</div>
<div>
<br /></div>
<div>
As for when 3rd down situation may dictate setting up 3rd and short, that will have to be published later as part two. There are a lot of new concepts to be introduced, and unfortunately there isn’t enough data tracking to really prove it in the game of football that I am aware of, but I am confident that there are hypothetical instances that exist, and they may exist throughout the entire game, which may drastically impact some decisions making a pass short of the 1st down on 2nd down very acceptable.</div>
<div>
<br /></div>
<div>
Following the EP model I believe still provides a very significant edge, however there are advancements that can be made, if only individual statistical categories are better defined as the play develops and as presnap reads are made, for now though, 2nd and short is superior to 1st and 10 occasionally, and 3rd and 1 is certainly not as good as 1st and 10, that much I am certain holds true in most situations.</div>
Unknownnoreply@blogger.com0tag:blogger.com,1999:blog-5204092591876211047.post-51005133732654733402012-10-13T10:39:00.000-04:002012-10-13T10:42:03.656-04:00Brees, Unitas and DiMaggio: 47-Game Streaks Fifty Years Apart, and that 56-Gamer, in Perspective.<!--[if gte mso 9]><xml> <o:DocumentProperties> <o:Revision>0</o:Revision> <o:TotalTime>0</o:TotalTime> <o:Pages>1</o:Pages> <o:Words>1659</o:Words> <o:Characters>9461</o:Characters> <o:Company>Simply Blended Wines</o:Company> <o:Lines>78</o:Lines> <o:Paragraphs>22</o:Paragraphs> <o:CharactersWithSpaces>11098</o:CharactersWithSpaces> <o:Version>14.0</o:Version> </o:DocumentProperties> <o:OfficeDocumentSettings> <o:PixelsPerInch>96</o:PixelsPerInch> <o:TargetScreenSize>800x600</o:TargetScreenSize> </o:OfficeDocumentSettings> </xml><![endif]--> <!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:TrackMoves/> <w:TrackFormatting/> <w:PunctuationKerning/> <w:ValidateAgainstSchemas/> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:DoNotPromoteQF/> <w:LidThemeOther>EN-US</w:LidThemeOther> <w:LidThemeAsian>JA</w:LidThemeAsian> <w:LidThemeComplexScript>X-NONE</w:LidThemeComplexScript> <w:Compatibility> <w:BreakWrappedTables/> <w:SnapToGridInCell/> <w:WrapTextWithPunct/> <w:UseAsianBreakRules/> <w:DontGrowAutofit/> <w:SplitPgBreakAndParaMark/> <w:EnableOpenTypeKerning/> <w:DontFlipMirrorIndents/> <w:OverrideTableStyleHps/> </w:Compatibility> <m:mathPr> <m:mathFont m:val="Cambria Math"/> <m:brkBin m:val="before"/> <m:brkBinSub m:val="--"/> <m:smallFrac m:val="off"/> <m:dispDef/> <m:lMargin m:val="0"/> <m:rMargin m:val="0"/> <m:defJc m:val="centerGroup"/> <m:wrapIndent m:val="1440"/> <m:intLim m:val="subSup"/> <m:naryLim m:val="undOvr"/> </m:mathPr></w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" DefUnhideWhenUsed="true"
DefSemiHidden="true" DefQFormat="false" DefPriority="99"
LatentStyleCount="276"> <w:LsdException Locked="false" Priority="0" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Normal"/> <w:LsdException Locked="false" Priority="9" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="heading 1"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 2"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 3"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 4"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 5"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 6"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 7"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 8"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 9"/> <w:LsdException Locked="false" Priority="39" Name="toc 1"/> <w:LsdException Locked="false" Priority="39" Name="toc 2"/> <w:LsdException Locked="false" Priority="39" Name="toc 3"/> <w:LsdException Locked="false" Priority="39" Name="toc 4"/> <w:LsdException Locked="false" Priority="39" Name="toc 5"/> <w:LsdException Locked="false" Priority="39" Name="toc 6"/> <w:LsdException Locked="false" Priority="39" Name="toc 7"/> <w:LsdException Locked="false" Priority="39" Name="toc 8"/> <w:LsdException Locked="false" Priority="39" Name="toc 9"/> <w:LsdException Locked="false" Priority="35" QFormat="true" Name="caption"/> <w:LsdException Locked="false" Priority="10" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Title"/> <w:LsdException Locked="false" Priority="1" Name="Default Paragraph Font"/> <w:LsdException Locked="false" Priority="11" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtitle"/> <w:LsdException Locked="false" Priority="22" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Strong"/> <w:LsdException Locked="false" Priority="20" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Emphasis"/> <w:LsdException Locked="false" Priority="59" SemiHidden="false"
UnhideWhenUsed="false" Name="Table Grid"/> <w:LsdException Locked="false" UnhideWhenUsed="false" Name="Placeholder Text"/> <w:LsdException Locked="false" Priority="1" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="No Spacing"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 1"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 1"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 1"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 1"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 1"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 1"/> <w:LsdException Locked="false" UnhideWhenUsed="false" Name="Revision"/> <w:LsdException Locked="false" Priority="34" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="List Paragraph"/> <w:LsdException Locked="false" Priority="29" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Quote"/> <w:LsdException Locked="false" Priority="30" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Quote"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 1"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 1"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 1"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 1"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 1"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 1"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 1"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 1"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 2"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 2"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 2"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 2"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 2"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 2"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 2"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 2"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 2"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 2"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 2"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 2"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 2"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 2"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 3"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 3"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 3"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 3"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 3"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 3"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 3"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 3"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 3"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 3"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 3"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 3"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 3"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 3"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 4"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 4"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 4"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 4"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 4"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 4"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 4"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 4"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 4"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 4"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 4"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 4"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 4"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 4"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 5"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 5"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 5"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 5"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 5"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 5"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 5"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 5"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 5"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 5"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 5"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 5"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 5"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 5"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 6"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 6"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 6"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 6"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 6"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 6"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 6"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 6"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 6"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 6"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 6"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 6"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 6"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 6"/> <w:LsdException Locked="false" Priority="19" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtle Emphasis"/> <w:LsdException Locked="false" Priority="21" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Emphasis"/> <w:LsdException Locked="false" Priority="31" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtle Reference"/> <w:LsdException Locked="false" Priority="32" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Reference"/> <w:LsdException Locked="false" Priority="33" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Book Title"/> <w:LsdException Locked="false" Priority="37" Name="Bibliography"/> <w:LsdException Locked="false" Priority="39" QFormat="true" Name="TOC Heading"/> </w:LatentStyles> </xml><![endif]--> <!--[if gte mso 10]> <style>
/* Style Definitions */
table.MsoNormalTable
{mso-style-name:"Table Normal";
mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
mso-style-priority:99;
mso-style-parent:"";
mso-padding-alt:0cm 5.4pt 0cm 5.4pt;
mso-para-margin:0cm;
mso-para-margin-bottom:.0001pt;
mso-pagination:widow-orphan;
font-size:10.0pt;
font-family:Calibri;}
</style> <![endif]--> <!--StartFragment--> <br />
<div class="MsoNormal">
by Jim Glass</div>
<div class="MsoNormal">
Drew Brees is collecting well-deserved congratulations on breaking what many have long considered to be the greatest record in pro-football: the streak of 47 consecutive games with a touchdown pass thrown, set by John Unitas during the 1956 through 1960 seasons. In my youth that was often compared to Joe DiMaggio's famous "unbreakable record" 56-game hitting streak in baseball. Last week <a href="https://www.google.com/search?q=brees%20unitas%20dimaggio&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a&source=hp&channel=np">it was again</a>.<o:p></o:p></div>
<div class="MsoNormal">
Yet Brees tied-and-broke that record with no fewer than <i style="mso-bidi-font-style: normal;">seven</i> TD passes in his last two games, while looking as if he's going to "keep on going and going and going" like that trademarked battery-packed bunny.<o:p></o:p></div>
<div class="MsoNormal">
So just how "unbreakable" should these records be considered to be?<span style="mso-spacerun: yes;"> </span>With all the changes in the game that have occurred during the last 60 years, has Brees' streak really matched Unitas' as being "comparably unlikely," an equal achievement against the odds?<span style="mso-spacerun: yes;"> </span>And how do these streaks actually compare to DiMaggio's.<span style="mso-spacerun: yes;"> </span>Here's a quick take:<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span style="font-size: 12.0pt; line-height: 115%;"><b>Running the Numbers</b><o:p></o:p></span></div>
<div class="MsoNormal">
How unlikely were the Brees and Unitas 47-game streaks?<span style="mso-spacerun: yes;"> </span>To adjust for the different styles of play of different times, a reasonable measure is the probability of the average team of each era (not quarterbacked by Brees or Unitas) scoring at least one touchdown by passing for that many consecutive games.<span style="mso-spacerun: yes;"> </span><o:p></o:p></div>
<a name='more'></a><br />
<div class="MsoNormal">
The PFR.com <a href="http://www.pro-football-reference.com/play-index/">database</a> informs us that during the Unitas streak (from game #10 of the 1956 season through game #10 in 1960) teams other than his Colts scored TDs through the air in 70.3% of their games, while during the Brees streak (game #5 in 2009 to game #4 in 2012) NFL teams apart from the Saints threw at least one TD pass in 78.3% of their games.<o:p></o:p></div>
<div class="MsoNormal">
Passing yards per game in the NFL increased by a good 33% over that period (to 225 from 169) so this increase of only 8 percentage points (or by 11%) in the number of games with TD passes thrown may seem unexpectedly small. <span style="mso-spacerun: yes;"> </span>But while teams throw much more often and for more total yards today, back in the Unitas era the fewer pass attempts generally were more aggressive and deeper, producing significantly greater yards-per-completion and TDs-per-attempt numbers than today (as detailed <a href="http://community.advancednflstats.com/2011/10/appreciating-how-old-ones-played-or-joe_06.html">previously</a><b style="mso-bidi-font-weight: normal;">.</b>)<o:p></o:p></div>
<div class="MsoNormal">
The probability of the average team in each era scoring a touchdown by passing in 47 consecutive games by random chance, starting in any single given game, is simply the above percentages compounded to the 47th power. <o:p></o:p></div>
<div class="MsoNormal">
• Brees era probability: 0.783^47 = 1.01579E-05<o:p></o:p></div>
<div class="MsoNormal">
• Unitas era probabiity:<span style="mso-spacerun: yes;"> </span>0.703^47 =<span style="mso-spacerun: yes;"> </span><span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">6.41062E-08<o:p></o:p></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Those results are made more comprehensible by converting them into "Once per how many games", via dividing 1 by each result above. Giving...<o:p></o:p></div>
<div class="MsoNormal">
• Brees era:<span style="mso-spacerun: yes;"> </span>Once per <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">98,446</span> games.<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";"><o:p></o:p></span></div>
<div class="MsoNormal">
• Unitas era:<span style="mso-spacerun: yes;"> </span>Once per <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">15,599,107 </span>games.<o:p></o:p></div>
<div class="MsoNormal">
The Brees record is a very impressive, expected to be seen starting only once in near a hundred thousand games -- but Unitas' is once in <i style="mso-bidi-font-style: normal;">15.6 million.</i><span style="mso-spacerun: yes;"> </span><o:p></o:p></div>
<div class="MsoNormal">
Those mere 8 percentage points make a serious difference when compounded 47 times.<o:p></o:p></div>
<div class="MsoNormal">
Another way to look at these records is "Once in how many years".<span style="mso-spacerun: yes;"> </span>A streak can start with every game played by every team.<span style="mso-spacerun: yes;"> </span>Thus, the chance of one starting in any given season is the "once per how many games" number multiplied by the number of games in a season.<span style="mso-spacerun: yes;"> </span>In today's NFL with 32 teams each playing 16 games, there are 512 games per season.<span style="mso-spacerun: yes;"> </span>During the Unitas-streak era 12 teams played 12 games each season for 144 games.<span style="mso-spacerun: yes;"> </span>(In 1960 Dallas joined the league as its 13th team, still playing a 12-game season.)<span style="mso-spacerun: yes;"> </span>Applying these numbers we get...<o:p></o:p></div>
<div class="MsoNormal">
• Brees record:<span style="mso-spacerun: yes;"> </span>Once in 192 years.<o:p></o:p></div>
<div class="MsoNormal">
• Unitas record when set:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">108,327</span> years. (That is not a typo!)<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";"><o:p></o:p></span></div>
<div class="MsoNormal">
• Unitas record with today's 512-game season:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">30,467 </span>years.<o:p></o:p></div>
<div class="MsoNormal">
As impressive as Brees's performance is -- and it is very impressive -- by the measures used here, it is simply not "comparably improbable" to Unitas' accomplishment.<o:p></o:p></div>
<div class="MsoNormal">
How many consecutive games with a TD pass must Brees achieve for his record to match Unitas' as an equally improbable achievement?<span style="mso-spacerun: yes;"> </span>By the methodology used here ... 68.<span style="mso-spacerun: yes;"> </span>That would happen in the ninth game of the 2013 season, if he doesn't sit out any games before then. Set your DVR now to record it, so you don't forget. <span style="mso-spacerun: yes;"> </span>With his talent and the offensive talent around him on that team, I'm not doubting that he can make it.<o:p></o:p></div>
<div class="MsoNormal">
For more perspective on these two historically great sustained performances by these two great quarterbacks in very different eras of QB play, here are the numbers for each during their 47-game streaks.<span style="mso-spacerun: yes;"> </span><o:p></o:p></div>
<div class="MsoNormal">
Since the average numbers for the two eras are so different, I've also added a three digit percent number comparing the average of each stat with the NFL average for all the non-Brees, non-Unitas teams during the period of each streak:<span style="mso-spacerun: yes;"> </span>100 is average, 120 is 20% better than average (more than average, except for interceptions for which it is less than average), etc.<o:p></o:p></div>
<div class="MsoNormal">
<span style="mso-spacerun: yes;"> </span>BREES <span style="mso-spacerun: yes;"> </span>and UNITAS<o:p></o:p></div>
<table border="0" cellpadding="0" cellspacing="0" class="MsoNormalTable" style="border-collapse: collapse; margin-left: 4.7pt; mso-padding-alt: 0cm 5.4pt 0cm 5.4pt; mso-yfti-tbllook: 1184; width: 339px;"><tbody>
<tr style="height: 15.0pt; mso-yfti-firstrow: yes; mso-yfti-irow: 0;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Totals<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Unitas <o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">%vLgAv<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Brees<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">%vLgAv<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 1;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"></td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 2;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Attempts<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">1304<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">109<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">1891<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">120<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 3;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Completed<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">700<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">118<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">1302<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">136<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 4;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Comp%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">53.7%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">108<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">68.9%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">114<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 5;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Yards<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">10696<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">139<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">14803<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">142<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 6;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">TDs<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">102<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">170<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">114<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">172<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 7;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">INTs<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">61<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">129<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">50<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">94<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 8;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"></td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 9;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Attempts/game<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">27.7<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">109<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">40.2<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">120<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 10;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Completed/game<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">14.9<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">118<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">27.7<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">136<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 11;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Yards/game<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">228<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">139<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">315<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">142<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 12;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Yards/attempt<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">8.2<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">127<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">7.8<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">118<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 13;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">Yards/completion<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">15.3<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">117<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">11.4<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">104<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 14;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">TD%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">7.8%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">155<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">6.0%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">143<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 15;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">TDs/completed<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">14.6%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">144<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">8.8%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">126<o:p></o:p></span></div>
</td> </tr>
<tr style="height: 15.0pt; mso-yfti-irow: 16; mso-yfti-lastrow: yes;"> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 86.0pt;" valign="bottom" width="86"><div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">INT%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 71.0pt;" valign="bottom" width="71"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">4.7%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 44.0pt;" valign="bottom" width="44"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">141<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 22.0pt;" valign="bottom" width="22"></td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 68.0pt;" valign="bottom" width="68"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">2.6%<o:p></o:p></span></div>
</td> <td nowrap="" style="height: 15.0pt; padding: 0cm 5.4pt 0cm 5.4pt; width: 48.0pt;" valign="bottom" width="48"><div align="right" class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0cm; text-align: right;">
<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">112<o:p></o:p></span></div>
</td> </tr>
</tbody></table>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Those are two stellar sets of numbers.<o:p></o:p></div>
<div class="MsoNormal">
The greater aggressiveness of Unitas' passing (and that of his era) is seen in the fact that while he had 31% fewer attempts than Brees in their 47-game sets -- Brees had as many completions as Unitas had attempts -- and a completion percentage that was 22% lower than Brees', his yards-per-completion was 34% higher than Brees's and his touchdowns-per-completion fully 66% higher than Brees'.<o:p></o:p></div>
<div class="MsoNormal">
There's a common belief that the rule changes that have so opened up the passing game in recent years have made offense more aggressive and increased scoring.<span style="mso-spacerun: yes;"> </span>But in reality, the rule changes have led to a big increase in conservative, short, ball-control passing, replacing the former running game. <span style="mso-spacerun: yes;"> </span>As the average pass has become shorter and safer, the running game has been evaporating, but scoring hasn't increased as much as many think. <span style="mso-spacerun: yes;"> </span>In 1958 NFL teams averaged 22.6 points a game -- during the middle of Unitas streak as the Colts won the title behind his passing.<span style="mso-spacerun: yes;"> </span>Last year, 2011, the league averaged fewer, 22.2 points, in spite of all the passing records that were set and all the breathless journalism about them.<span style="mso-spacerun: yes;"> </span>But that's <a href="http://community.advancednflstats.com/2011/10/joes-numbers-and-moral-of-story.html">another story</a>.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span style="font-size: 12.0pt; line-height: 115%;"><a href="http://www.sbnation.com/nfl/2012/10/7/3460276/drew-brees-touchdown-streak-joe-dimaggio">"Is Drew Brees' touchdown streak superior to DiMaggio's hit streak?"</a><o:p></o:p></span></div>
<div class="MsoNormal">
The question seems more appropriately asked about the Unitas streak, but let's look at <span style="mso-spacerun: yes;"> </span>the DiMaggio s streak to see, using the same methodology as above as closely as it can be applied to a very different sport.<o:p></o:p></div>
<div class="MsoNormal">
DiMaggio hit safely in 56 consecutive games during the 1941 MLB season.<span style="mso-spacerun: yes;"> </span>The Baseball Reference.com database tells us that during that season the overall batting average for non-pitchers was .274,<span style="mso-spacerun: yes;"> </span>and that each of the nine slots in the batting order had an average of<span style="mso-spacerun: yes;"> </span>3.83 at bats per game.<o:p></o:p></div>
<div class="MsoNormal">
The chance of the average batter getting a hit in the average game is the inverse of that of not getting a hit in any of his at bats.<span style="mso-spacerun: yes;"> </span>Using the numbers above, the probability of not getting a hit in any one at bat is .726, and thus 0.726^3.83 gives a .293 probability of not getting a hit in the average game -- and a .707 likelihood of getting a hit.<o:p></o:p></div>
<div class="MsoNormal">
As it happens, the Unitas and DiMaggio streaks were <i style="mso-bidi-font-style: normal;">very</i> comparable on a per game basis, with a nearly identical per game chance of "success" of .703 for quarterbacks and .707 for batters.<span style="mso-spacerun: yes;"> </span>But DiMaggio's streak ran nine games longer.<span style="mso-spacerun: yes;"> </span>How much difference does this make?<o:p></o:p></div>
<div class="MsoNormal">
Repeating the methodology above, the probability of each streak starting in any given game for the average player...<o:p></o:p></div>
<div class="MsoNormal">
• DiMaggio streak:<span style="mso-spacerun: yes;"> </span>0.707^56 = <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">3.69392E-09<o:p></o:p></span></div>
<div class="MsoNormal">
• Unitas streak:<span style="mso-spacerun: yes;"> </span>0.703^47 =<span style="mso-spacerun: yes;"> </span><span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">6.41062E-08</span><o:p></o:p></div>
<div class="MsoNormal">
Which gives....<o:p></o:p></div>
<div class="MsoNormal">
• DiMaggio streak:<span style="mso-spacerun: yes;"> </span>Once per <a href="http://www.blogger.com/blogger.g?blogID=5204092591876211047" name="OLE_LINK1"><span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">270,715,316 </span></a><span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">games (!!)<o:p></o:p></span></div>
<div class="MsoNormal">
• Unitas streak:<span style="mso-spacerun: yes;"> </span>Once per <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">15,599,107 </span>games.<b style="mso-bidi-font-weight: normal;"><o:p></o:p></b></div>
<div class="MsoNormal">
Wow.<span style="mso-spacerun: yes;"> </span>As great as the Unitas streak is, DiMaggio's is a good deal even more so as a "starting from any given game" event.<o:p></o:p></div>
<div class="MsoNormal">
But there is another way to look at it. There are many more games in a baseball season than in an NFL season, so the "once in how many years" baseball record will be correspondingly reduced.<o:p></o:p></div>
<div class="MsoNormal">
In a single season during the Unitas-record era a starting QB played 12 games a season, and so had 12 chances to start a streak.<span style="mso-spacerun: yes;"> </span>In 1941 baseball batter played a 154 game season, and so had 154 chances.<span style="mso-spacerun: yes;"> </span>Thus, first, the probability of a given single average player starting a record streak in a given season...<o:p></o:p></div>
<div class="MsoNormal">
• DiMaggio streak:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">1,757,892 </span>seasons.<o:p></o:p></div>
<div class="MsoNormal">
• Unitas streak:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">1,299,926 seasons.<o:p></o:p></span></div>
<div class="MsoNormal">
By this measure they are nearing equal.<o:p></o:p></div>
<div class="MsoNormal">
Then again there is the "Once in how many years" will the streak be expected occur for the entire pro sport given how it is organized.<o:p></o:p></div>
<div class="MsoNormal">
In 1941 there were 16 MLB teams playing a 154-game season, and for the purpose here I count eight batters in the lineup per game (disregarding pitchers).<span style="mso-spacerun: yes;"> </span>Multiplying those numbers out gives 19,172 chances for some batter on some team to start a hitting streak in the 1941 season.<o:p></o:p></div>
<div class="MsoNormal">
Today's MLB plays a 162-game season with 30 teams, of which 16 are the National League for which I again count eight batters each, and 14 are in the American League with nine batters each (thanks to the designated hitter). <span style="mso-spacerun: yes;"> </span>Multiply those out and we get <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">41,148 </span>chances for some batter to start a streak each season, which gives...<o:p></o:p></div>
<div class="MsoNormal">
• DiMaggio record when set:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">14,120 years.</span><o:p></o:p></div>
<div class="MsoNormal">
• DiMaggio record, today's MLB season:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">6,579 years</span>.<span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";"><o:p></o:p></span></div>
<div class="MsoNormal">
Compared to, as we have already seen...<o:p></o:p></div>
<div class="MsoNormal">
• Unitas record when set:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">108,327</span> years. <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";"><o:p></o:p></span></div>
<div class="MsoNormal">
• Unitas record with today's 512-game season:<span style="mso-spacerun: yes;"> </span>Once in <span style="color: black; mso-bidi-font-family: Calibri; mso-fareast-font-family: "Times New Roman";">30,467 </span>years.<o:p></o:p></div>
<div class="MsoNormal">
Now the Unitas streak looks the more impressive.<o:p></o:p></div>
<div class="MsoNormal">
So it depends what measure one judges by.<span style="mso-spacerun: yes;"> </span>The DiMaggio hitting streak is significantly more impressive -- improbable, against the odds -- in terms of an individual player's starting such a streak in any given game.<span style="mso-spacerun: yes;"> </span>But because so many more hitters play so many more games in major league baseball each year, giving so many more chances to break the DiMaggio record,<span style="mso-spacerun: yes;"> </span>it is the Unitas streak that seems to be the one more likely to last "for the ages" before matched by another of equal improbability.<o:p></o:p></div>
<div class="MsoNormal">
So which record is the "greatest"?<span style="mso-spacerun: yes;"> </span>That's subjective, you decide.<span style="mso-spacerun: yes;"> </span><o:p></o:p></div>
<div class="MsoNormal">
And don't forget to set your DVR to record those Saints games in weeks #9 and #10 of the 2013 season.<o:p></o:p></div>
<!--EndFragment-->Unknownnoreply@blogger.com7tag:blogger.com,1999:blog-5204092591876211047.post-43499564677328271462012-09-10T23:51:00.000-04:002012-09-10T23:51:42.517-04:00Combining Win Probability Model With Live WP Graph<!--[if gte mso 9]><xml> <o:DocumentProperties> <o:Revision>0</o:Revision> <o:TotalTime>0</o:TotalTime> <o:Pages>1</o:Pages> <o:Words>323</o:Words> <o:Characters>1846</o:Characters> <o:Company>Simply Blended Wines</o:Company> <o:Lines>15</o:Lines> <o:Paragraphs>4</o:Paragraphs> <o:CharactersWithSpaces>2165</o:CharactersWithSpaces> <o:Version>14.0</o:Version> </o:DocumentProperties> <o:OfficeDocumentSettings> <o:AllowPNG/> </o:OfficeDocumentSettings> </xml><![endif]--> <!--[if gte mso 9]><xml> <w:WordDocument> <w:View>Normal</w:View> <w:Zoom>0</w:Zoom> <w:TrackMoves/> <w:TrackFormatting/> <w:PunctuationKerning/> <w:ValidateAgainstSchemas/> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:DoNotPromoteQF/> <w:LidThemeOther>EN-US</w:LidThemeOther> <w:LidThemeAsian>JA</w:LidThemeAsian> <w:LidThemeComplexScript>X-NONE</w:LidThemeComplexScript> <w:Compatibility> <w:BreakWrappedTables/> <w:SnapToGridInCell/> <w:WrapTextWithPunct/> <w:UseAsianBreakRules/> <w:DontGrowAutofit/> <w:SplitPgBreakAndParaMark/> <w:EnableOpenTypeKerning/> <w:DontFlipMirrorIndents/> <w:OverrideTableStyleHps/> </w:Compatibility> <m:mathPr> <m:mathFont m:val="Cambria Math"/> <m:brkBin m:val="before"/> <m:brkBinSub m:val="--"/> <m:smallFrac m:val="off"/> <m:dispDef/> <m:lMargin m:val="0"/> <m:rMargin m:val="0"/> <m:defJc m:val="centerGroup"/> <m:wrapIndent m:val="1440"/> <m:intLim m:val="subSup"/> <m:naryLim m:val="undOvr"/> </m:mathPr></w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" DefUnhideWhenUsed="true"
DefSemiHidden="true" DefQFormat="false" DefPriority="99"
LatentStyleCount="276"> <w:LsdException Locked="false" Priority="0" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Normal"/> <w:LsdException Locked="false" Priority="9" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="heading 1"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 2"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 3"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 4"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 5"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 6"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 7"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 8"/> <w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 9"/> <w:LsdException Locked="false" Priority="39" Name="toc 1"/> <w:LsdException Locked="false" Priority="39" Name="toc 2"/> <w:LsdException Locked="false" Priority="39" Name="toc 3"/> <w:LsdException Locked="false" Priority="39" Name="toc 4"/> <w:LsdException Locked="false" Priority="39" Name="toc 5"/> <w:LsdException Locked="false" Priority="39" Name="toc 6"/> <w:LsdException Locked="false" Priority="39" Name="toc 7"/> <w:LsdException Locked="false" Priority="39" Name="toc 8"/> <w:LsdException Locked="false" Priority="39" Name="toc 9"/> <w:LsdException Locked="false" Priority="35" QFormat="true" Name="caption"/> <w:LsdException Locked="false" Priority="10" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Title"/> <w:LsdException Locked="false" Priority="0" Name="Default Paragraph Font"/> <w:LsdException Locked="false" Priority="11" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtitle"/> <w:LsdException Locked="false" Priority="22" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Strong"/> <w:LsdException Locked="false" Priority="20" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Emphasis"/> <w:LsdException Locked="false" Priority="59" SemiHidden="false"
UnhideWhenUsed="false" Name="Table Grid"/> <w:LsdException Locked="false" UnhideWhenUsed="false" Name="Placeholder Text"/> <w:LsdException Locked="false" Priority="1" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="No Spacing"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 1"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 1"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 1"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 1"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 1"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 1"/> <w:LsdException Locked="false" UnhideWhenUsed="false" Name="Revision"/> <w:LsdException Locked="false" Priority="34" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="List Paragraph"/> <w:LsdException Locked="false" Priority="29" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Quote"/> <w:LsdException Locked="false" Priority="30" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Quote"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 1"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 1"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 1"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 1"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 1"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 1"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 1"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 1"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 2"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 2"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 2"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 2"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 2"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 2"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 2"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 2"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 2"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 2"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 2"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 2"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 2"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 2"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 3"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 3"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 3"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 3"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 3"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 3"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 3"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 3"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 3"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 3"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 3"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 3"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 3"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 3"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 4"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 4"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 4"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 4"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 4"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 4"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 4"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 4"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 4"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 4"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 4"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 4"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 4"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 4"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 5"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 5"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 5"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 5"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 5"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 5"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 5"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 5"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 5"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 5"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 5"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 5"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 5"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 5"/> <w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 6"/> <w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 6"/> <w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 6"/> <w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 6"/> <w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 6"/> <w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 6"/> <w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 6"/> <w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 6"/> <w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 6"/> <w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 6"/> <w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 6"/> <w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 6"/> <w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 6"/> <w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 6"/> <w:LsdException Locked="false" Priority="19" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtle Emphasis"/> <w:LsdException Locked="false" Priority="21" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Emphasis"/> <w:LsdException Locked="false" Priority="31" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtle Reference"/> <w:LsdException Locked="false" Priority="32" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Reference"/> <w:LsdException Locked="false" Priority="33" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Book Title"/> <w:LsdException Locked="false" Priority="37" Name="Bibliography"/> <w:LsdException Locked="false" Priority="39" QFormat="true" Name="TOC Heading"/> </w:LatentStyles> </xml><![endif]--> <!--[if gte mso 10]> <style>
/* Style Definitions */
table.MsoNormalTable
{mso-style-name:"Table Normal";
mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
mso-style-priority:99;
mso-style-parent:"";
mso-padding-alt:0cm 5.4pt 0cm 5.4pt;
mso-para-margin:0cm;
mso-para-margin-bottom:.0001pt;
mso-pagination:widow-orphan;
font-size:10.0pt;
font-family:"Times New Roman";}
</style> <![endif]--> <!--StartFragment--> <br />
<div class="MsoNormal">
<div class="separator" style="clear: both; text-align: center;">
</div>
<div class="separator" style="clear: both; text-align: center;">
<br /></div>
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj7M4gmq0EEOOuUBh_ghV-9ZatVg_KXq6-VZLg85LR0wutgShfIr2FTsE-ihjwbhVssZQHrDST2LmoYxHhO36C-5Jx7jtLmpqEyTFRkG9Sl85mJ36Uoatp41bEn_94ceNURsioQfploqz1o/s1600/equation.jpg" imageanchor="1" style="clear: left; float: left; margin-bottom: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj7M4gmq0EEOOuUBh_ghV-9ZatVg_KXq6-VZLg85LR0wutgShfIr2FTsE-ihjwbhVssZQHrDST2LmoYxHhO36C-5Jx7jtLmpqEyTFRkG9Sl85mJ36Uoatp41bEn_94ceNURsioQfploqz1o/s1600/equation.jpg" /></a></div>
by Tom Baldwin</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<span lang="EN-GB">Andrew Foland provided a solution to this all the way back in January 2011, but it has not been implemented, perhaps because of the complexity of the solution, perhaps simply because nobody has got around to it yet, whichever the case I am here to provide a simple alternative and hope it gets implemented.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<div class="MsoNormal">
<span lang="EN-GB">The problem is that of combining the prior strength of the teams – the expected difference in performance over a game, let us call this S, with the current state of the game as expressed as a probability, WP. To do this we must consider the total game time, 60 minutes, and the game time remaining, T, in minutes.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"></span><br />
<a name='more'></a><span lang="EN-GB"><br />
</span></div>
<div class="MsoNormal">
<span lang="EN-GB">Intuitively we can say that S varies such that S(T)=S(60)*T/60, where S(60) is simply the value of S at the start of the game. We can see this is true, intuitively, because if I tell you team A will on average beat team B by ten points over a sixty minute game, then we'd both agree that if the games were cut to thirty minutes then on average A would beat B by five points.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<div class="MsoNormal">
<span lang="EN-GB">However, we must also consider how the standard deviation of this value varies with time, and the answer happens to be that it varies as the square root of the ratio of time reamining to total time, in other words: Stdev(T)=Stdev(60)*((T/60)^0.5), where Stdev(60) is the standard deviation at the start of the game. As such we reach the equation for the variation of the team strength parameter over the course of the game, S(T)=S(60)*((T/60)^0.5).<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<div class="MsoNormal">
<span lang="EN-GB">How do we get the initial value of S, S(60)? We take it from Brian's win probability for the game:<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">S(60)=ln(P/(1-P)), where P is Brian's predicted win probability.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<div class="MsoNormal">
<span lang="EN-GB">So now, lastly, we need the information from Brian's live model, which we get from taking the probability from the model for the current game time, call it WP, and doing as we did to find S(60):<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">W=ln(WP/(1-WP)), where W is the logit value of WP.<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB"><br />
</span></div>
<div class="MsoNormal">
<span lang="EN-GB">Now, finally, we have everything, and it combines nicely into this neat, simple equation:<o:p></o:p></span></div>
<div class="MsoNormal">
<span lang="EN-GB">PWIN=1/(1+exp(-ln(WP/(1-WP))-ln(P/(1-P))*((T/60)^0.5)))<o:p></o:p></span></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<div style="text-align: left;">
<span lang="EN-GB">And that's it, hardly complicated all in all, maybe if we're very lucky it'll be implemented.</span></div>
</div>
<!--EndFragment-->Unknownnoreply@blogger.com4tag:blogger.com,1999:blog-5204092591876211047.post-76305646526704223412012-04-13T18:45:00.000-04:002012-04-15T14:54:15.012-04:00Comeback Wins/Losses: The Comeback Kings<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><br />
<div class="separator" style="clear: both; text-align: center;"></div>by Clark Heins<br />
<br />
<p>For every comeback win there is a corresponding comeback loss, and one cannot be considered without the other. A comeback win occurs when the winning team overcomes a deficit at the start of the fourth quarter, at sometime during the fourth quarter or, if necessary, in overtime. Comeback wins have little to do with “comeback opportunities,” as the latter deal specifically with a point spread of eight or fewer points and include games that are tied in the fourth quarter. A comeback win can occur from any deficit and doesn’t deal with ties.<br />
<br />
For the purposes of this study, I have made no attempt to credit a QB’s total of comeback wins/losses based upon whether or not he deserves them, as luck always plays a role. My totals are entirely based upon one criteria---who was the QB of record when the comeback win or loss was attained, regardless of how it was attained. As an example, I didn't credit Dan Marino, John Elway, Kerry Collins, and Warren Moon with comeback wins when they were injured during a game-winning drive and replaced by another QB. To do so would ignore the element of luck. Also, my calculations are based upon “QB starts” rather than “games played”, as it would be extremely unfair to use the latter stat for many of the QBs. “QB starts” isn’t perfect either, as several of the QBs mentioned here scored comeback wins or losses in relief.<a name='more'></a><br />
<br />
My interest in comeback wins began when I read an article about “comeback opportunities” by Jason McKinley ("Quarterbacks and Fourth Quarter Comebacks”, Football Outsiders, June 26, 2006). McKinley formulated the concept of “QB of record”. In doing so, he created a level playing field for all the QBs who could be judged by one common standard while, at the same time, eliminating any personal bias or value judgments on the part of the researcher. However, little data existed concerning comeback wins, and my frustration to find information fueled my interest. Fortune smiled when Doug Drinen published over 10,000 NFL box scores on his website, pro-football-reference.com. Given the box scores, I could easily figure out who the winning QBs of record were for about 90 percent of the games. The remaining 10 percent I had to look up in newspaper articles. Foolishly, I did not record the losing QBs of record and have had to go back and correct that mistake because I realized I had only half of the equation that would lead to the answer to the question I was interested in: “Who were the real comeback kings?”<br />
<br />
Okay, let’s look at the raw figures: Twenty-five NFL QBs have attained 20 or more comeback wins in their careers with Drew Brees, Ben Roethlisberger and Eli Manning reaching that figure in 2011. Taken together, these 25 QBs have totaled 636 comeback wins and 474 comeback losses. It should be noted that in 32 of these comeback wins (5%), the winning points were scored by either a defensive or special teams player. However, this does not diminish the role that the winning QB of record plays in the outcome as, on average, the go-ahead points in a comeback win are scored with eight minutes and ten seconds remaining in the contest---which means that the winning QB of record must help his team maintain and protect the lead for nearly eight minutes of the fourth quarter while, at the same time, the losing QB of record has nearly eight minutes to overcome a deficit which, on average is 4.8 points (see McKinley's article for a full discussion). Acknowledging the fact that football is the ultimate team sport and that QBs are merely the titular representatives of their teams, these are their comeback wins minus their comeback losses and the difference, in plus or minus terms: </p><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th> </th><th>Wins</th><th>Losses</th><th>Difference</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;"> Dan Marino</td><td>37</td><td>26</td><td>11</td></tr>
<tr><td style="text-align: center;"> Peyton Manning</td><td>36</td><td>24</td><td>12</td></tr>
<tr><td style="text-align: center;"> Johnny Unitas</td><td>35</td><td>17</td><td>18</td></tr>
<tr><td style="text-align: center;"> John Elway</td><td>33</td><td>18</td><td>15</td></tr>
<tr><td style="text-align: center;"> Brett Favre</td><td>32</td><td>26</td><td>6</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Joe Montana</td><td>31</td><td>16</td><td>15</td></tr>
<tr><td style="text-align: center;"> Vinny Testaverde</td><td>29</td><td>28</td><td>1</td></tr>
<tr><td style="text-align: center;"> Fran Tarkenton</td><td>29</td><td>30</td><td>-1</td></tr>
<tr><td style="text-align: center;"> Drew Bledsoe</td><td>27</td><td>22</td><td>5</td></tr>
<tr><td style="text-align: center;"> Warren Moon</td><td>25</td><td>25</td><td>0</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Tom Brady</td><td>25</td><td>10</td><td>15</td></tr>
<tr><td style="text-align: center;"> Dave Krieg</td><td>24</td><td>17</td><td>7</td></tr>
<tr><td style="text-align: center;"> Jim Kelly</td><td>24</td><td>19</td><td>5</td></tr>
<tr><td style="text-align: center;"> Dan Fouts</td><td>23</td><td>23</td><td>0</td></tr>
<tr><td style="text-align: center;"> Randall Cunningham</td><td>22</td><td>19</td><td>3</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Jake Plummer</td><td>21</td><td>11</td><td>10</td></tr>
<tr><td style="text-align: center;"> Joe Theismann</td><td>21</td><td>8</td><td>13</td></tr>
<tr><td style="text-align: center;"> Steve Bartkowski</td><td>20</td><td>22</td><td>-2</td></tr>
<tr><td style="text-align: center;"> Boomer Esiason</td><td>20</td><td>26</td><td>-6</td></tr>
<tr><td style="text-align: center;"> Y.A. Tittle</td><td>20</td><td>11</td><td>9</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Joe Ferguson</td><td>20</td><td>17</td><td>3</td></tr>
<tr><td style="text-align: center;"> Kerry Collins</td><td>20</td><td>17</td><td>3</td></tr>
<tr><td style="text-align: center;"> Eli Manning</td><td>22</td><td>10</td><td>12</td></tr>
<tr><td style="text-align: center;"> Ben Roethlisberger</td><td>20</td><td>10</td><td>10</td></tr>
<tr><td style="text-align: center;"> Drew Brees</td><td>20</td><td>22</td><td>-2</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Terry Bradshaw</td><td>19</td><td>11</td><td>8</td></tr>
<tr><td style="text-align: center;"> Ken Stabler</td><td>19</td><td>13</td><td>6</td></tr>
<tr><td style="text-align: center;"> Jim Plunkett</td><td>19</td><td>14</td><td>5</td></tr>
<tr><td style="text-align: center;"> Jon Kitna</td><td>19</td><td>19</td><td>0</td></tr>
<tr><td style="text-align: center;"> Donovan McNabb</td><td>18</td><td>22</td><td>-4</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> John Brodie</td><td>18</td><td>16</td><td>2</td></tr>
<tr><td style="text-align: center;"> Jake Delhomme</td><td>18</td><td>13</td><td>5</td></tr>
<tr><td style="text-align: center;"> Ron Jaworski</td><td>17</td><td>20</td><td>-3</td></tr>
<tr><td style="text-align: center;"> Steve DeBerg</td><td>17</td><td>22</td><td>-5</td></tr>
<tr><td style="text-align: center;"> Norm Van Brocklin (one CBW from 1949)</td><td>17</td><td>9</td><td>8</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Doug Williams</td><td>17</td><td>9</td><td>8</td></tr>
<tr><td style="text-align: center;"> Jim Hart</td><td>17</td><td>17</td><td>0</td></tr>
<tr><td style="text-align: center;"> Brian Sipe</td><td>17</td><td>15</td><td>2</td></tr>
<tr><td style="text-align: center;"> Steve McNair</td><td>17</td><td>14</td><td>3</td></tr>
<tr><td style="text-align: center;"> Mark Brunell</td><td>17</td><td>20</td><td>-3</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> George Blanda</td><td>16</td><td>12</td><td>4</td></tr>
<tr><td style="text-align: center;"> Roger Staubach</td><td>16</td><td>11</td><td>5</td></tr>
<tr><td style="text-align: center;"> Trent Green</td><td>16</td><td>13</td><td>3</td></tr>
<tr><td style="text-align: center;"> Bart Starr</td><td>16</td><td>11</td><td>5</td></tr>
<tr><td style="text-align: center;"> Rich Gannon</td><td>16</td><td>25</td><td>-9</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Troy Aikman</td><td>16</td><td>19</td><td>-3</td></tr>
<tr><td style="text-align: center;"> Neil O’Donnell</td><td>16</td><td>6</td><td>10</td></tr>
<tr><td style="text-align: center;"> Jay Schroeder</td><td>16</td><td>12</td><td>4</td></tr>
<tr><td style="text-align: center;"> Tommy Kramer</td><td>16</td><td>13</td><td>3</td></tr>
<tr><td style="text-align: center;"> Charlie Conerly (one CBW from 1949)</td><td>15</td><td>14</td><td>1</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Bobby Layne (one CBW from 1949)</td><td>15</td><td>10</td><td>5</td></tr>
<tr><td style="text-align: center;"> Danny White</td><td>15</td><td>10</td><td>5</td></tr>
<tr><td style="text-align: center;"> Bernie Kosar</td><td>15</td><td>14</td><td>1</td></tr>
<tr><td style="text-align: center;"> Jim Harbaugh</td><td>15</td><td>18</td><td>-3</td></tr>
<tr><td style="text-align: center;"> Steve Young</td><td>14</td><td>15</td><td>-1</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Sonny Jurgensen</td><td>14</td><td>13</td><td>1</td></tr>
<tr><td style="text-align: center;"> Steve Grogan</td><td>14</td><td>18</td><td>-4</td></tr>
<tr><td style="text-align: center;"> Ken O’Brien</td><td>14</td><td>12</td><td>2</td></tr>
<tr><td style="text-align: center;"> Brad Johnson</td><td>14</td><td>13</td><td>1</td></tr>
<tr><td style="text-align: center;"> Trent Dilfer</td><td>14</td><td>8</td><td>6</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Dan Pastorini</td><td>14</td><td>10</td><td>4</td></tr>
<tr><td style="text-align: center;"> Bob Griese</td><td>14</td><td>14</td><td>0</td></tr>
<tr><td style="text-align: center;"> Steve Beuerlein</td><td>14</td><td>13</td><td>1</td></tr>
<tr><td style="text-align: center;"> Daryle Lamonica</td><td>14</td><td>2</td><td>12</td></tr>
</tbody></table></div><p>The raw results show that, while Dan Marino has the most comeback wins and Fran Tarkenton has the most comeback losses, Johnny Unitas has the best differential – all the more remarkable in that he did not have the benefit of overtime games to pad his figures. The two big surprises have to be Joe Theismann and Jake Plummer, neither of whom is considered among the elite QBs, but both of whom performed well under fourth-quarter pressure; indeed, McKinley had Plummer as the top-rated QB in his survey which covered the years 1996-05.<br />
<br />
Neil O’Donnell and Daryle Lamonica are the seventh and eighth NFL QBs who had at least 10 more comeback wins than losses during their careers. Currently, Peyton Manning, Tom Brady, Ben Rothlisberger and Eli Manning also have at least ten more comeback wins than losses. The big disappointment has to be Brett Favre who, despite his 32 comeback wins, recorded only six of those wins on the road! Meanwhile, Joe Montana and Peyton Manning share the record for the most road comeback wins (22), while Vinny Testaverde racked up an impressive 18.<br />
<br />
Other interesting stats include Daryle Lamonica never suffering a comeback loss at home, Tom Brady having only one comeback loss at home, and the Steelers not having a single comeback loss at home during an entire decade, the 1970s. Remarkably, Lamonica had only one comeback loss in 91 starts (ties not counted) and only two comeback losses altogether. Peyton Manning holds the record for most comeback wins in a single decade (29) while Drew Brees has the dubious record for most comeback losses in a single decade (20).<br />
<br />
Perhaps the oddest single stat I came across occurred in the 1998 season when, from November 8 through December 6, 18 consecutive comeback wins were recorded by home teams! Overall, home teams have a slight advantage over road teams in achieving a comeback win, but this advantage is not as large as one might expect. Since 1950, there have been 12,105 games played in the NFL (ties omitted) and 2,678 of those have been decided by comeback wins: 1,252 on the road, 1,412 at home, and 14 at neutral sites.<br />
</p><br />
<p>As interesting as these raw figures are, there are better ways to calculate who the real “comeback kings” were. One method simply involves figuring the percentage of comeback wins (excluding those in relief) versus the total number of games started (ties omitted) for each QB. Unitas, Favre, Montana, Testaverde, and Krieg each had one comeback win in relief; Esiason had two and Tittle had five. Among others, Earl Morrall and Chariie Conerly also had five comeback wins in relief. The following percentages emerge for the QBs listed above:<br />
</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th> </th><th>Comeback Wins</th><th>Total Starts (less ties)</th><th>Percentage</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;"> Johnny Unitas</td><td>34</td><td>190</td><td>17.9</td></tr>
<tr><td style="text-align: center;"> Eli Manning</td><td>22</td><td>130</td><td>16.9</td></tr>
<tr><td style="text-align: center;"> Joe Montana</td><td>30</td><td>187</td><td>16</td></tr>
<tr><td style="text-align: center;"> Peyton Manning</td><td>36</td><td>226</td><td>15.9</td></tr>
<tr><td style="text-align: center;"> Joe Theismann</td><td>21</td><td>132</td><td>15.9</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Ben Roethlisberger</td><td>20</td><td>127</td><td>15.7</td></tr>
<tr><td style="text-align: center;"> Randall Cunningham</td><td>22</td><td>143</td><td>15.4</td></tr>
<tr><td style="text-align: center;"> Steve Bartkowski</td><td>20</td><td>131</td><td>15.3</td></tr>
<tr><td style="text-align: center;"> Jake Plummer</td><td>20</td><td>142</td><td>14.8</td></tr>
<tr><td style="text-align: center;"> Dan Marino</td><td>37</td><td>258</td><td>14.3</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Tom Brady</td><td>25</td><td>181</td><td>13.8</td></tr>
<tr><td style="text-align: center;"> Drew Bledsoe</td><td>27</td><td>199</td><td>13.6</td></tr>
<tr><td style="text-align: center;"> Jim Kelly</td><td>24</td><td>177</td><td>13.6</td></tr>
<tr><td style="text-align: center;"> John Elway</td><td>33</td><td>251</td><td>13.1</td></tr>
<tr><td style="text-align: center;"> Dan Fouts</td><td>23</td><td>177</td><td>13</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Vinny Testaverde</td><td>28</td><td>218</td><td>12.8</td></tr>
<tr><td style="text-align: center;"> Dave Krieg</td><td>23</td><td>184</td><td>12.5</td></tr>
<tr><td style="text-align: center;"> Drew Brees</td><td>20</td><td>162</td><td>12.3</td></tr>
<tr><td style="text-align: center;"> Fran Tarkenton</td><td>29</td><td>244</td><td>11.9</td></tr>
<tr><td style="text-align: center;"> Warren Moon</td><td>25</td><td>213</td><td>11.7</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Joe Ferguson</td><td>20</td><td>175</td><td>11.4</td></tr>
<tr><td style="text-align: center;"> Y.A. Tittle</td><td>15</td><td>134</td><td>11.2</td></tr>
<tr><td style="text-align: center;"> Kerry Collins</td><td>20</td><td>187</td><td>10.7</td></tr>
<tr><td style="text-align: center;"> Boomer Esiason</td><td>18</td><td>178</td><td>10.1</td></tr>
<tr><td style="text-align: center;"> Brett Favre</td><td>31</td><td>322</td><td>9.6</td></tr>
</tbody></table></div><br />
<br />
<p>Johnny Unitas is the runaway winner here, even more so when we consider that during the 1950s and 1960s, the NFL average for all games was only 10.2 percent, which includes comeback wins by QBs who came off the bench. The AFL average was only 8.8 percent during the 1960s. Compare those figures with 11.7 percent, the percentage attained by NFL QBs (including those in relief) for all games over the last 30 years. Aside from Unitas, Y.A. Tittle also played during the 1950s and 1960s. Of the 25 QBs considered, only Joe Ferguson, Fran Tarkenton and Dan Fouts spent a significant portion of their careers during the 1970s when the percentages were 8.4 percent from 1970-73 (no overtime) and 10.7 percent from 1974-79 (overtime). The big surprise on this list has to be Joe Theismann, while the biggest bust is, once again, Brett Favre.<br />
<br />
There is another way to look at these figures – namely, by comparing the number of comeback wins (as starters) against career victories. These numbers represent the fact that some QBs just had to work a lot harder than other QBs to attain their wins. The 25 QBs from above: <br />
</p><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th> </th><th>Comeback Wins</th><th>Total Wins</th><th>Percentage</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;"> Steve Barkowski</td><td>20</td><td>60</td><td>33.3</td></tr>
<tr><td style="text-align: center;"> Vinny Testaverde</td><td>28</td><td>92</td><td>30.4</td></tr>
<tr><td style="text-align: center;"> Jake Plummer</td><td>21</td><td>71</td><td>29.6</td></tr>
<tr><td style="text-align: center;"> Eli Manning</td><td>22</td><td>77</td><td>28.6</td></tr>
<tr><td style="text-align: center;"> Johnny Unitas</td><td>34</td><td>124</td><td>27.4</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Drew Bledsoe</td><td>27</td><td>101</td><td>26.7</td></tr>
<tr><td style="text-align: center;"> Randall Cunningham</td><td>22</td><td>85</td><td>25.9</td></tr>
<tr><td style="text-align: center;"> Dan Fouts</td><td>23</td><td>89</td><td>25.8</td></tr>
<tr><td style="text-align: center;"> Joe Theismann</td><td>21</td><td>83</td><td>25.3</td></tr>
<tr><td style="text-align: center;"> Joe Ferguson</td><td>20</td><td>80</td><td>25.0</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Peyton Manning</td><td>36</td><td>150</td><td>24.0</td></tr>
<tr><td style="text-align: center;"> Dan Marino</td><td>37</td><td>155</td><td>23.9</td></tr>
<tr><td style="text-align: center;"> Warren Moon</td><td>25</td><td>105</td><td>23.8</td></tr>
<tr><td style="text-align: center;"> Kerry Collins</td><td>20</td><td>84</td><td>23.8</td></tr>
<tr><td style="text-align: center;"> Dave Krieg</td><td>23</td><td>101</td><td>22.8</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Joe Montana</td><td>30</td><td>133</td><td>22.6</td></tr>
<tr><td style="text-align: center;"> Fran Tarkenton</td><td>29</td><td>130</td><td>22.3</td></tr>
<tr><td style="text-align: center;"> Ben Roethlisberger</td><td>20</td><td>90</td><td>22.2</td></tr>
<tr><td style="text-align: center;"> Jim Kelly</td><td>24</td><td>110</td><td>21.8</td></tr>
<tr><td style="text-align: center;"> Boomer Esiason</td><td>18</td><td>83</td><td>21.7</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Drew Brees</td><td>20</td><td>97</td><td>20.6</td></tr>
<tr><td style="text-align: center;"> John Elway</td><td>33</td><td>162</td><td>20.4</td></tr>
<tr><td style="text-align: center;"> Y.A. Tittle</td><td>15</td><td>78</td><td>19.2</td></tr>
<tr><td style="text-align: center;"> Tom Brady</td><td>25</td><td>140</td><td>17.9</td></tr>
<tr><td style="text-align: center;"> Brett Favre</td><td>31</td><td>199</td><td>15.6</td></tr>
</tbody></table></div><br />
<br />
<p>In this case, Brett Favre being at the tail-end of the pack may be a good thing, because it could represent dominance on Favre’s part. In other words, Favre’s teams were often so far ahead by the time the fourth quarter rolled around that there was little need for a comeback win. Remember, among the things that comeback wins tell us is that the losing team actually dominated the game through the first three quarters – which really is a very good thing, as teams that have the lead after three quarters will win well over 70 percent of those games. Bucking this trend was Warren Moon, whose teams held the lead entering the fourth quarter only once in his 25 comeback wins! On the opposite end of the spectrum, in Brett Favre’s 32 roller-coaster comeback wins, his teams had the lead in 15 of those games after three quarters, lost a fourth quarter lead in 17 of those games, only to regain it by game’s end.<br />
</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th> </th><th>Comeback Losses</th><th>Total Starts</th><th>Percentage</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;"> Joe Theismann</td><td>7</td><td>132</td><td>5.3</td></tr>
<tr><td style="text-align: center;"> Tom Brady</td><td>10</td><td>181</td><td>5.5</td></tr>
<tr><td style="text-align: center;"> Jake Plummer</td><td>10</td><td>142</td><td>7.1</td></tr>
<tr><td style="text-align: center;"> John Elway</td><td>18</td><td>251</td><td>7.2</td></tr>
<tr><td style="text-align: center;"> Y.A. Tittle</td><td>10</td><td>134</td><td>7.5</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Eli Manning</td><td>10</td><td>130</td><td>7.7</td></tr>
<tr><td style="text-align: center;"> Ben Roethlisberger</td><td>10</td><td>127</td><td>7.9</td></tr>
<tr><td style="text-align: center;"> Joe Montana</td><td>15</td><td>187</td><td>8.0</td></tr>
<tr><td style="text-align: center;"> Brett Favre</td><td>26</td><td>322</td><td>8.1</td></tr>
<tr><td style="text-align: center;"> Dave Krieg</td><td>16</td><td>184</td><td>8.7</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Johnny Unitas</td><td>17</td><td>190</td><td>8.9</td></tr>
<tr><td style="text-align: center;"> Kerry Collins</td><td>17</td><td>187</td><td>9.1</td></tr>
<tr><td style="text-align: center;"> Joe Ferguson</td><td>17</td><td>175</td><td>9.7</td></tr>
<tr><td style="text-align: center;"> Dan Marino</td><td>26</td><td>258</td><td>10.1</td></tr>
<tr><td style="text-align: center;"> Peyton Manning</td><td>24</td><td>226</td><td>10.6</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Jim Kelly</td><td>19</td><td>177</td><td>10.7</td></tr>
<tr><td style="text-align: center;"> Drew Bledsoe</td><td>22</td><td>199</td><td>11.1</td></tr>
<tr><td style="text-align: center;"> Warren Moon</td><td>25</td><td>213</td><td>11.7</td></tr>
<tr><td style="text-align: center;"> Fran Tarkenton</td><td>30</td><td>244</td><td>12.3</td></tr>
<tr><td style="text-align: center;"> Vinny Testaverde</td><td>27</td><td>218</td><td>12.4</td></tr>
<tr><td style="text-align: center;"> </td><td> </td><td> </td><td> </td></tr>
<tr><td style="text-align: center;"> Dan Fouts</td><td>22</td><td>177</td><td>12.4</td></tr>
<tr><td style="text-align: center;"> Randall Cunningham</td><td>19</td><td>143</td><td>13.3</td></tr>
<tr><td style="text-align: center;"> Drew Brees</td><td>22</td><td>162</td><td>13.6</td></tr>
<tr><td style="text-align: center;"> Boomer Esiason</td><td>26</td><td>178</td><td>14.6</td></tr>
<tr><td style="text-align: center;"> Steve Bartkowski</td><td>22</td><td>131</td><td>16.8</td></tr>
</tbody></table></div><br />
<p>Again, the NFL average over the last 30 years (which includes comeback losses in relief) is 11.7 percent. Tom Brady is a big winner here, but, as noted below, he had certain advantages that many others did not. Joe Theismann is once again the big surprise. Y.A. Tittle deserves recognition among the old-timers. Steve Bartkowski lived on the razor’s edge, as he had only 131 starts, but 42 of them were decided by a comeback win or loss. Ironically, Elway and Favre, famous for comeback wins, were actually superior at preventing comeback losses. As Joe Montana once wisely commented, “It is much harder maintaining a slight lead in the fourth quarter than overcoming one.”<br />
</p><br />
<p>Kurt Warner suffered only five comeback losses in 129 starts and Jack Kemp had only three comeback losses in 108 starts!<br />
<br />
Okay, so what does this tell us? We can probably narrow our candidates for the all-time “comeback king” down to three selections – the brilliant all-around achievements of Unitas, who ranks at or near the top in every category and towers over all the other QBs from his own era. Also, Unitas had a personal hand in 21 of his 35 comeback wins (20 game-winning TD passes and one rushing touchdown), although it should be noted that his contemporary Y.A. Tittle had a personal hand in 15 of his 20 comeback wins (12 game-winning TD passes and three rushing TDs). Unitas and Tittle had a big advantage playing during an era that featured man-to-man defenses, rather than zones. Then there is the remarkable comeback ability on the road of Montana and Manning. After all, the single most difficult feat for any QB is to win consistently on the road before a hostile crowd and on a foreign field. Montana and Manning are both exceptional in this capacity. Unitas wasn’t shabby on the road either, as he had 15 comeback wins away from home. Of Montana’s 31 comeback wins, he had 14 game-winning TD passes and one TD run. Of Manning’s 36 comeback wins, he has twelve game-winning TD passes and three TD runs.<br />
<br />
Honorable mention goes to John Elway, Dan Marino and Tom Brady. Elway gets eliminated because he had a tremendous physical and psychological advantage playing at Mile High, which greatly padded his figures; 21 of his 33 comeback wins occurred at home and he had a personal hand in only eleven of his comeback wins (nine game-winning TD passes and two rushing TDs). Marino gets eliminated because, while he was very good in all areas (16 game-winning TD passes in his 37 comeback wins), he doesn’t overwhelm you in any particular category and, like Unitas, he had a very lackluster career winning percentage (44.7%) against winning teams; this latter factor is further emphasized by the fact that only twelve of his 37 comeback wins were achieved against teams with a winning record.<br />
<br />
Meanwhile, Brady appears likely to overtake Unitas in comeback win/loss differential and, among his many records, also has the best winning percentage against winning teams in NFL history – and 14 of his 25 comeback wins have come against teams with a winning record, which is tops among the 25 QBs considered, followed by Fouts (12 of 23), Montana (see below) and Kelly (12 of 24). However, he has had a personal hand in only ten of his 25 comeback wins, as nine of them came via a field goal and one by a defensive score. Also, a recent study by Nicholas Higgins ("Adjusted Comeback Efficiency”, Football Outsiders, February 2, 2010) indicates that Brady, despite having the highest percentage rate of converting “comeback opportunities”, had the third easiest “degree of difficulty” in achieving his remarkable record when compared with 59 other QBs who were active from 1998-2009. In contrast, Jake Plummer had the fifth harshest “degree of difficulty” during this same period, and thus Higgins has Plummer and twelve other QBs (including Peyton Manning) rated ahead of Brady in “Adjusted Comeback Efficiency”. Eli Manning, who has had 12 game-winning TD passes among his 22 comeback wins, was the top-rated QB in Higgins' survey.<br />
<br />
Unfortunately, we can only measure “degree of difficulty” for QBs who were active over the last 15 years or so, as it requires documenting the time and outcome of every single play. However, we do know that Brady, like Montana, had the advantage of playing in a poor division and, as a result, his overall strength of schedule is fairly weak. Also, as McKinley and Higgins pointed out, Brady has greatly benefited from having a defensive genius as his head coach, one of the best, if not the best, teams of all time, the best field goal kickers, among the easiest of on-the-field situational circumstances, and, beginning with the infamous “tuck” game, an extraordinary run of luck that borders on the unbelievable. With Brady, more than any other QB, it is extremely difficult trying to separate the “dancer from the dance”.<br />
<br />
But, have we gone far enough in our analysis? Well, as usual, the answer is no. We have barely touched the tip of the iceberg. Among the many nuances we have not even fathomed are these two factors: the ability of a QB to put his team in a position to win the game, and the ability of a QB, once he has attained a lead, to hold onto it. Both of these abilities are difficult to measure statistically, yet each plays a very important role in comeback wins and losses.<br />
<br />
There are two other factors that should be obvious, but are often overlooked when trying to determine who the “comeback kings” really are. Simply stated, they are the relative strength of the teams the QB is pitted against during the course of his career and the relative strength of the teams he plays for. Fortunately, Doug Drinen has provided us with avenues to explore these two factors.<br />
<br />
The relative strength of the teams that a QB opposed during his career has been given to us not once, but twice in recent articles (March 30 and April 12, 2009) by Mr. Drinen. Sadly, the great disparity between the results of these two articles draws into question the validity of either. However, both appear to show that Peyton Manning had a much more difficult strength of schedule than Unitas, who had a more difficult strength of schedule than Montana. As pointed out above with Tom Brady, strength of schedule, inherent in “degree of difficulty”, must, of necessity, be a major consideration. This latter factor suggests that Manning, given everything else, might be the one true “comeback king” – although it should be pointed out that, in another one of Drinen’s articles (August 6, 2008), Montana is given credit for a far better winning percentage (65.2%) against winning teams than Manning (49.1%) or Unitas (42.0%). Of Montana’s 31 comeback wins, 16 were achieved against teams with a winning record; Manning’s figure is 16 of 36, while Unitas totaled a lowly 9 of 35! Montana, as usual, was at his best when the pressure was greatest.<br />
<br />
The second factor is much more difficult to analyze. The relative strength of the teams that a QB plays for can be loosely determined by examining the “expected” won-loss records of those teams from year to year against their actual won-loss records and then determining the variance between the two. Any variance between “expected” and real won-loss records can, in large part, be explained by just how good or how bad that team really was. Using data from pro-football-reference.com, Manning has had thirteen full seasons with the Colts, who have managed to win thirteen more games than expected, Montana had ten full seasons with the 49ers and Chiefs, who won 3.4 more games than expected, and Unitas had thirteen full seasons with the Colts, who won 0.4 more games than expected. Inversely, these figures seem to tip the scales toward Unitas as the NFL’s one true “comeback king”, as Unitas’ teams were inferior to those of Montana, whose teams were inferior to those of Manning – thus making Unitas’ comeback win/loss differential all the more impressive.<br />
<br />
What all of this suggests is that, while Manning may have had a tougher schedule than either Unitas or Montana, he also had a better team surrounding him; thus, these two facets tend to offset each other. Team success and QB success most often go hand-in-hand. How to qualitatively separate the two presents us with our greatest mystery. When and if we are finally able to overcome this mystery should provide us with the last chapter to our story, but my suspicion is that Peyton Manning will eventually emerge as the NFL’s true “comeback king”.<br />
<br />
Until then, like Tennyson’s <i>Ulysses</i>, I shall continue to “Follow knowledge like a sinking star, Beyond the utmost bound of human thought.”</p>Unknownnoreply@blogger.com7tag:blogger.com,1999:blog-5204092591876211047.post-3537315959634315102012-02-24T23:29:00.001-05:002012-02-25T09:30:17.932-05:00Spygate: The Effectiveness of Cheating<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiWMZxd-Zg0p27FuVlq6qvc60nkDyDPWyTuWRDmHEelpib6a_2KhZF8CcaYYwTVO1ido2KUhM4lGRBXmJnTC0IHRDQxs-pjjrxYspERN3Pj6_yW-o9Ml5J8vw0QGswQiGte7x_EvDP_O5zW/s1600/cheating.jpg" imageanchor="1" style="clear:right; float:right; margin-left:1em; margin-bottom:1em"><img border="0" height="113" width="170" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiWMZxd-Zg0p27FuVlq6qvc60nkDyDPWyTuWRDmHEelpib6a_2KhZF8CcaYYwTVO1ido2KUhM4lGRBXmJnTC0IHRDQxs-pjjrxYspERN3Pj6_yW-o9Ml5J8vw0QGswQiGte7x_EvDP_O5zW/s320/cheating.jpg" /></a></div>by Paul Benjamin<br />
<br />
<p>Enough time has passed to evaluate the effect of Bill Belichick's cheating. The cheating took place from 2000-2006, and was ended early in 2007, giving 5 years of data since.<br />
<br />
The known cheating consisted of two components, as revealed by Eric Mangini. First, the Patriots would tape opponents defensive hand signals. This permitted coaches to correlate the signals with the defensive alignments and figure out what each signal meant. Second, the Patriots used unregistered radio frequencies, so that the second time they played that team the offensive coordinator could watch the defensive signals and choose the perfect play to tell the quarterback. Normally, the referee cuts the registered radio frequency 15 seconds before the snap, so the offensive coordinator cannot communicate with the quarterback after the defense makes its substitutions, but the Patriots were the only team in the league that had radio equipment that could broadcast on multiple frequencies simultaneously. After the referee would cut the registered frequency, the quarterback could still hear the coordinator on the other frequency, so he could be told the defensive alignment he was facing and what play to call.<br />
<br />
So the plays and blocking schemes were always perfect ones to exploit each defensive alignment.<a name='more'></a><br />
<br />
To measure the effect of this scheme, we need to isolate pairs of games in which the Patriots would be obtaining tape then using it. Some teams are played only every three years, so that data is not likely to show much. Teams in the same division are played twice every year and tape from the previous year can be used, so the effect of the cheating scheme may be harder to detect. I started by analyzing games played in the same season against out-of-division opponents. The second game against such an opponent is always a postseason game, so this has the advantage of measuring postseason success. After looking at these games, I saw that the Patriots have twice faced a division opponent (Jets) in the postseason, so I added those games, too. So the analysis below is of all opponents the Patriots played in the regular season and postseason of the same year. There are 30 such games.<br />
<br />
The overall result is that during the spying era, the Patriots were 4-5 during the regular season but went 6-2 against the same teams in the postseason, so they did much better the second time. Since the cheating was ended, the Patriots have gone 5-2 in the regular season but dropped to 2-4 in the postseason, with their offense per game dropping by 10 points in the postseason, so they are doing much worse the second time, and primarily because their offense is tanking. This is despite the Patriot offense scoring more points per game during 2007-2011 than they did in 2000-2006, which reflects they have more talent.<br />
<br />
The numbers indicate that the cheating scheme was worth more than a touchdown a game.<br />
<br />
Results of Patriots' games, showing only opponents they played both in regular season and postseason:</p><br />
After cheating was ended:<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th> </th><th>Opponent</th><th>Regular Season</th><th>Postseason</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;">2011</td><td>Denver Broncos</td><td>W 41-23 (Away, week 15)</td><td>W 45-10</td> </tr>
<tr><td style="text-align: center;"> </td><td>New York Giants</td><td>L 20-24 (Home, week 9)</td><td>L 17-21</td></tr>
<tr><td style="text-align: center;">2010</td><td>New York Jets</td><td>L 14-28 (Away, week 2)</td><td>L 21-28</td></tr>
<tr><td style="text-align: center;"> </td><td>New York Jets</td><td>W 45-3 (Home, week 13)</td><td> </td></tr>
<tr><td style="text-align: center;">2009</td><td>Baltimore Ravens</td><td>W 27-21 (Home, week 4)</td><td>L 14-33</td></tr>
<tr><td style="text-align: center;">2007</td><td>San Diego Chargers</td><td>W 38-14 (Home, week 2)</td><td>W 21-12</td></tr>
<tr><td style="text-align: center;"> </td><td>New York Giants</td><td>W 38-35 (Away, week 17)</td><td>L 14-17 (Superbowl)</td></tr>
</tbody></table></div><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th>Summary</th><th>Regular Season</th><th>Postseason</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;">Record</td><td>5-2</td><td>2-4</td> </tr>
<tr><td style="text-align: center;">Points Scored per Game;</td><td>31.9</td><td>22.0</td></tr>
<tr><td style="text-align: center;">Points Allowed per Game</td><td>21.1</td><td>20.2</td></tr>
</tbody></table></div><br />
While cheating:<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th> </th><th>Opponent</th><th>Regular Season</th><th>Postseason</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;">2006</td><td>New York Jets</td><td>W 24-17 (Away, week 2)</td><td>W 37-16</td> </tr>
<tr><td style="text-align: center;"> </td><td>New York Jets</td><td>L 14-17 (Home, week 10)</td><td> </td></tr>
<tr><td style="text-align: center;"> </td><td>Indianapolis Colts</td><td>L 20-27 (Home, week 9)</td><td>L 34-38</td></tr>
<tr><td style="text-align: center;">2005</td><td>Denver Broncos</td><td>L 20-28 (Away, week 6)</td><td>L 13-27</td></tr>
<tr><td style="text-align: center;">2004</td><td>Indianapolis Colts</td><td>W 27-24 (Home, week 1)</td><td>W 20-3</td></tr>
<tr><td style="text-align: center;"> </td><td>Pittsburgh Steelers</td><td>L 20-34 (Away, week 8)</td><td>W 41-27</td></tr>
<tr><td style="text-align: center;">2003</td><td>Tennessee Titans</td><td>W 38-30 (Home, week 5)</td><td>W 17-14 (Superbowl)</td></tr>
<tr><td style="text-align: center;"> </td><td>Indianapolis Colts</td><td>W 38-34 (Away, week 13)</td><td>W 24-17</td></tr>
<tr><td style="text-align: center;">2001</td><td>St. Louis Rams</td><td>L 17-24 (Home, week 10)</td><td>W 20-17 (Superbowl)</td></tr>
</tbody></table></div><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th>Summary</th><th>Regular Season</th><th>Postseason</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;">Record</td><td>4-5</td><td>6-2</td> </tr>
<tr><td style="text-align: center;">Points Scored per Game;</td><td>24.2</td><td>25.8</td></tr>
<tr><td style="text-align: center;">Points Allowed per Game</td><td>26.1</td><td>19.9</td></tr>
</tbody></table></div>Unknownnoreply@blogger.com23tag:blogger.com,1999:blog-5204092591876211047.post-49102266189633048412012-02-06T19:55:00.000-05:002012-02-06T20:33:01.114-05:00Ring Probability Added<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><br />
by Joe Harris<br />
When arguing a QB's "greatness" people often quote the number of rings a player has as a definitive conclusion to a debate. For example, <i>Dilfer is obviously greater than Marino because he has a ring. And there is nothing else to it.</i> That statement takes the logic a bit further than most people would, but that is essentially how a lot of fans view the world. Whilst I am not a fan of this form of logic, I thought that it would be interesting to look at this concept through the lens of WPA or, more specically, RPA - Ring Probability Added.<br />
<br />
<b>Ring Probability Added</b><br />
The basic idea is to take Brian's WPA stats and weight it depending on the magnitude of the game. For example, in 2004 when New England beat Carolina, Tom Brady essentially did enough to win the game single-handedly with +0.97 WPA. This corresponds to +0.49 RPA - he increased New England's chances of winning the Superbowl by 49%.<br />
<a name='more'></a><br />The game magnitudes I assigned were:<br />
<ul>Superbowl: 50%</ul>
<ul>Conference Championship: 25%</ul>
<ul>Divisional Round: 12.5%</ul>
<ul>Wild Card Round: 6.25%</ul>
<ul>Regular Season Game: 0.4%</ul>
The logic behind the Regular Season weighting was that I wanted to keep all the games equal. So I used a weighting of 1/256 (the number of games in a season). What this doesn't do is account for the fact that, when it comes to winning a Superbowl, 0 wins for the season is just as useful as 6 wins - either way your team misses the playoffs. But in the end the regular season had very little impact on the final results.<br />
I thought it would also be fun to think about the Total Rings a player wins for himself and his teammates. Based on the assumption of 53 players on an NFL roster, I multiply the RPA by 53. Using this logic I conclude that in Brady's career he has won 73 rings for himself and his teammates.<br />
<br />
It should go without saying that every QBs RPA is extremely dependent on the performance of the O-line and receivers in the same games.<br />
<br />
<b>The Results</b><br />
The results are not hugely surprising. Brady leads the way with +1.38 RPA, followed by the Manning brothers, Roethlisberger and Brees - the winners of 5 of the last 6 Superbowls.<br />
<br />
My favourite result is that Rex Grossman managed to total -0.38 RPA or -20 Total Rings in just one season. This is amazing but it is really a testament to that Bears defence; Not only did he play badly enough to lose each playoff game, the rest of the team bailed him out just enough that he had a chance to further hurt their chances in the next round.<br />
<div class="tableHolder">
<br />
<table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th>Rank</th><th>Name</th><th>RPA</th><th>Total Rings</th> </tr>
</thead><tbody>
<tr><td style="text-align: center;">1</td><td>T. Brady</td><td>+1.38</td><td>73</td> </tr>
<tr><td style="text-align: center;">2</td><td>P.Manning</td><td>+0.75</td><td>40</td></tr>
<tr><td style="text-align: center;">3</td><td>B.Roethlisberger</td><td>+0.57</td><td>30</td></tr>
<tr><td style="text-align: center;">4</td><td>E.Manning</td><td>+0.56</td><td>30</td></tr>
<tr><td style="text-align: center;">5</td><td>D.Brees</td><td>+0.52</td><td>27</td></tr>
<tr><td style="text-align: center;">6</td><td>K.Warner</td><td>+0.49</td><td>26</td></tr>
<tr><td style="text-align: center;">7</td><td>J.Delhomme</td><td>+0.30</td><td>16</td></tr>
<tr><td style="text-align: center;">8</td><td>A.Rodgers</td><td>+0.27</td><td>14</td></tr>
<tr><td style="text-align: center;">9</td><td>D.Culpepper</td><td>+0.16</td><td>9</td></tr>
<tr><td style="text-align: center;">10</td><td>S.McNair</td><td>+0.16</td><td>8</td></tr>
<tr><td style="text-align: center;">11</td><td>M.Sanchez</td><td>+0.15</td><td>8</td></tr>
<tr><td style="text-align: center;">12</td><td>M.Bulger</td><td>+0.12</td><td>6</td></tr>
<tr><td style="text-align: center;">13</td><td>J.Garcia</td><td>+0.09</td><td>5</td></tr>
<tr><td style="text-align: center;">14</td><td>P.Rivers</td><td>+0.08</td><td>4</td></tr>
<tr><td style="text-align: center;">15</td><td>B.Johnson</td><td>+0.08</td><td>4</td></tr>
<tr><td style="text-align: center;"></td><td></td><td></td><td></td></tr>
<tr><td style="text-align: center;">145</td><td>J.Flacco</td><td>-0.11</td><td>-6</td></tr>
<tr><td style="text-align: center;">146</td><td>T.Dilfer</td><td>-0.12</td><td>-6</td></tr>
<tr><td style="text-align: center;">147</td><td>R.Gannon</td><td>-0.14</td><td>-7</td></tr>
<tr><td style="text-align: center;">148</td><td>K.Collins</td><td>-0.23</td><td>-12</td></tr>
<tr><td style="text-align: center;">149</td><td>R.Grossman</td><td>-0.37</td><td>-20</td></tr>
</tbody></table>
</div>
<br />
<b>Some Final Thoughts</b><br />
When I started this analysis I was hoping that the results would show Peyton in a more favourable light. Whilst I obviously wasn't expecting him to outperform Tom Brady, I did think that he would do slightly better vs Eli and Big Ben. However, if you account for the number of seasons each QB has played all three QBs have just over 3.5 RPA per season.<br />
<br />
For good quarterbacks, having a good defence and running game is still very important when it comes to accumulating RPA. The chart below shows that Peyton has actual done more to get his teams to Superbowls than Tom Brady. Unfortunately for him this only translated to 2 Superbowls in real life vs Brady's 5.<br />
<br />
(click on the chart for a larger, clearer version.) <br />
<br />
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiV0_KqFRrpKnxyViEHNixUj7i3yQAfXFGRb9aK2spE7rTiEFtauwSdZecvtF8OV32aEFuEgx9zPNjAdYlFAoC9s43IN7tq5Si80WJwSowhhBqaIpFbxqeK8vIz0SM7M4R3VbBC7wDNvOKD/s1600/Chart.bmp" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="287" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiV0_KqFRrpKnxyViEHNixUj7i3yQAfXFGRb9aK2spE7rTiEFtauwSdZecvtF8OV32aEFuEgx9zPNjAdYlFAoC9s43IN7tq5Si80WJwSowhhBqaIpFbxqeK8vIz0SM7M4R3VbBC7wDNvOKD/s400/Chart.bmp" width="400" /></a><br />
Conversely, for bad quarterbacks, it can be better to have a bad defence - as highlighted by Rex Grossman who otherwise would never have been in a position to post such terrible stats in big games.Unknownnoreply@blogger.com10tag:blogger.com,1999:blog-5204092591876211047.post-17677070936158933142012-01-22T11:03:00.002-05:002012-01-29T17:26:25.456-05:00Betting Market Power Rankings – Conference Finals Edition<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><p>by Michael Beuoy<br />
<br />
<i>Editor's Note: Michael submitted this earlier this week and I was late in posting it. EA</i><br />
<br />
Here are the final Betting Market Power Rankings of the season, updated with the results of the prior week and the lines for this week. As promised last week, I will also revisit my predictions for the lines and over/unders for the conference final games.<br />
<br />
Refer to <a href="http://community.advancednflstats.com/2012/01/betting-market-power-rankings-offense.html">last week’s post</a> for more detail on the weights used.<br />
Here is a glossary of terms:<br />
<br />
<strong>LSTWK</strong> - The betting market rank as of the prior week<br />
<strong>GPF</strong> - Stands for Generic Points Favored. It’s what you would expect a team to be favored by against a league average opponent at a neutral site.<br />
<strong>oGPF</strong> – Offensive Generic Points Favored. The component of a team’s total GPF attributable to its ability to score points.<br />
<strong>dGPF</strong> – Defensive Generic Points Favored. The component of a team’s total GPF attributable to its ability to prevent the other team from scoring points<br />
<strong>O RANK</strong> – The team’s oGPF ranking.<br />
<strong>D RANK</strong> – The team’s dGPF ranking.<br />
<strong>GWP</strong> - Stands for Generic Win Probability. I converted the GPF into a generic win probability using the following formula: GWP = 1/(1+exp(-GPF/7)).<a name='more'></a><br />
<br />
And here is the ranking table (the Rank column is relative to all 32 teams, but I’m only showing the 12 playoff teams):<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"; white-space: nowrap;></col></colgroup><thead>
<tr><th>Rank</th><th>Team</th><th>LSTWK</th><th>GPF</th><th>oGPF</th><th>dGPF</th><th>GWP</th><th>ORank</th><th>DRank</th></tr>
</thead><td style="text-align: center;"> 1</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO</td><td>1</td><td>10.0</td><td>10.5</td><td>-0.5</td><td>0.81</td><td>1</td><td>21</td></tr>
<td style="text-align: center;"> 2</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td>3</td><td>9.0</td><td>8.5</td><td>0.5</td><td>0.79</td><td>2</td><td>12</td></tr>
<td style="text-align: center;"> 4</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/> GB</td><td>2</td><td>6.5</td><td>6.5</td><td>0.0</td><td>0.72</td><td>3</td><td>18</td></tr>
<td style="text-align: center;"> 5</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td>8</td><td>4.5</td><td>3.5</td><td>1.0</td><td>0.66</td><td>6</td><td>9</td></tr>
<td style="text-align: center;"> 6</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/> SF</td><td>5</td><td>4.5</td><td>0.0</td><td>4.5</td><td>0.66</td><td>14</td><td>2</td></tr>
<td style="text-align: center;"> 7</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td>7</td><td>4.5</td><td>1.0</td><td>3.5</td><td>0.66</td><td>11</td><td>3</td></tr>
<td style="text-align: center;"> 8</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PIT/PIT_logo-20x20.gif"/> PIT</td><td>6</td><td>4.0</td><td>-0.5</td><td>4.5</td><td>0.64</td><td>16</td><td>1</td></tr>
<td style="text-align: center;"> 9</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ATL/ATL_logo-20x20.gif"/> ATL</td><td>11</td><td>3.5</td><td>1.0</td><td>2.5</td><td>0.62</td><td>12</td><td>6</td></tr>
<td style="text-align: center;"> 11</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DET/DET_logo-20x20.gif"/> DET</td><td>9</td><td>2.5</td><td>3.5</td><td>-1.0</td><td>0.60</td><td>5</td><td>23</td></tr>
<td style="text-align: center;"> 15</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td>16</td><td>0.5</td><td>-2.5</td><td>3.0</td><td>0.52</td><td>23</td><td>5</td></tr>
<td style="text-align: center;"> 18</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CIN/CIN_logo-20x20.gif"/> CIN</td><td>19</td><td>-1.0</td><td>-1.0</td><td>0.0</td><td>0.47</td><td>20</td><td>16</td></tr>
<td style="text-align: center;"> 24</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td>24</td><td>-4.0</td><td>-3.0</td><td>-1.0</td><td>0.37</td><td>25</td><td>22</td></tr>
</tbody></table></div><br />
<li>New England is the clear favorite among the field of four.</li><br />
<br />
<br />
<br />
<br />
<li>The remaining three teams all have identical GPF, indicating a competitive matchup in the Superbowl should New England happen to lose this weekend.</li><br />
<br />
<br />
<br />
<br />
<p>Here is how the model predicted the point spreads and over/unders for the two Conference Finals. I’ll show two versions of the predictions. The first is just copied from last week’s post. The second includes one more piece of information, which is how each team performed against the market’s expectation. As noted in my <a href="http://community.advancednflstats.com/2011/12/betting-market-power-rankings.html">original post</a> on this topic, the market appears to trust the outcome of each game with 15% credibility.</p><br />
<strong>Last Week</strong><br />
<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"; white-space: nowrap;></col></colgroup><thead>
<tr style="background-color: #aad5ff;"><td class="headhover"><b>Game</b></td><td class="headhover"><b>Pred Line</b></td><td class="headhover"><b>ActLine</b></td><td class="headhover"><b>Diff</b></td><td class="headhover"><b>Pred OU</b></td><td class="headhover"><b>Act OU</b></td><td class="headhover"><b>OU Diff</b></td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL @ NE <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/></td><td>6.5</td><td>7.0</td><td>0.5</td><td>49.0</td><td>50.5</td><td>1.5</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG @ SF <img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/></td><td>3.5</td><td>2.5</td><td>-1.0</td><td>42.0</td><td>42.0</td><td>0.0</td></tr>
</tbody></table></div><br />
<strong>This Week (factors in Divisional Round results)</strong><br />
<br />
<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"; white-space: nowrap;></col></colgroup><thead>
<tr style="background-color: #aad5ff;"><td class="headhover"><b>Game</b></td><td class="headhover"><b>Pred Line</b></td><td class="headhover"><b>ActLine</b></td><td class="headhover"><b>Diff</b></td><td class="headhover"><b>Pred OU</b></td><td class="headhover"><b>Act OU</b></td><td class="headhover"><b>OU Diff</b></td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL @ NE <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/></td><td>7.5</td><td>7.0</td><td>-0.5</td><td>49.0</td><td>50.5</td><td>1.5</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG @ SF <img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/></td><td>2.5</td><td>2.5</td><td>0.0</td><td>42.0</td><td>42.0</td><td>0.0</td></tr>
</tbody></table></div><br />
<p>Last week’s prediction was fairly close (not as close as Brian’s <a href="http://twitter.com/#!/Adv_NFL_Stats/status/158717588824797184" >tweet</a>, but this week’s nudged closer due to the model factoring in the Giants and Patriots beating the market’s expectation by about 25 points and 20 points, respectively. SF also beat expectations, but only by about 7 points, while the Ravens performed as expected by beating the Texans by a touchdown.</p><br />
<br />
<i>Editor's note: The last two tables are a revision from the original post. The tables had been switched in the original version.</i><br />
<br />
<br />Unknownnoreply@blogger.com5tag:blogger.com,1999:blog-5204092591876211047.post-38778573690233101882012-01-13T02:30:00.000-05:002012-01-13T02:40:55.072-05:00Best (And Worst) Post-Season Coaching Records Since 1950, via a Binomial Viewby Jim Glass<br />
<style type="text/css">
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
th,td
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><p>Vince Lombardi's post-season coaching W-L record of 9-1, .900, is the best ever. Or maybe not, some say Joe Gibb's record of 17-7 is standard to beat - "only" .708, but over a run of 2.4 times as many games it is much harder to keep a big winning record. How can we compare them?<br />
<br />
One way is to compute the binomial probability of a coach attaining a given won-loss record by random chance. For instance, in Herm Edwards' first year coaching my Jets, he went 10-6. I was happy. That .625 winning record was better than Tom Landry's .607 and our former coach Bill Parcells' .570 - better than a Hall of Famer's and sure future Hall of Famer's! It looked like we had a great coach. Except that Parcells earned his .570 over 303 games and Landry earned his .607 over 418, while Herm had earned his .625 over only 16. <br />
<br />
The binomial calculation can give the probability of winning a given number of games out of any number played, and so providea a common standard to apply to the W-L performances of different coaches with different W-L percentages over differing numbers of games. It told me that, assuming game outcomes were random with a 50% chance of winning/losing, Herm's record of .625 (or better) had only a 22% probability of occurring by random chance, which was pretty encouraging - but Bill's .570 record had only a 1% chance, and Tom's .607 had only a 0.001% chance. So perhaps it was premature to declare Herm a better coach than Tuna and Tom (as indeed it turned out to be).<a name='more'></a><br />
<br />
Now it's playoff time, so I wondered: what if we applied this common standard when looking at the playoff coaching records of Belichick, McCarthy, Dungy, and all the other coaches of all post-season games back to 1950? And suppose we set the random probability of winning each playoff game not at 50%, but at the <em>actual</em> probability of winning indicated by the relative strength of the competing teams and home field advantage?<br />
<br />
Which coaches would we see to have beaten the odds, which not, and who would the surprises be? This is the exercise followed below.<br />
<br />
<strong>Method</strong><br />
I used the PFR.com data base to compile a list of all NFL post-season games and coaches from 1950 through 2010, using teams' "<a href="http://www.pro-football-reference.com/blog/?p=37">Simple Rating System</a>" numbers to gauge their relative strength. The SRS gives a team's strength-of-schedule adjusted average net points per game (points for minus points against) compared to the league average. To this I added 2.5 points to the rating of the home team (when there was one). From the resulting point differential the conventional Pythagorean formula provides a winning probability for each team in each game. <br />
<br />
Taking all the games for each coach, the resulting "<a href="http://community.advancednflstats.com/2011/12/towards-better-pythagorean-should.html">Unit Pythagorean</a>" rating provides his expected W-L percentage. <br />
Using this percentage instead of 50% as the probability of winning, the binomial calculation gives the probability of the coach's actual W-L record resulting from random chance.<br />
<br />
Take Dick Vermeil as an example. His 6-5 winning record with a Super Bowl championship appears very credible on its face. But his teams averaged a full touchdown better than the opposition by SRS, were the higher rated in every single game, and on top of that had home field advantage seven times to only twice for the opponent. All this gives him a .689 expecting winning rate, the highest of any coach with three or more post-season games. Put that into the calculator and it says his actual 6-5, .545 record was better than only a meager 9% of those expected by chance - random chance would beat his playoff record 91% of the time.<br />
<br />
At the other extreme, Blanton Collier as the successor to the great Paul Brown disappointed the Browns fans of his day by going only 3-4 in the post-season. But as he had only a .255 expected winning percentage, his .429 winning record was superior to .746 of those expected by chance, the highest binomial rating of any coach with a losing record.<br />
<br />
More recently, Ken Whisenhunt has gone 4-2, .667, in the playoffs with only a .281 expected winning rate, giving him a winning record better than .944 of those expected by chance - the highest binomial rating among all the 128 coaches to take a team to the playoffs since 1950. (Lombardi is #2.)<br />
<br />
<strong>The numbers, and interpreting them</strong><br />
I've limited the list below to the 70 coaches who have coached five or more playoff games since 1950. <br />
<br />
Given for each is the number of playoff games coached, his W-L count, actual winning percentage, expected winning percentage, and the binomial calculation of the percentage of random results his record exceeds. Thus, a figure of .612 indicates the coach's record is <em>better than</em> 61.2% of the records produced by chance (given his expected winning percentage).<br />
<br />
Personally, I do not consider these numbers to be very persuasive evidence of "how good" a coach is or was. The sample sizes for all are small to very small and vary greatly, and random results in just a few close games can make a very big difference in the binomial result. <br />
<br />
But this data does show, objectively, how well each coach's actual record in the playoffs compares to reasonable expectation. Is Coach X's "great" record in the playoffs really as good as it looks? Is Coach Y's "poor" record actually better than it looks? Does Marty Schottenheimer really have the worst playoff coaching record of all time? (No, but close.) <br />
<br />
For perspective on (and arguments about) such questions, I think this data is useful. <br />
<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th>Rank</th><th>Name</th><th>Games</th><th> </th><th>Won</th><th>Lost</th><th>Won Lost%</th><th>Expected WL%</th><th>Binomial Performance</th></tr>
</thead><tbody>
<td style="text-align: center;"> 1</td><td>Ken Whisenhunt</td><td>6</td><td></td><td>4</td><td>2</td><td>0.667</td><td>0.281</td><td>0.944</td></tr>
<tr/><td style="text-align: center;"> 2</td><td>Vince Lombardi</td><td>10</td><td></td><td>9</td><td>1</td><td>0.900</td><td>0.662</td><td>0.901</td></tr>
<tr/><td style="text-align: center;"> 3</td><td>Weeb Ewbank</td><td>5</td><td></td><td>4</td><td>1</td><td>0.800</td><td>0.448</td><td>0.871</td></tr>
<tr/><td style="text-align: center;"> 4</td><td>Bum Phillips</td><td>7</td><td></td><td>4</td><td>3</td><td>0.571</td><td>0.308</td><td>0.863</td></tr>
<tr/><td style="text-align: center;"> 5</td><td>Joe Gibbs</td><td>24</td><td></td><td>17</td><td>7</td><td>0.708</td><td>0.578</td><td>0.862</td></tr>
<tr/><td style="text-align: center;"> 6</td><td>Jimmy Johnson</td><td>13</td><td></td><td>9</td><td>4</td><td>0.692</td><td>0.504</td><td>0.860</td></tr>
<tr/><td style="text-align: center;"> 7</td><td>Tom Flores</td><td>11</td><td></td><td>8</td><td>3</td><td>0.727</td><td>0.521</td><td>0.857</td></tr>
<tr/><td style="text-align: center;"> 8</td><td>Chuck Noll</td><td>24</td><td></td><td>16</td><td>8</td><td>0.667</td><td>0.545</td><td>0.839</td></tr>
<tr/><td style="text-align: center;"> 9</td><td>Bill Belichick</td><td>21</td><td></td><td>15</td><td>6</td><td>0.714</td><td>0.601</td><td>0.797</td></tr>
<tr/><td style="text-align: center;"> 10</td><td>Tom Coughlin</td><td>15</td><td></td><td>8</td><td>7</td><td>0.533</td><td>0.396</td><td>0.796</td></tr>
<tr/><td style="text-align: center;"> </td><td> </td><td> </td><td></td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>
<tr/><td style="text-align: center;"> 11</td><td>John Fox</td><td>8</td><td></td><td>5</td><td>3</td><td>0.625</td><td>0.422</td><td>0.790</td></tr>
<tr/><td style="text-align: center;"> 12</td><td>Bill Walsh</td><td>14</td><td></td><td>10</td><td>4</td><td>0.714</td><td>0.574</td><td>0.783</td></tr>
<tr/><td style="text-align: center;"> 13</td><td>Hank Stram</td><td>8</td><td></td><td>5</td><td>3</td><td>0.625</td><td>0.427</td><td>0.782</td></tr>
<tr/><td style="text-align: center;"> 14</td><td>Don McCafferty</td><td>5</td><td></td><td>4</td><td>1</td><td>0.800</td><td>0.530</td><td>0.773</td></tr>
<tr/><td style="text-align: center;"> 15</td><td>Blanton Collier</td><td>7</td><td></td><td>3</td><td>4</td><td>0.429</td><td>0.255</td><td>0.746</td></tr>
<tr/><td style="text-align: center;"> 16</td><td>Rex Ryan</td><td>6</td><td></td><td>4</td><td>2</td><td>0.667</td><td>0.452</td><td>0.741</td></tr>
<tr/><td style="text-align: center;"> 17</td><td>Raymond Berry</td><td>5</td><td></td><td>3</td><td>2</td><td>0.600</td><td>0.379</td><td>0.718</td></tr>
<tr/><td style="text-align: center;"> 18</td><td>Bill Parcells</td><td>19</td><td></td><td>11</td><td>8</td><td>0.579</td><td>0.500</td><td>0.676</td></tr>
<tr/><td style="text-align: center;"> 19</td><td>Jerry Burns</td><td>6</td><td></td><td>3</td><td>3</td><td>0.500</td><td>0.340</td><td>0.667</td></tr>
<tr/><td style="text-align: center;"> 20</td><td>Marv Levy</td><td>19</td><td></td><td>11</td><td>8</td><td>0.579</td><td>0.504</td><td>0.663</td></tr>
<tr/><td style="text-align: center;"> </td><td> </td><td> </td><td></td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>
<tr/><td style="text-align: center;"> 21</td><td>Brian Billick</td><td>8</td><td></td><td>5</td><td>3</td><td>0.625</td><td>0.512</td><td>0.610</td></tr>
<tr/><td style="text-align: center;"> 22</td><td>Barry Switzer</td><td>7</td><td></td><td>5</td><td>2</td><td>0.714</td><td>0.594</td><td>0.593</td></tr>
<tr/><td style="text-align: center;"> 23</td><td>Dan Reeves</td><td>20</td><td></td><td>11</td><td>9</td><td>0.550</td><td>0.499</td><td>0.592</td></tr>
<tr/><td style="text-align: center;"> 24</td><td>Jeff Fisher</td><td>11</td><td></td><td>5</td><td>6</td><td>0.455</td><td>0.379</td><td>0.591</td></tr>
<tr/><td style="text-align: center;"> 25</td><td>John Madden</td><td>16</td><td></td><td>9</td><td>7</td><td>0.563</td><td>0.504</td><td>0.586</td></tr>
<tr/><td style="text-align: center;"> 26</td><td>Mark Holmgren</td><td>24</td><td></td><td>13</td><td>11</td><td>0.542</td><td>0.503</td><td>0.569</td></tr>
<tr/><td style="text-align: center;"> 27</td><td>Mike Shanahan</td><td>13</td><td></td><td>8</td><td>5</td><td>0.615</td><td>0.556</td><td>0.556</td></tr>
<tr/><td style="text-align: center;"> 28</td><td>Bill Cowher</td><td>21</td><td></td><td>12</td><td>9</td><td>0.571</td><td>0.534</td><td>0.548</td></tr>
<tr/><td style="text-align: center;"> 29</td><td>John Harbaugh</td><td>7</td><td></td><td>4</td><td>3</td><td>0.571</td><td>0.479</td><td>0.546</td></tr>
<tr/><td style="text-align: center;"> 30</td><td>Ray Malavasi</td><td>6</td><td></td><td>3</td><td>3</td><td>0.500</td><td>0.402</td><td>0.540</td></tr>
<tr/><td style="text-align: center;"> </td><td> </td><td> </td><td></td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>
<tr/><td style="text-align: center;"> 31</td><td>Mike Tomlin</td><td>7</td><td></td><td>5</td><td>2</td><td>0.714</td><td>0.630</td><td>0.513</td></tr>
<tr/><td style="text-align: center;"> 32</td><td>Sam Wyche</td><td>5</td><td></td><td>3</td><td>2</td><td>0.600</td><td>0.495</td><td>0.509</td></tr>
<tr/><td style="text-align: center;"> 33</td><td>Mike McCarthy</td><td>7</td><td></td><td>5</td><td>2</td><td>0.714</td><td>0.634</td><td>0.504</td></tr>
<tr/><td style="text-align: center;"> 34</td><td>John Robinson</td><td>10</td><td></td><td>4</td><td>6</td><td>0.400</td><td>0.355</td><td>0.500</td></tr>
<tr/><td style="text-align: center;"> 35</td><td>Tom Landry</td><td>36</td><td></td><td>20</td><td>16</td><td>0.556</td><td>0.543</td><td>0.492</td></tr>
<tr/><td style="text-align: center;"> 36</td><td>George Seifert</td><td>15</td><td></td><td>10</td><td>5</td><td>0.667</td><td>0.636</td><td>0.482</td></tr>
<tr/><td style="text-align: center;"> 37</td><td>Norv Turner</td><td>8</td><td></td><td>4</td><td>4</td><td>0.500</td><td>0.458</td><td>0.458</td></tr>
<tr/><td style="text-align: center;"> 38</td><td>Jerry Glanville</td><td>7</td><td></td><td>3</td><td>4</td><td>0.429</td><td>0.403</td><td>0.413</td></tr>
<tr/><td style="text-align: center;"> 39</td><td>Andy Reid</td><td>19</td><td></td><td>10</td><td>9</td><td>0.526</td><td>0.526</td><td>0.409</td></tr>
<tr/><td style="text-align: center;"> 40</td><td>John Gruden</td><td>9</td><td></td><td>5</td><td>4</td><td>0.556</td><td>0.541</td><td>0.400</td></tr>
<tr/><td style="text-align: center;"> </td><td> </td><td> </td><td></td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>
<tr/><td style="text-align: center;"> 41</td><td>Tony Dungy</td><td>19</td><td></td><td>9</td><td>10</td><td>0.474</td><td>0.479</td><td>0.393</td></tr>
<tr/><td style="text-align: center;"> 42</td><td>Sean Payton</td><td>6</td><td></td><td>4</td><td>2</td><td>0.667</td><td>0.631</td><td>0.392</td></tr>
<tr/><td style="text-align: center;"> 43</td><td>Dave Wannstedt</td><td>5</td><td></td><td>2</td><td>3</td><td>0.400</td><td>0.378</td><td>0.376</td></tr>
<tr/><td style="text-align: center;"> 44</td><td>Ted Marchibroda</td><td>6</td><td></td><td>2</td><td>4</td><td>0.333</td><td>0.327</td><td>0.364</td></tr>
<tr/><td style="text-align: center;"> 45</td><td>Pete Carroll</td><td>5</td><td></td><td>2</td><td>3</td><td>0.400</td><td>0.393</td><td>0.349</td></tr>
<tr/><td style="text-align: center;"> 46</td><td>Art Shell</td><td>5</td><td></td><td>2</td><td>3</td><td>0.400</td><td>0.427</td><td>0.292</td></tr>
<tr/><td style="text-align: center;"> 47</td><td>Herm Edwards</td><td>6</td><td></td><td>2</td><td>4</td><td>0.333</td><td>0.375</td><td>0.274</td></tr>
<tr/><td style="text-align: center;"> 48</td><td>Dick Nolan</td><td>5</td><td></td><td>2</td><td>3</td><td>0.400</td><td>0.458</td><td>0.244</td></tr>
<tr/><td style="text-align: center;"> 49</td><td>Bud Grant</td><td>22</td><td></td><td>10</td><td>12</td><td>0.455</td><td>0.514</td><td>0.220</td></tr>
<tr/><td style="text-align: center;"> 50</td><td>Steve Mariucci</td><td>7</td><td></td><td>3</td><td>4</td><td>0.429</td><td>0.513</td><td>0.206</td></tr>
<tr/><td style="text-align: center;"> </td><td> </td><td> </td><td></td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>
<tr/><td style="text-align: center;"> 51</td><td>Mike Ditka</td><td>12</td><td></td><td>6</td><td>6</td><td>0.500</td><td>0.586</td><td>0.184</td></tr>
<tr/><td style="text-align: center;"> 52</td><td>Bobby Ross</td><td>8</td><td></td><td>3</td><td>5</td><td>0.375</td><td>0.474</td><td>0.181</td></tr>
<tr/><td style="text-align: center;"> 53</td><td>Jim Fassel</td><td>5</td><td></td><td>2</td><td>3</td><td>0.400</td><td>0.506</td><td>0.180</td></tr>
<tr/><td style="text-align: center;"> 54</td><td>Chuck Knox</td><td>18</td><td></td><td>7</td><td>11</td><td>0.389</td><td>0.474</td><td>0.169</td></tr>
<tr/><td style="text-align: center;"> 55</td><td>Don Shula</td><td>36</td><td></td><td>19</td><td>17</td><td>0.528</td><td>0.595</td><td>0.161</td></tr>
<tr/><td style="text-align: center;"> 56</td><td>Red Miller</td><td>5</td><td></td><td>2</td><td>3</td><td>0.400</td><td>0.532</td><td>0.150</td></tr>
<tr/><td style="text-align: center;"> 57</td><td>Lovie Smith</td><td>6</td><td></td><td>3</td><td>3</td><td>0.500</td><td>0.631</td><td>0.139</td></tr>
<tr/><td style="text-align: center;"> 58</td><td>Mike Martz</td><td>7</td><td></td><td>3</td><td>4</td><td>0.429</td><td>0.587</td><td>0.109</td></tr>
<tr/><td style="text-align: center;"> 59</td><td>Don Coryell</td><td>9</td><td></td><td>3</td><td>6</td><td>0.333</td><td>0.485</td><td>0.106</td></tr>
<tr/><td style="text-align: center;"> 60</td><td>Dick Vermeil</td><td>11</td><td></td><td>6</td><td>5</td><td>0.545</td><td>0.689</td><td>0.091</td></tr>
<tr/><td style="text-align: center;"> </td><td> </td><td> </td><td></td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>
<tr/><td style="text-align: center;"> 61</td><td>Mike Sherman</td><td>6</td><td></td><td>2</td><td>4</td><td>0.250</td><td>0.531</td><td>0.083</td></tr>
<tr/><td style="text-align: center;"> 62</td><td>Wayne Fontes</td><td>5</td><td></td><td>1</td><td>4</td><td>0.200</td><td>0.409</td><td>0.072</td></tr>
<tr/><td style="text-align: center;"> 63</td><td>Dennis Green</td><td>12</td><td></td><td>4</td><td>8</td><td>0.333</td><td>0.519</td><td>0.056</td></tr>
<tr/><td style="text-align: center;"> 64</td><td>George Allen</td><td>9</td><td></td><td>2</td><td>7</td><td>0.222</td><td>0.432</td><td>0.048</td></tr>
<tr/><td style="text-align: center;"> 65</td><td>Paul Brown</td><td>12</td><td></td><td>4</td><td>8</td><td>0.333</td><td>0.541</td><td>0.041</td></tr>
<tr/><td style="text-align: center;"> 66</td><td>Sid Gillman</td><td>6</td><td></td><td>1</td><td>5</td><td>0.167</td><td>0.420</td><td>0.038</td></tr>
<tr/><td style="text-align: center;"> 67</td><td>Jack Pardee</td><td>6</td><td></td><td>1</td><td>5</td><td>0.167</td><td>0.552</td><td>0.008</td></tr>
<tr/><td style="text-align: center;"> 68</td><td>Wade Phillips</td><td>6</td><td></td><td>1</td><td>5</td><td>0.167</td><td>0.560</td><td>0.007</td></tr>
<tr/><td style="text-align: center;"> 69</td><td>Marty Schottenheimer</td><td>18</td><td></td><td>5</td><td>13</td><td>0.278</td><td>0.534</td><td>0.007</td></tr>
<tr/><td style="text-align: center;"> 70</td><td>Jim Mora, Sr.</td><td>6</td><td></td><td>0</td><td>6</td><td>0.000</td><td>0.597</td><td>0.000</td></tr>
</tbody></table></div>Unknownnoreply@blogger.com6tag:blogger.com,1999:blog-5204092591876211047.post-63227486740693174642012-01-12T13:32:00.000-05:002012-01-22T16:09:22.682-05:00Betting Market Power Rankings – Divisional Round Editionby Michael Beuoy<br />
<style type="text/css">
#version2
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
td
{
white-space: nowrap;
}
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0;
white-space: nowrap;
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><p><br />
In <a href="http://community.advancednflstats.com/2012/01/betting-market-power-rankings.html">last week’s</a> post, I showed how one can use the betting over/under in conjunction with the point spread to decompose team strength into an offensive and defensive Generic Points Favored (GPF = oGPF + dGPF). The post was essentially a redo of the Week 16 rankings, and unfortunately, I did not have enough time to apply the new method to the Wildcard Round of the playoffs. This week, I do have time, so here is a peek into the mind of the Betting Market for the Divisional Round of the Playoffs. In addition, I’ve laid out a table of the predicted lines and over/unders for each possible matchup in the Conference Finals and Superbowl. I’ll return to the predictions in the following weeks to see how the model did (testable predictions! science!).</p><p>For those of you that are interested, I’ve decided to start a <a href=" http://bettingmarketanalytics.blogspot.com/">blog</a> for the purposes of publishing these rankings for various sports. I’ll start off with the NBA (see the first set of rankings <a href="http://bettingmarketanalytics.blogspot.com/2012/01/nba-team-rankings-january-11-2012.html">here</a>). After that, I’ll take a crack at NCAA Basketball, and then hopefully move on to Major League Baseball (which presents some interesting opportunities for decomposing team strength into offense, defense, and pitching, and creating a separate set of starting pitcher rankings). The blog will probably be pretty rough in the early going (i.e. ugly and confusing), but I hope to learn quickly.<a name='more'></a></p><p><i>Anyway</i>, here are the Betting Market Power Rankings for the Divisional Round of the playoffs. I had to play things by ear with regard to weighting each week, given that each new playoff week only adds a handful of games, rather than the full 16 games. So rather than dropping the oldest week and adding the newest like I do during the regular season, I’m going to keep the old weeks frozen, and just add in the new weeks at progressively higher weights. Here are the weights I am using:</p><p>Week 13 – 1<br />
Week 14 – 2<br />
Week 15 – 3<br />
Week 16 – 4<br />
Week 17 – 0 <- final week, too many garbage games
Week 18 – 6 <- Wildcard Round
Week 19 – 7 <- Divisional Round
Week 20 - 8 <- Conference Finals</p><br />
<br />
<br />
<br />
<p>Here is a glossary of terms (I had to drop the comparisons to the ANS model since the rankings aren’t updated during the playoffs):</p><p><b>LSTWK</b> - The betting market rank as of the prior week (what I would have published for the Wildcard round if I had had the time)<br />
<b>GPF</b> - Stands for Generic Points Favored. It’s what you would expect a team to be favored by against a league average opponent at a neutral site.<br />
<b>oGPF</b> – Offensive Generic Points Favored. The component of a team’s total GPF attributable to its ability to score points.<br />
<b>dGPF</b> – Defensive Generic Points Favored. The component of a team’s total GPF attributable to its ability to prevent the other team from scoring points<br />
<b>O RANK</b> – The team’s oGPF ranking.<br />
<b>D RANK</b> – The team’s dGPF ranking.<br />
<b>GWP</b> - Stands for Generic Win Probability. I converted the GPF into a generic win probability using the following formula: GWP = 1/(1+exp(-GPF/7)).<br />
<br />
And here is the ranking table (the Rank column is relative to all 32 teams, but I’m only showing the 12 playoff teams):</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"; white-space: nowrap;></col></colgroup><thead>
<tr><th>Rank</th><th>Team</th><th>LSTWK</th><th>GPF</th><th>oGPF</th><th>dGPF</th><th>GWP</th><th>ORank</th><th>DRank</th></tr>
</thead><tbody> <tr/><td style="text-align: center;"> 1</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO</td><td>1</td><td>10.0</td><td>10.0</td><td>0.0</td><td>0.81</td><td>1</td><td>15</td></tr>
<tr/><td style="text-align: center;"> 2</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/> GB</td><td>2</td><td>8.5</td><td>7.5</td><td>1.0</td><td>0.78</td><td>3</td><td>10</td></tr>
<tr/><td style="text-align: center;"> 3</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td>3</td><td>8.0</td><td>8.0</td><td>0.0</td><td>0.76</td><td>2</td><td>19</td></tr>
<tr/><td style="text-align: center;"> 5</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/> SF</td><td>4</td><td>4.5</td><td>0.0</td><td>4.5</td><td>0.65</td><td>15</td><td>1</td></tr>
<tr/><td style="text-align: center;"> 6</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PIT/PIT_logo-20x20.gif"/> PIT</td><td>6</td><td>4.5</td><td>0.0</td><td>4.5</td><td>0.65</td><td>14</td><td>2</td></tr>
<tr/><td style="text-align: center;"> 7</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td>7</td><td>4.0</td><td>0.5</td><td>3.5</td><td>0.64</td><td>12</td><td>3</td></tr>
<tr/><td style="text-align: center;"> 8</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td>9</td><td>3.5</td><td>3.0</td><td>0.5</td><td>0.62</td><td>6</td><td>13</td></tr>
<tr/><td style="text-align: center;"> 9</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DET/DET_logo-20x20.gif"/> DET</td><td>10</td><td>3.0</td><td>4.0</td><td>-1.0</td><td>0.60</td><td>4</td><td>24</td></tr>
<tr/><td style="text-align: center;"> 11</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ATL/ATL_logo-20x20.gif"/> ATL</td><td>8</td><td>2.5</td><td>0.5</td><td>2.0</td><td>0.60</td><td>11</td><td>7</td></tr>
<tr/><td style="text-align: center;"> 16</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td>16</td><td>0.0</td><td>-2.5</td><td>2.5</td><td>0.50</td><td>24</td><td>4</td></tr>
<tr/><td style="text-align: center;"> 19</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CIN/CIN_logo-20x20.gif"/> CIN</td><td>17</td><td>-1.0</td><td>-1.0</td><td>0.0</td><td>0.46</td><td>21</td><td>18</td></tr>
<tr/><td style="text-align: center;"> 24</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td>26</td><td>-3.0</td><td>-2.5</td><td>-0.5</td><td>0.39</td><td>25</td><td>22</td></tr>
</tbody></table></div><p>• New Orleans has taken over the top spot, bypassing both Green Bay and New England.<br />
• According to the betting market the 8 team playoff field breaks down as follows:<br />
o 3 “elite” teams – New Orleans, New England, and Green Bay, all offensive powerhouses according to oGPF.<br />
o 3 “good” teams – San Francisco, Baltimore, and New York (two defensive powerhouses and one good offense – which should tell you something about the relative importance of offenses and defenses)<br />
o 1 “mediocre” team – Houston (with offsetting oGPF and dGPF)<br />
o 1 “bad” team – Denver (negative on both oGPF and dGPF)</p><p>Here is how the model predicted the point spreads for each Divisional Round matchup. Thanks to the addition of oGPF and dGPF, I can also generate a prediction of the over/unders as well. “PRED LINE”, “ACT LINE”, and “LINE DIFF” show the line the model predicted, the actual line, and the difference. The next three columns do the same for the over/under.</p><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead>
<tr><th>Game</th><th>Pred Line</th><th>Act Line</th><th>Line Diff</th><th>Pred OU</th><th>Act OU</th><th>OU Diff</th></tr>
</thead><tbody> <tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN @ NE <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/></td><td>13.5</td><td>13.5</td><td>0.0</td><td>49</td><td>51</td><td>2.0</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO @ SF <img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/></td><td>-2.0</td><td>-3.5</td><td>-1.5</td><td>50.5</td><td>47.5</td><td>-3.0</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG @ GB <img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/></td><td>7.5</td><td>8.5</td><td>1.0</td><td>53.5</td><td>52</td><td>-1.5</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> Tex @ Bal <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/></td><td>5.5</td><td>7.5</td><td>2.0</td><td>37.5</td><td>36</td><td>-1.5</td></tr>
</tbody></table></div><p>The model actually did a pretty good job (in my opinion) at predicting this week, which is unfortunate in a way. Assuming my model is a reasonable baseline for how the betting market normally reacts, a big miss is a reliable indicator that something unusual has happened, like a key injury, or a particularly illuminating on-field performance (there was a severe market correction prior to the Wild Card round in regards to Denver – the point spread was 4 additional points in favor of Pittsburgh than the baseline prediction, and it all came out of Denver’s point total – after that 7-3 final against KC, nobody was putting much confidence in Tebow’s ability to score points).<br />
<br />
Here’s another view of the table above, but this time broken down by predicted score for each team (it’s a useful way to understand what’s driving a miss in the line prediction).</p><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol" ></col></colgroup><thead>
<tr><th>Game</th><th>Away Pred</th><th>Away Act</th><th>Away Diff</th><th>Home Pred</th><th>Home Act</th><th>Home Diff</th></tr>
</thead><tbody> <tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN @ NE <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/></td><td>17.75</td><td>18.75</td><td>1.0</td><td>31.25</td><td>32.25</td><td>1.0</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO @ SF <img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/></td><td>26.25</td><td>25.5</td><td>-0.75</td><td>24.25</td><td>22</td><td>-2.3</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG @ GB <img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/></td><td>23.0</td><td>21.75</td><td>-1.25</td><td>30.5</td><td>30.25</td><td>-0.3</td></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> Tex @ Bal <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/></td><td>16.0</td><td>14.25</td><td>-1.75</td><td>21.5</td><td>21.75</td><td>0.3</td></tr>
</tbody></table></div><p>What surprised me most is the source of the miss on the NO @ SF line. New Orleans is favored by 1.5 points more than the model indicates. But the source of the miss is that SF is assumed to score <i>fewer</i> points, not that New Orleans is expected to score more.<br />
<br />
<b>Conference Finals and Superbowl Predictions</b><br />
<br />
Here are predicted lines and over/unders for each possible Conference Finals matchup and Superbowl matchup (I’ll check back on these to see how I did).<br />
<br />
<b>Conference Finals:</b></p><br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col><col class="colorcol"></col></colgroup><thead>
<tr><th>Away</th><th>Home</th><th>Line</th><th>Over/Under</th></tr>
</thead><tbody> <tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"0.00.0/> NE</td><td>6.5</td><td>49<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"0.00.0/> NE</td><td>10.5</td><td>47<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"0.00.0/> TEX</td><td>5.5</td><td>37<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"0.00.0/> BAL</td><td>9.5</td><td>39<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/> SF</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"0.00.0/> GB</td><td>6.5</td><td>46<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"0.00.0/> GB</td><td>1</td><td>60.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"0.00.0/> NO</td><td>9</td><td>56.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"0.00.0/> SF</td><td>3.5</td><td>42<br />
</tbody></table></div><br />
<b>Superbowl</b> (positive line indicates NFC team is favored):<br />
<br />
<div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col><col class="colorcol"></col></colgroup><thead>
<tr><th>Away</th><th>Home</th><th>Line</th><th>Over/Under</th></tr>
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"0.00.0/> GB</td><td>0.5</td><td>58.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"0.00.0/> SF</td><td>-3.5</td><td>47.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"0.00.0/> NO</td><td>2</td><td>62<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"0.00.0/> NYG</td><td>-4.5</td><td>54.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"0.00.0/> GB</td><td>4.5</td><td>47.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"0.00.0/> SF</td><td>0.5</td><td>36.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"0.00.0/> NO</td><td>6</td><td>51<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"0.00.0/> NYG</td><td>-0.5</td><td>43.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"0.00.0/> GB</td><td>8.5</td><td>45.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"0.00.0/> SF</td><td>4.5</td><td>34.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"0.00.0/> NO</td><td>10</td><td>49<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"0.00.0/> NYG</td><td>3.5</td><td>41.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"0.00.0/> GB</td><td>11.5</td><td>48.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"0.00.0/> SF</td><td>7.5</td><td>37.5<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"0.00.0/> NO</td><td>13</td><td>52<br />
<tr/><td style="text-align: center;"> <img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"0.00.0/> NYG</td><td>6.5</td><td>44.5<br />
</tbody></table></div><p>And finally, here is a brief tutorial on how to create point spreads and over/unders for any hypothetical matchup, using GPF, oGPF, and dGPF from the rankings:<br />
<br />
<b>How to Build a Point Spread:</b><br />
<br />
Point Spread (in favor of home team) = 2.5 + GPF<sub>home</sub> - GPF<sub>away</sub><br />
<br />
<b>How to Build a Over/Under</b><br />
<br />
Over/Under = 2*22.0 + oGPF<sub>home</sub> + oGPF<sub>away</sub> - dGPF<sub>home</sub> - dGPF<sub>away</sub><br />
<br />
The 22.0 represents league average scoring and is determined dynamically each week with the ratings (but it tends to stay pretty consistent at 22).<br />
<br />
How to Build Predicted Scores<br />
<br />
Home Team Score = (22.0 + 1.25) + oGPF<sub>home</sub> - dGPF<sub>away</sub><br />
Away Team Score = (22.0 - 1.25) + oGPF<sub>away</sub> - dGPF<sub>home</sub></p>Unknownnoreply@blogger.com7tag:blogger.com,1999:blog-5204092591876211047.post-61790148247787512022012-01-06T20:15:00.013-05:002012-01-11T19:25:53.276-05:00NFL Coach Quality: A Bayesian Approach To Approximating the Value of Coaches - UPDATED<a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhtBhE0vk4nOnrm641JjoFLxN0IbbqKB3JhgXyK8-DAfy7A6r8gq3t75sfEO6NmJHQs9KcBRppxMzMK_czg8S5YGJ5vXIjvUT1BerU8prZBREEULjSVRb_b9EiKa1by58gHwIOqdD8hGCb-/s1600/coaches.jpg"><img style="float:left; margin:0 10px 10px 0;cursor:pointer; cursor:hand;width: 234px; height: 216px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhtBhE0vk4nOnrm641JjoFLxN0IbbqKB3JhgXyK8-DAfy7A6r8gq3t75sfEO6NmJHQs9KcBRppxMzMK_czg8S5YGJ5vXIjvUT1BerU8prZBREEULjSVRb_b9EiKa1by58gHwIOqdD8hGCb-/s320/coaches.jpg" border="0" alt=""id="BLOGGER_PHOTO_ID_5694705491037038594" /></a><p>by David Durschlag</p><style type="text/css">
#version2
{
display: none;
}
h4
{
margin-top: 1em;
margin-bottom: 0px;
}
ul
{
margin-top: 0px;
margin-bottom: 1em;
}
p
{
margin-top: 0px;
margin-bottom: 1em;
}
table
{
width:450px;
margin-left: auto;
margin-right: auto;
margin-bottom: 1em;
}
.tableHolder
{
text-align: center;
}
table,
table tr,
table tr td,
table tr th
{
border-collapse: collapse;
border-width: 1px;
border-style: solid;
border-color: black;
}
th
{
padding: 3px;
background-color: #aad5ff;
}
td
{
text-align: center;
padding: 3px;
}
#logocell
{
padding: 0px 3px 0px 3px;
}
.colorcol
{
background-color:#ffffe0
}
tr.myClass:hover
{
background-color: #e1ecff;
}
#logo
{
border:0; vertical-align:middle
}
th:hover
{
text-decoration: underline; cursor: pointer; cursor: hand
}
</style><script>
var v1Div = null
var v2Div = null;
var numHolder = null;
var version = 1;
function PrepVersion()
{
v1Div = document.getElementById("version1");
v2Div = document.getElementById("version2");
numHolder = document.getElementById("vNumHolder");
}
setTimeout( PrepVersion, 1 );
function SwitchVersions()
{
if ( version == 1 )
{
version = 2;
v1Div.style.display = "none";
v2Div.style.display = "block";
numHolder.innerHTML = "2";
} else {
version = 1;
v2Div.style.display = "none";
v1Div.style.display = "block";
numHolder.innerHTML = "1";
}
}
</script><p>You are currently viewing version <span id="vNumHolder">1</span> of this article. To view version two, please <a href="javascript:SwitchVersions()">click here</a>.</p><div id="version1"><h4>Summary</h4><p>Evaluating NFL coaches is a difficult task, popular among fans and vitally important to franchises. This is a brief attempt at the task, using purely quantitative data.</p><h4>Data</h4><p>The numbers of regular season games each team won each year are treated as data points. No information beyond number of regular season wins was used.</p><p>While the "metagame" of the NFL continues to evolve, the data used herein is from 1993 onward, when the last Collective Bargaining Agreement was signed. While victories now come in different environments, they are all under (roughly) the same rules. Data from before this period could be skewed based on the different rules for control of players, so it was excluded.</p><p>Also excluded was the performance of any team in a year in which it had multiple head coaches. This was done to ensure that credit for a season was easy to assign.</p><a name='more'></a><p>In total, 107 coaches and 565 team-years of data were used.</p><h4>Assumptions</h4><ul><li>Each coach has a hidden "value". Better coaches have higher value.</li><li>The number of games a team wins can be modeled as a draw from a normal distribution with a mean of the value of their coach, and an unknown variance dubbed "Season Variance". This variance is constant across all seasons for all coaches.</li><li>The value of coaches is normally distributed across the population, with unknown mean and variance.</li></ul><h4>Process</h4><p>The above assumptions were encoded as a model for BUGS, which was run for 10,000 iterations, then another 10,000 iterations.</p><h4>Results</h4><p>Coach quality had converged after 10,000 iterations.</p><p>The posterior distribution for system constants were as follows:</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead><tr><th>Constant</th><th>Mean</th><th>Standard Deviation</th></tr></thead><tbody><tr><td> Season Variance</td><td>0.137</td><td>0.009</td></tr><tr><td> Coach Value Population Mean</td><td>7.698</td><td>0.191</td></tr><tr><td> Coach Value Population Variance</td><td>0.626</td><td>0.207</td></tr></tbody></table></div><p>The posterior distributions for coach values were as follows:</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead><tr><th>Coach</th><th>Mean Value</th><th>Standard Deviation Value</th></tr></thead><tbody><tr><td> Bill Belichick</td><td>10.100</td><td>0.633</td></tr><tr><td> Tony Dungy</td><td>9.948</td><td>0.671</td></tr><tr><td> Mike Tomlin</td><td>9.490</td><td>0.920</td></tr><tr><td> Bill Cowher</td><td>9.350</td><td>0.636</td></tr><tr><td> Mike McCarthy</td><td>9.344</td><td>0.865</td></tr><tr><td> John Harbaugh</td><td>9.303</td><td>0.972</td></tr><tr><td> Sean Payton</td><td>9.245</td><td>0.852</td></tr><tr><td> Marty Schottenheimer</td><td>9.209</td><td>0.686</td></tr><tr><td> Mike Smith</td><td>9.197</td><td>0.970</td></tr><tr><td> Andy Reid</td><td>9.180</td><td>0.656</td></tr><tr><td> Mike Holmgren</td><td>9.107</td><td>0.606</td></tr><tr><td> Wade Phillips</td><td>9.051</td><td>0.792</td></tr><tr><td> Mike Shanahan</td><td>8.970</td><td>0.606</td></tr><tr><td> Barry Switzer</td><td>8.833</td><td>0.957</td></tr><tr><td> Mike Martz</td><td>8.763</td><td>0.863</td></tr><tr><td> Jimmy Johnson</td><td>8.751</td><td>0.892</td></tr><tr><td> Mike Sherman</td><td>8.746</td><td>0.856</td></tr><tr><td> Tom Coughlin</td><td>8.626</td><td>0.608</td></tr><tr><td> Jeff Fisher</td><td>8.578</td><td>0.604</td></tr><tr><td> Jack Pardee</td><td>8.549</td><td>1.221</td></tr><tr><td> Dennis Green</td><td>8.507</td><td>0.684</td></tr><tr><td> Brian Billick</td><td>8.505</td><td>0.738</td></tr><tr><td> Lovie Smith</td><td>8.466</td><td>0.777</td></tr><tr><td> George Seifert</td><td>8.412</td><td>0.812</td></tr><tr><td> Marv Levy</td><td>8.397</td><td>0.905</td></tr><tr><td> Rex Ryan</td><td>8.380</td><td>1.020</td></tr><tr><td> Don Shula</td><td>8.375</td><td>1.017</td></tr><tr><td> Bill Parcells</td><td>8.372</td><td>0.694</td></tr><tr><td> Jon Gruden</td><td>8.370</td><td>0.692</td></tr><tr><td> Steve Mariucci</td><td>8.216</td><td>0.778</td></tr><tr><td> Bobby Ross</td><td>8.148</td><td>0.772</td></tr><tr><td> Jim Caldwell</td><td>8.105</td><td>1.009</td></tr><tr><td> Wayne Fontes</td><td>8.094</td><td>0.945</td></tr><tr><td> Jim Fassel</td><td>8.077</td><td>0.805</td></tr><tr><td> Brad Childress</td><td>8.066</td><td>0.908</td></tr><tr><td> Dick Vermeil</td><td>8.058</td><td>0.778</td></tr><tr><td> John Fox</td><td>7.978</td><td>0.743</td></tr><tr><td> Pete Carroll</td><td>7.967</td><td>0.935</td></tr><tr><td> Al Groh</td><td>7.954</td><td>1.210</td></tr><tr><td> Ken Whisenhunt</td><td>7.876</td><td>0.897</td></tr><tr><td> Mike Tice</td><td>7.845</td><td>0.944</td></tr><tr><td> Jim Mora</td><td>7.833</td><td>0.956</td></tr><tr><td> Gunther Cunningham</td><td>7.801</td><td>1.104</td></tr><tr><td> Gary Kubiak</td><td>7.768</td><td>0.849</td></tr><tr><td> Jason Garrett</td><td>7.766</td><td>1.203</td></tr><tr><td> Jack Del Rio</td><td>7.759</td><td>0.746</td></tr><tr><td> Hue Jackson</td><td>7.745</td><td>1.201</td></tr><tr><td> Tony Sparano</td><td>7.734</td><td>0.943</td></tr><tr><td> Jim L. Mora</td><td>7.731</td><td>0.960</td></tr><tr><td> Dave Wannstedt</td><td>7.722</td><td>0.698</td></tr><tr><td> Dan Reeves</td><td>7.705</td><td>0.707</td></tr><tr><td> Norv Turner</td><td>7.704</td><td>0.634</td></tr><tr><td> Marvin Lewis</td><td>7.695</td><td>0.748</td></tr><tr><td> Nick Saban</td><td>7.631</td><td>1.094</td></tr><tr><td> Bill Callahan</td><td>7.629</td><td>1.099</td></tr><tr><td> Joe Gibbs</td><td>7.616</td><td>0.946</td></tr><tr><td> Mike White</td><td>7.607</td><td>1.102</td></tr><tr><td> Jim Haslett</td><td>7.584</td><td>0.855</td></tr><tr><td> Ray Rhodes</td><td>7.546</td><td>0.887</td></tr><tr><td> Mike Singletary</td><td>7.479</td><td>1.092</td></tr><tr><td> Mike Mularkey</td><td>7.467</td><td>1.103</td></tr><tr><td> Art Shell</td><td>7.423</td><td>1.016</td></tr><tr><td> Todd Haley</td><td>7.403</td><td>1.022</td></tr><tr><td> Jerry Glanville</td><td>7.373</td><td>1.210</td></tr><tr><td> Chan Gailey</td><td>7.358</td><td>0.968</td></tr><tr><td> Tom Cable</td><td>7.311</td><td>1.119</td></tr><tr><td> Rich Brooks</td><td>7.307</td><td>1.100</td></tr><tr><td> Josh McDaniels</td><td>7.155</td><td>1.102</td></tr><tr><td> Dick Jauron</td><td>7.151</td><td>0.752</td></tr><tr><td> Tom Flores</td><td>7.143</td><td>1.092</td></tr><tr><td> Buddy Ryan</td><td>7.142</td><td>1.096</td></tr><tr><td> Steve Spurrier</td><td>7.141</td><td>1.099</td></tr><tr><td> Lindy Infante</td><td>7.139</td><td>1.119</td></tr><tr><td> Jim Zorn</td><td>7.135</td><td>1.094</td></tr><tr><td> Eric Mangini</td><td>7.124</td><td>0.906</td></tr><tr><td> Vince Tobin</td><td>7.107</td><td>0.957</td></tr><tr><td> June Jones</td><td>7.104</td><td>1.022</td></tr><tr><td> Dennis Erickson</td><td>7.098</td><td>0.864</td></tr><tr><td> Herman Edwards</td><td>7.090</td><td>0.787</td></tr><tr><td> Butch Davis</td><td>7.002</td><td>0.947</td></tr><tr><td> Sam Wyche</td><td>6.997</td><td>1.030</td></tr><tr><td> Scott Linehan</td><td>6.983</td><td>1.104</td></tr><tr><td> Kevin Gilbride</td><td>6.977</td><td>1.232</td></tr><tr><td> Jim E. Mora</td><td>6.975</td><td>0.958</td></tr><tr><td> Richie Petitbon</td><td>6.975</td><td>1.231</td></tr><tr><td> Joe Bugel</td><td>6.967</td><td>1.113</td></tr><tr><td> Lane Kiffin</td><td>6.962</td><td>1.231</td></tr><tr><td> Romeo Crennel</td><td>6.870</td><td>0.957</td></tr><tr><td> Gregg Williams</td><td>6.867</td><td>1.033</td></tr><tr><td> Raheem Morris</td><td>6.864</td><td>1.035</td></tr><tr><td> Ted Marchibroda</td><td>6.793</td><td>0.861</td></tr><tr><td> Mike Nolan</td><td>6.722</td><td>1.025</td></tr><tr><td> Dave McGinnis</td><td>6.717</td><td>1.030</td></tr><tr><td> Chuck Knox</td><td>6.654</td><td>1.123</td></tr><tr><td> Bruce Coslet</td><td>6.617</td><td>0.972</td></tr><tr><td> Dom Capers</td><td>6.597</td><td>0.789</td></tr><tr><td> Mike Ditka</td><td>6.573</td><td>1.050</td></tr><tr><td> Dave Campo</td><td>6.569</td><td>1.032</td></tr><tr><td> Dick LeBeau</td><td>6.496</td><td>1.124</td></tr><tr><td> Mike Riley</td><td>6.443</td><td>1.052</td></tr><tr><td> Cam Cameron</td><td>6.366</td><td>1.263</td></tr><tr><td> Dave Shula</td><td>6.311</td><td>1.041</td></tr><tr><td> Rich Kotite</td><td>6.263</td><td>0.995</td></tr><tr><td> Chris Palmer</td><td>6.011</td><td>1.162</td></tr><tr><td> Marty Mornhinweg</td><td>6.009</td><td>1.164</td></tr><tr><td> Steve Spagnuolo</td><td>5.877</td><td>1.072</td></tr><tr><td> Rod Marinelli</td><td>5.864</td><td>1.071</td></tr></tbody></table></div><h4>Conclusions and Analysis</h4><p>Despite having a small sample size and extremely limited data, the estimated value of coaches agrees closely with conventional wisdom. Value estimates are relatively narrow, ranging from a 66% chance that Jeff Fisher's value is between 7.974 and 9.182 to a 66% chance Cam Cameron's value is between 5.103 and 7.629. Applying Microsoft's ? - 3 * ? method of combining the parameters of a normal distribution for TrueSkill, then renormalizing (so that the unit of value is approximately the win), the following list is obtained:</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead><tr><th>Coach</th><th>Normalized Combined Rating</th></tr></thead><tbody><tr><td> Bill Belichick</td><td>10.060</td></tr><tr><td> Tony Dungy</td><td>9.870</td></tr><tr><td> Bill Cowher</td><td>9.520</td></tr><tr><td> Mike Holmgren</td><td>9.410</td></tr><tr><td> Andy Reid</td><td>9.360</td></tr><tr><td> Mike Shanahan</td><td>9.310</td></tr><tr><td> Marty Schottenheimer</td><td>9.310</td></tr><tr><td> Tom Coughlin</td><td>9.070</td></tr><tr><td> Jeff Fisher</td><td>9.040</td></tr><tr><td> Mike McCarthy</td><td>9.030</td></tr><tr><td> Mike Tomlin</td><td>9.010</td></tr><tr><td> Sean Payton</td><td>8.980</td></tr><tr><td> Wade Phillips</td><td>8.970</td></tr><tr><td> Dennis Green</td><td>8.820</td></tr><tr><td> John Harbaugh</td><td>8.770</td></tr><tr><td> Jon Gruden</td><td>8.700</td></tr><tr><td> Bill Parcells</td><td>8.700</td></tr><tr><td> Brian Billick</td><td>8.700</td></tr><tr><td> Mike Smith</td><td>8.700</td></tr><tr><td> Mike Sherman</td><td>8.620</td></tr><tr><td> Mike Martz</td><td>8.620</td></tr><tr><td> Lovie Smith</td><td>8.590</td></tr><tr><td> Jimmy Johnson</td><td>8.550</td></tr><tr><td> George Seifert</td><td>8.480</td></tr><tr><td> Barry Switzer</td><td>8.470</td></tr><tr><td> Steve Mariucci</td><td>8.410</td></tr><tr><td> Bobby Ross</td><td>8.380</td></tr><tr><td> Norv Turner</td><td>8.350</td></tr><tr><td> John Fox</td><td>8.320</td></tr><tr><td> Dick Vermeil</td><td>8.300</td></tr><tr><td> Marv Levy</td><td>8.270</td></tr><tr><td> Jim Fassel</td><td>8.260</td></tr><tr><td> Dave Wannstedt</td><td>8.230</td></tr><tr><td> Dan Reeves</td><td>8.200</td></tr><tr><td> Jack Del Rio</td><td>8.150</td></tr><tr><td> Marvin Lewis</td><td>8.110</td></tr><tr><td> Brad Childress</td><td>8.030</td></tr><tr><td> Don Shula</td><td>8.010</td></tr><tr><td> Rex Ryan</td><td>8.010</td></tr><tr><td> Wayne Fontes</td><td>7.970</td></tr><tr><td> Gary Kubiak</td><td>7.940</td></tr><tr><td> Ken Whisenhunt</td><td>7.920</td></tr><tr><td> Pete Carroll</td><td>7.900</td></tr><tr><td> Jim Caldwell</td><td>7.840</td></tr><tr><td> Jim Haslett</td><td>7.800</td></tr><tr><td> Mike Tice</td><td>7.790</td></tr><tr><td> Jim Mora</td><td>7.760</td></tr><tr><td> Tony Sparano</td><td>7.720</td></tr><tr><td> Dick Jauron</td><td>7.710</td></tr><tr><td> Ray Rhodes</td><td>7.700</td></tr><tr><td> Jack Pardee</td><td>7.700</td></tr><tr><td> Jim L. Mora</td><td>7.680</td></tr><tr><td> Joe Gibbs</td><td>7.630</td></tr><tr><td> Herman Edwards</td><td>7.590</td></tr><tr><td> Dennis Erickson</td><td>7.430</td></tr><tr><td> Gunther Cunningham</td><td>7.420</td></tr><tr><td> Chan Gailey</td><td>7.390</td></tr><tr><td> Eric Mangini</td><td>7.360</td></tr><tr><td> Art Shell</td><td>7.340</td></tr><tr><td> Nick Saban</td><td>7.320</td></tr><tr><td> Todd Haley</td><td>7.310</td></tr><tr><td> Bill Callahan</td><td>7.310</td></tr><tr><td> Al Groh</td><td>7.300</td></tr><tr><td> Mike White</td><td>7.290</td></tr><tr><td> Vince Tobin</td><td>7.240</td></tr><tr><td> Dom Capers</td><td>7.240</td></tr><tr><td> Ted Marchibroda</td><td>7.220</td></tr><tr><td> Mike Singletary</td><td>7.220</td></tr><tr><td> Butch Davis</td><td>7.190</td></tr><tr><td> Mike Mularkey</td><td>7.190</td></tr><tr><td> Jason Garrett</td><td>7.180</td></tr><tr><td> Hue Jackson</td><td>7.170</td></tr><tr><td> Jim E. Mora</td><td>7.150</td></tr><tr><td> June Jones</td><td>7.100</td></tr><tr><td> Rich Brooks</td><td>7.080</td></tr><tr><td> Romeo Crennel</td><td>7.070</td></tr><tr><td> Tom Cable</td><td>7.040</td></tr><tr><td> Sam Wyche</td><td>7.010</td></tr><tr><td> Tom Flores</td><td>6.980</td></tr><tr><td> Buddy Ryan</td><td>6.970</td></tr><tr><td> Jim Zorn</td><td>6.970</td></tr><tr><td> Josh McDaniels</td><td>6.970</td></tr><tr><td> Steve Spurrier</td><td>6.960</td></tr><tr><td> Lindy Infante</td><td>6.920</td></tr><tr><td> Gregg Williams</td><td>6.910</td></tr><tr><td> Raheem Morris</td><td>6.900</td></tr><tr><td> Jerry Glanville</td><td>6.890</td></tr><tr><td> Bruce Coslet</td><td>6.860</td></tr><tr><td> Scott Linehan</td><td>6.840</td></tr><tr><td> Mike Nolan</td><td>6.820</td></tr><tr><td> Joe Bugel</td><td>6.810</td></tr><tr><td> Dave McGinnis</td><td>6.810</td></tr><tr><td> Dave Campo</td><td>6.700</td></tr><tr><td> Mike Ditka</td><td>6.660</td></tr><tr><td> Mike Riley</td><td>6.570</td></tr><tr><td> Chuck Knox</td><td>6.560</td></tr><tr><td> Richie Petitbon</td><td>6.560</td></tr><tr><td> Kevin Gilbride</td><td>6.560</td></tr><tr><td> Rich Kotite</td><td>6.560</td></tr><tr><td> Lane Kiffin</td><td>6.550</td></tr><tr><td> Dave Shula</td><td>6.500</td></tr><tr><td> Dick LeBeau</td><td>6.450</td></tr><tr><td> Steve Spagnuolo</td><td>6.120</td></tr><tr><td> Rod Marinelli</td><td>6.110</td></tr><tr><td> Cam Cameron</td><td>6.060</td></tr><tr><td> Chris Palmer</td><td>6.020</td></tr><tr><td> Marty Mornhinweg</td><td>6.020</td></tr></tbody></table></div><p>The top two coaches both spent a lot of their career with transcendent quarterbacks. With the firing of Steve Spagnuolo and Raheem Morris, Romeo Crennel is the lowest ranking active head coach. If Bill Cowher says he'd like to get back into coaching, and inquires as to whether your organization is hiring, you say "yes." Using a similar model based on points for/against might not only produce slightly more accurate information, but could also reveal whether head coaches can be "defense-oriented" or "offence-oriented" and, if so, which ones are which.</p></div><div id="version2"><h4>Summary</h4><p>Evaluating NFL coaches is a difficult task, popular among fans and vitally important to franchises. This is a brief attempt at the task, using purely quantitative data. The goal here is dual -- both to increase our understanding of how (and how much) NFL teams are reflective of their coaches, as well as to introduce the dichotomy of frequentist and Bayesian analysis to the NFL statistics community, from which it is largely absent.</p><h4>Data</h4><p>The numbers of regular season games each team won each year are treated as data points. No information beyond number of regular season wins was used.</p><p>While the "metagame" of the NFL continues to evolve, the data used herein is from 1993 onward, when the last Collective Bargaining Agreement was signed. While victories now come in different environments, they are all under (roughly) the same rules. Data from before this period could be skewed based on the different rules for control of players, so it was excluded.</p><p>Also excluded was the performance of any team in a year in which it had multiple head coaches. This was done to ensure that credit for a season was easy to assign.</p><p>In total, 107 coaches and 565 team-years of data were used.</p><h4>Assumptions</h4><ul><li>Each coach has a hidden "value". Better coaches have higher value.</li><li>The number of games a team wins can be modeled as a draw from a normal distribution with a mean of the value of their coach, and an unknown standard deviation which is constant across all seasons for all coaches. This will be refered to as "Season Standard Deviation."</li><li>The value of coaches is normally distributed across the population, with unknown mean and standard deviation. These will be refered to as "Population Mean" and "Population Standard Deviation".</li></ul><h4>Process</h4><p>The above assumptions were encoded as a model for BUGS, which was run for 10,000 iterations, then another 10,000 iterations.</p><h4>Results</h4><p>Coach quality had converged after 10,000 iterations.</p><p>The posterior distribution for system constants were as follows. Posterior information for individual coaches is included in the large table in the next section.</p><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead><tr><th>Constant</th><th>Mean</th><th>Standard Deviation</th></tr></thead><tbody><tr><td>Season Standard Deviation</td><td>2.70</td><td>0.09</td></tr><tr><td>Population Mean</td><td>7.69</td><td>0.19</td></tr><tr><td>Population Standard Deviation</td><td>1.33</td><td>0.18</td></tr></tbody></table></div><h4>Conclusions and Analysis</h4><p>Below is a table with a variety of data about each coach.</p><ul><li>Value Posterior Mean: The mean of the posterior distribution for the coach's value.</li><li>Value Posterior StdDev: The standard deviation of the posterior distribution for the coach's value.</li><li>Triple-Conservative Rating: μ - 3 * σ -- a conservative single-number rating. Microsoft uses this to collapse TrueSkill distributions to single ratings.</li><li>Normalized Triple-Conservative Rating: The triple-conservative rating re-normalized to the same scale as posterior mean coach value.</li><li>Raw Average Wins: The coach's raw number of average wins over the data set. Provided for comparison to the posterior means -- this is one way to gauge the benefit of the Bayesian model over a standard frequentist approach. Because the Bayesian model incorporates the idea of uncertainty, a coach with one season of 14 wins is not considered a 14 win coach. Alternately sorting between this column and that of posterior mean, then judging which list looks better, is a reasonable shortcut for juding the modeling approach taken here.</li><li>80% Confidence Range: The range of win values the model expects with 80% confidence. In other words, this coach would be expected to win fewer games than the minimum 10% of the time, and more than the maximum 10% of the time. This can be used to gauge the amount of information added by the model -- the narrower these ranges are, the more information was available for judging that coach. The fact that these tend to be very wide indicates that the model cannot make strong predictions -- a result of both the minimal amount of data available and the unpredictability of the NFL. Taking all coaches as a data set together yields an 80% confidence range of 4.27-11.91. Comparing this to the ranges for invidual coaches is a good way to see how much information the model was able to add. In general, you'll find that the range has narrowed only very slightly, but has shifted a win or two. This can be translated roughly as "the uncertainty created by minimal data and the general difficulty in predicting the NFL means it is hard to predict how many games an individual coach's team will win, but we have a pretty good idea who the 'better' coaches are."</li></ul><div class="tableHolder"><table align="center" class="sortable" style="width: 450px;"><colgroup><col class="colorcol"></col></colgroup><thead><tr><th>Coach</th><th>Value Posterior Mean</th><th>Value Posterior StdDev</th><th>Triple-Conservative Rating</th><th>Normalized Triple-Conservative Rating</th><th>Raw Average Wins</th><th>80% Confidence Range</th></tr></thead><tbody><tr><td>Al Groh</td><td>7.95</td><td>1.21</td><td>4.32</td><td>7.30</td><td>9</td><td>4.03-11.87</td></tr><tr><td>Andy Reid</td><td>9.18</td><td>0.65</td><td>7.21</td><td>9.36</td><td>9.69</td><td>5.81-12.54</td></tr><tr><td>Art Shell</td><td>7.42</td><td>1.01</td><td>4.37</td><td>7.34</td><td>7</td><td>3.70-11.14</td></tr><tr><td>Barry Switzer</td><td>8.83</td><td>0.95</td><td>5.96</td><td>8.47</td><td>10</td><td>5.17-12.49</td></tr><tr><td>Bill Belichick</td><td>10.1</td><td>0.63</td><td>8.20</td><td>10.06</td><td>10.8</td><td>6.76-13.43</td></tr><tr><td>Bill Callahan</td><td>7.62</td><td>1.09</td><td>4.33</td><td>7.31</td><td>7.5</td><td>3.82-11.43</td></tr><tr><td>Bill Cowher</td><td>9.35</td><td>0.63</td><td>7.44</td><td>9.52</td><td>9.85</td><td>6.00-12.69</td></tr><tr><td>Bill Parcells</td><td>8.37</td><td>0.69</td><td>6.29</td><td>8.70</td><td>8.63</td><td>4.97-11.77</td></tr><tr><td>Bobby Ross</td><td>8.14</td><td>0.77</td><td>5.83</td><td>8.38</td><td>8.37</td><td>4.67-11.62</td></tr><tr><td>Brad Childress</td><td>8.06</td><td>0.90</td><td>5.34</td><td>8.03</td><td>8.4</td><td>4.45-11.67</td></tr><tr><td>Brian Billick</td><td>8.50</td><td>0.73</td><td>6.29</td><td>8.70</td><td>8.88</td><td>5.06-11.94</td></tr><tr><td>Bruce Coslet</td><td>6.61</td><td>0.97</td><td>3.70</td><td>6.86</td><td>5.5</td><td>2.93-10.29</td></tr><tr><td>Buddy Ryan</td><td>7.14</td><td>1.09</td><td>3.85</td><td>6.97</td><td>6</td><td>3.34-10.94</td></tr><tr><td>Butch Davis</td><td>7.00</td><td>0.94</td><td>4.16</td><td>7.19</td><td>6.25</td><td>3.34-10.65</td></tr><tr><td>Cam Cameron</td><td>6.36</td><td>1.26</td><td>2.57</td><td>6.06</td><td>1</td><td>2.39-10.33</td></tr><tr><td>Chan Gailey</td><td>7.35</td><td>0.96</td><td>4.45</td><td>7.39</td><td>7</td><td>3.68-11.03</td></tr><tr><td>Chris Palmer</td><td>6.01</td><td>1.16</td><td>2.52</td><td>6.02</td><td>2.5</td><td>2.14-9.87</td></tr><tr><td>Chuck Knox</td><td>6.65</td><td>1.12</td><td>3.28</td><td>6.56</td><td>4.5</td><td>2.82-10.48</td></tr><tr><td>Dan Reeves</td><td>7.70</td><td>0.70</td><td>5.58</td><td>8.20</td><td>7.7</td><td>4.29-11.11</td></tr><tr><td>Dave Campo</td><td>6.56</td><td>1.03</td><td>3.47</td><td>6.70</td><td>5</td><td>2.83-10.30</td></tr><tr><td>Dave McGinnis</td><td>6.71</td><td>1.03</td><td>3.62</td><td>6.81</td><td>5.33</td><td>2.98-10.45</td></tr><tr><td>Dave Shula</td><td>6.31</td><td>1.04</td><td>3.18</td><td>6.50</td><td>4.33</td><td>2.56-10.05</td></tr><tr><td>Dave Wannstedt</td><td>7.72</td><td>0.69</td><td>5.62</td><td>8.23</td><td>7.72</td><td>4.31-11.12</td></tr><tr><td>Dennis Erickson</td><td>7.09</td><td>0.86</td><td>4.50</td><td>7.43</td><td>6.66</td><td>3.52-10.66</td></tr><tr><td>Dennis Green</td><td>8.50</td><td>0.68</td><td>6.45</td><td>8.82</td><td>8.81</td><td>5.11-11.89</td></tr><tr><td>Dick Jauron</td><td>7.15</td><td>0.75</td><td>4.89</td><td>7.71</td><td>6.88</td><td>3.69-10.60</td></tr><tr><td>Dick LeBeau</td><td>6.49</td><td>1.12</td><td>3.12</td><td>6.45</td><td>4</td><td>2.66-10.32</td></tr><tr><td>Dick Vermeil</td><td>8.05</td><td>0.77</td><td>5.72</td><td>8.30</td><td>8.25</td><td>4.57-11.54</td></tr><tr><td>Dom Capers</td><td>6.59</td><td>0.78</td><td>4.23</td><td>7.24</td><td>6</td><td>3.10-10.09</td></tr><tr><td>Don Shula</td><td>8.37</td><td>1.01</td><td>5.32</td><td>8.01</td><td>9.33</td><td>4.65-12.09</td></tr><tr><td>Eric Mangini</td><td>7.12</td><td>0.90</td><td>4.40</td><td>7.36</td><td>6.6</td><td>3.51-10.73</td></tr><tr><td>Gary Kubiak</td><td>7.76</td><td>0.84</td><td>5.22</td><td>7.94</td><td>7.83</td><td>4.21-11.32</td></tr><tr><td>George Seifert</td><td>8.41</td><td>0.81</td><td>5.97</td><td>8.48</td><td>8.85</td><td>4.89-11.93</td></tr><tr><td>Gregg Williams</td><td>6.86</td><td>1.03</td><td>3.76</td><td>6.91</td><td>5.66</td><td>3.12-10.60</td></tr><tr><td>Gunther Cunningham</td><td>7.80</td><td>1.10</td><td>4.48</td><td>7.42</td><td>8</td><td>3.99-11.61</td></tr><tr><td>Herman Edwards</td><td>7.09</td><td>0.78</td><td>4.72</td><td>7.59</td><td>6.75</td><td>3.59-10.58</td></tr><tr><td>Hue Jackson</td><td>7.74</td><td>1.20</td><td>4.14</td><td>7.17</td><td>8</td><td>3.83-11.65</td></tr><tr><td>Jack Del Rio</td><td>7.75</td><td>0.74</td><td>5.52</td><td>8.15</td><td>7.77</td><td>4.30-11.21</td></tr><tr><td>Jack Pardee</td><td>8.54</td><td>1.22</td><td>4.88</td><td>7.70</td><td>12</td><td>4.62-12.47</td></tr><tr><td>Jason Garrett</td><td>7.76</td><td>1.20</td><td>4.15</td><td>7.18</td><td>8</td><td>3.85-11.67</td></tr><tr><td>Jeff Fisher</td><td>8.57</td><td>0.60</td><td>6.76</td><td>9.04</td><td>8.81</td><td>5.26-11.88</td></tr><tr><td>Jerry Glanville</td><td>7.37</td><td>1.21</td><td>3.74</td><td>6.89</td><td>6</td><td>3.45-11.28</td></tr><tr><td>Jim Caldwell</td><td>8.10</td><td>1.00</td><td>5.07</td><td>7.84</td><td>8.66</td><td>4.39-11.82</td></tr><tr><td>Jim E. Mora</td><td>6.97</td><td>0.95</td><td>4.10</td><td>7.15</td><td>6.25</td><td>3.31-10.63</td></tr><tr><td>Jim Fassel</td><td>8.07</td><td>0.80</td><td>5.66</td><td>8.26</td><td>8.28</td><td>4.56-11.58</td></tr><tr><td>Jim Haslett</td><td>7.58</td><td>0.85</td><td>5.01</td><td>7.80</td><td>7.5</td><td>4.02-11.14</td></tr><tr><td>Jim L. Mora</td><td>7.73</td><td>0.96</td><td>4.85</td><td>7.68</td><td>7.75</td><td>4.06-11.39</td></tr><tr><td>Jim Mora</td><td>7.83</td><td>0.95</td><td>4.96</td><td>7.76</td><td>8</td><td>4.17-11.49</td></tr><tr><td>Jim Zorn</td><td>7.13</td><td>1.09</td><td>3.85</td><td>6.97</td><td>6</td><td>3.33-10.93</td></tr><tr><td>Jimmy Johnson</td><td>8.75</td><td>0.89</td><td>6.07</td><td>8.55</td><td>9.6</td><td>5.15-12.34</td></tr><tr><td>Joe Bugel</td><td>6.96</td><td>1.11</td><td>3.62</td><td>6.81</td><td>5.5</td><td>3.14-10.78</td></tr><tr><td>Joe Gibbs</td><td>7.61</td><td>0.94</td><td>4.77</td><td>7.63</td><td>7.5</td><td>3.96-11.26</td></tr><tr><td>John Fox</td><td>7.97</td><td>0.74</td><td>5.74</td><td>8.32</td><td>8.11</td><td>4.52-11.42</td></tr><tr><td>John Harbaugh</td><td>9.30</td><td>0.97</td><td>6.38</td><td>8.77</td><td>11</td><td>5.62-12.98</td></tr><tr><td>Jon Gruden</td><td>8.37</td><td>0.69</td><td>6.29</td><td>8.70</td><td>8.63</td><td>4.97-11.76</td></tr><tr><td>Josh McDaniels</td><td>7.15</td><td>1.10</td><td>3.84</td><td>6.97</td><td>6</td><td>3.34-10.96</td></tr><tr><td>June Jones</td><td>7.10</td><td>1.02</td><td>4.03</td><td>7.10</td><td>6.33</td><td>3.37-10.83</td></tr><tr><td>Ken Whisenhunt</td><td>7.87</td><td>0.89</td><td>5.18</td><td>7.92</td><td>8</td><td>4.27-11.47</td></tr><tr><td>Kevin Gilbride</td><td>6.97</td><td>1.23</td><td>3.28</td><td>6.56</td><td>4</td><td>3.03-10.91</td></tr><tr><td>Lane Kiffin</td><td>6.96</td><td>1.23</td><td>3.26</td><td>6.55</td><td>4</td><td>3.02-10.89</td></tr><tr><td>Lindy Infante</td><td>7.13</td><td>1.11</td><td>3.78</td><td>6.92</td><td>6</td><td>3.31-10.96</td></tr><tr><td>Lovie Smith</td><td>8.46</td><td>0.77</td><td>6.13</td><td>8.59</td><td>8.87</td><td>4.98-11.94</td></tr><tr><td>Marty Mornhinweg</td><td>6.00</td><td>1.16</td><td>2.51</td><td>6.02</td><td>2.5</td><td>2.13-9.87</td></tr><tr><td>Marty Schottenheimer</td><td>9.20</td><td>0.68</td><td>7.15</td><td>9.31</td><td>9.75</td><td>5.81-12.60</td></tr><tr><td>Marv Levy</td><td>8.39</td><td>0.90</td><td>5.68</td><td>8.27</td><td>9</td><td>4.78-12.00</td></tr><tr><td>Marvin Lewis</td><td>7.69</td><td>0.74</td><td>5.45</td><td>8.11</td><td>7.66</td><td>4.24-11.14</td></tr><tr><td>Mike Ditka</td><td>6.57</td><td>1.05</td><td>3.42</td><td>6.66</td><td>5</td><td>2.81-10.32</td></tr><tr><td>Mike Holmgren</td><td>9.10</td><td>0.60</td><td>7.29</td><td>9.41</td><td>9.5</td><td>5.79-12.41</td></tr><tr><td>Mike Martz</td><td>8.76</td><td>0.86</td><td>6.17</td><td>8.62</td><td>9.5</td><td>5.19-12.33</td></tr><tr><td>Mike McCarthy</td><td>9.34</td><td>0.86</td><td>6.74</td><td>9.03</td><td>10.5</td><td>5.77-12.91</td></tr><tr><td>Mike Mularkey</td><td>7.46</td><td>1.10</td><td>4.15</td><td>7.19</td><td>7</td><td>3.65-11.27</td></tr><tr><td>Mike Nolan</td><td>6.72</td><td>1.02</td><td>3.64</td><td>6.82</td><td>5.33</td><td>2.99-10.45</td></tr><tr><td>Mike Riley</td><td>6.44</td><td>1.05</td><td>3.28</td><td>6.57</td><td>4.66</td><td>2.68-10.20</td></tr><tr><td>Mike Shanahan</td><td>8.97</td><td>0.60</td><td>7.15</td><td>9.31</td><td>9.31</td><td>5.65-12.28</td></tr><tr><td>Mike Sherman</td><td>8.74</td><td>0.85</td><td>6.17</td><td>8.62</td><td>9.5</td><td>5.18-12.30</td></tr><tr><td>Mike Singletary</td><td>7.47</td><td>1.09</td><td>4.20</td><td>7.22</td><td>7</td><td>3.68-11.27</td></tr><tr><td>Mike Smith</td><td>9.19</td><td>0.96</td><td>6.28</td><td>8.70</td><td>10.75</td><td>5.52-12.87</td></tr><tr><td>Mike Tice</td><td>7.84</td><td>0.94</td><td>5.01</td><td>7.79</td><td>8</td><td>4.19-11.49</td></tr><tr><td>Mike Tomlin</td><td>9.49</td><td>0.92</td><td>6.72</td><td>9.01</td><td>11</td><td>5.86-13.11</td></tr><tr><td>Mike White</td><td>7.60</td><td>1.10</td><td>4.30</td><td>7.29</td><td>7.5</td><td>3.79-11.41</td></tr><tr><td>Nick Saban</td><td>7.63</td><td>1.09</td><td>4.34</td><td>7.32</td><td>7.5</td><td>3.83-11.43</td></tr><tr><td>Norv Turner</td><td>7.70</td><td>0.63</td><td>5.80</td><td>8.35</td><td>7.71</td><td>4.36-11.04</td></tr><tr><td>Pete Carroll</td><td>7.96</td><td>0.93</td><td>5.16</td><td>7.90</td><td>8.25</td><td>4.32-11.60</td></tr><tr><td>Raheem Morris</td><td>6.86</td><td>1.03</td><td>3.75</td><td>6.90</td><td>5.66</td><td>3.12-10.60</td></tr><tr><td>Ray Rhodes</td><td>7.54</td><td>0.88</td><td>4.88</td><td>7.70</td><td>7.4</td><td>3.95-11.13</td></tr><tr><td>Rex Ryan</td><td>8.38</td><td>1.02</td><td>5.32</td><td>8.01</td><td>9.33</td><td>4.65-12.10</td></tr><tr><td>Rich Brooks</td><td>7.30</td><td>1.1</td><td>4.00</td><td>7.08</td><td>6.5</td><td>3.50-11.11</td></tr><tr><td>Rich Kotite</td><td>6.26</td><td>0.99</td><td>3.27</td><td>6.56</td><td>4.75</td><td>2.56-9.96</td></tr><tr><td>Richie Petitbon</td><td>6.97</td><td>1.23</td><td>3.28</td><td>6.56</td><td>4</td><td>3.03-10.91</td></tr><tr><td>Rod Marinelli</td><td>5.86</td><td>1.07</td><td>2.65</td><td>6.11</td><td>3.33</td><td>2.08-9.64</td></tr><tr><td>Romeo Crennel</td><td>6.87</td><td>0.95</td><td>3.99</td><td>7.07</td><td>6</td><td>3.20-10.53</td></tr><tr><td>Sam Wyche</td><td>6.99</td><td>1.03</td><td>3.90</td><td>7.01</td><td>6</td><td>3.26-10.73</td></tr><tr><td>Scott Linehan</td><td>6.98</td><td>1.10</td><td>3.67</td><td>6.84</td><td>5.5</td><td>3.17-10.79</td></tr><tr><td>Sean Payton</td><td>9.24</td><td>0.85</td><td>6.68</td><td>8.98</td><td>10.33</td><td>5.68-12.80</td></tr><tr><td>Steve Mariucci</td><td>8.21</td><td>0.77</td><td>5.88</td><td>8.41</td><td>8.5</td><td>4.73-11.69</td></tr><tr><td>Steve Spagnuolo</td><td>5.87</td><td>1.07</td><td>2.66</td><td>6.12</td><td>3.33</td><td>2.09-9.65</td></tr><tr><td>Steve Spurrier</td><td>7.14</td><td>1.09</td><td>3.84</td><td>6.96</td><td>6</td><td>3.33-10.94</td></tr><tr><td>Ted Marchibroda</td><td>6.79</td><td>0.86</td><td>4.21</td><td>7.22</td><td>6.16</td><td>3.22-10.35</td></tr><tr><td>Todd Haley</td><td>7.40</td><td>1.02</td><td>4.33</td><td>7.31</td><td>7</td><td>3.67-11.13</td></tr><tr><td>Tom Cable</td><td>7.31</td><td>1.11</td><td>3.95</td><td>7.04</td><td>6.5</td><td>3.48-11.13</td></tr><tr><td>Tom Coughlin</td><td>8.62</td><td>0.60</td><td>6.80</td><td>9.07</td><td>8.87</td><td>5.31-11.93</td></tr><tr><td>Tom Flores</td><td>7.14</td><td>1.09</td><td>3.86</td><td>6.98</td><td>6</td><td>3.34-10.94</td></tr><tr><td>Tony Dungy</td><td>9.94</td><td>0.67</td><td>7.93</td><td>9.87</td><td>10.69</td><td>6.57-13.32</td></tr><tr><td>Tony Sparano</td><td>7.73</td><td>0.94</td><td>4.90</td><td>7.72</td><td>7.75</td><td>4.08-11.38</td></tr><tr><td>Vince Tobin</td><td>7.10</td><td>0.95</td><td>4.23</td><td>7.24</td><td>6.5</td><td>3.44-10.77</td></tr><tr><td>Wade Phillips</td><td>9.05</td><td>0.79</td><td>6.67</td><td>8.97</td><td>9.75</td><td>5.55-12.54</td></tr><tr><td>Wayne Fontes</td><td>8.09</td><td>0.94</td><td>5.25</td><td>7.97</td><td>8.5</td><td>4.44-11.74</td></tr></tbody></table></div><p>One thing to note about this information is that some of it points to possible violations of the model's assumptions. The top two coaches both spent a lot of their career with transcendent quarterbacks, for example. That's ok -- the model will simply be off on coaches for whom the assumptions don't hold as well. This is not about finding an exact cause-and-effect relationship, it's about finding general corrolative information, which means that some coaches will be easier to predict than others.</p></div>Unknownnoreply@blogger.com11tag:blogger.com,1999:blog-5204092591876211047.post-27442850683497649242012-01-06T01:20:00.014-05:002012-01-06T02:00:38.166-05:00Betting Market Power Rankings – Offense and Defense Rankings<a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgtwZpPCSDCf8G9ZjjjIS40cxGiQlUUVneZDWExmw6erkbG_C2i_NfwycnhlmvI4Et27BnMVpnfEE3Ue8HC-jcej0L_j9v0ToAa7lIYujGkQxMerDy89tzuAZTe3WIjddN0GRlC2OJLR3PN/s1600/weik8k.jpg"><img style="float:left; margin:0 10px 10px 0;cursor:pointer; cursor:hand;width: 150px; height: 150px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgtwZpPCSDCf8G9ZjjjIS40cxGiQlUUVneZDWExmw6erkbG_C2i_NfwycnhlmvI4Et27BnMVpnfEE3Ue8HC-jcej0L_j9v0ToAa7lIYujGkQxMerDy89tzuAZTe3WIjddN0GRlC2OJLR3PN/s320/weik8k.jpg" border="0" alt=""id="BLOGGER_PHOTO_ID_5694410098349685826" /></a><br />by Michael Beuoy<br /><br />The purpose of this post is to show how the Betting Market Power Rankings can be decomposed into Offensive and Defensive strength by looking at the over/under betting lines in conjunction with the point spreads.<br /><br />One of the best features of the Advanced NFL Stats efficiency model is that it not only tells you who the best teams are, it also tells you why those teams are the best (passing efficiency, rushing success rate, penalty rate, etc.). Unfortunately, the betting markets don’t tell us why they favor one team over the other; all we get is the final point spread. However, by looking at the betting over/under for each game, and combining it with the point spread, we can at least get a sense as to whether it is offense or defense (or both) that is driving the market’s evaluation of each team.<a name='more'></a><br /><br />First, a caveat. For the purpose of these rankings, Offense is defined strictly as “Points Scored per Game” and Defense as “Points Allowed per Game”. While this may align with the general public sentiment as to what makes a good offense or a good defense, the definition is not perfect. The points a team scores is not solely a product of offensive skill and/or the defensive skill of their opponent. It can also be affected by the following:<br /><br />• Their defense – A defense can provide favorable field position to its offense by forcing short drives or turnovers.<br />• Special Teams play<br />• Pace – Not sure if this is much of a factor in the NFL (I know it is in basketball), but teams that play a faster paced game that runs less clock (no huddle, few running plays) will result in games with more scoring opportunities for both teams for a given 60 minutes of playing time.<br /><br />The ANS efficiency model avoids these pitfalls by focusing on per-play statistics. But I have no choice but to work with per-game estimates.<br /><br /><b>Methodology</b><br />The methodology ended up being very similar to the original power ranking methodology. I just had to apply some simple algebra in order to arrive at a new target. I’ll take Week 16’s Arizona @ Cincinnati game as an example. Cincinnati was favored by 4.5 points and the over/under on total points was 40.5. So, if the difference of the scores was expected to be 4.5 and the sum of the scores was expected to be 40.5, then that means that the implied predicted score was Cincinnati 22.5 and Arizona 18 (simple algebra).<br /><br />We know that average points scored in the NFL is around 22 points per team. So, the fact that the market expected Arizona to score only 18 points says either that Cincinnati’s defense is good, or that Arizona’s offense is bad (or a combination of both). Much in the same way that a high point spread tells you either the favored team is good or that the underdog is bad (or a combination of both).<br /><br />Here is how I built the original model that was based solely on point spreads (GPF = Generic Points Favored):<br /><br />Point Spread = Home Team GPF - Visiting Team GPF + 2.5<br /><br />With the team GPFs determined such that they best predicted the point spreads.<br /><br />The new model is built in a very similar fashion as follows:<br /><br />Implied Home Score = League Average Scoring + Home Team Offense GPF (oGPF) – Away Team Defense GPF (dGPF) + 1.25<br />Implied Away Score = League Average Scoring + Away Team Offense GPF (oGPF) – Home Team Defense GPF (dGPF) - 1.25<br /><br />Where I now determine two separate numbers for each team, an “oGPF” and a “dGPF”, which sum to the total team GPF (the League Average Scoring term works just like an intercept). Also note that I split the 2.5 point home field advantage evenly between offense and defense.<br /><br />See below for an updated week 16 ranking that includes O RANK and D RANK (I continue to blatantly plagiarize the ANS format):<br /><style type="text/css">.nobrtable br { display: none }</style><br /><div class="nobrtable"><br /><style type="text/css"><br />.logonobrtable br {display: none} table {border-collapse: collapse; border-width: 1px;<br /> border-style: solid; width:450px;} th {padding: 3px} td {text-align: center; padding: 3px;} #logocell {padding: 0px 3px 0px 3px; }<br /> #colorcol {background-color:#ffffe0} tr.myClass:hover {background-color: #e1ecff;} #logo {border:0; vertical-align:middle}<br /> td.headhover:hover {text-decoration: underline; cursor: pointer; cursor: hand}<br /></style><br /><br /><br /><br /><div class="logonobrtable"><table align="center" border="1" class="sortable" style="width: 450px;"><col id="colorcol"></col> <br /> <br /> <tbody><br /><tr style="background-color: #aad5ff;"><td class="headhover"><b>Rank</b></td><td class="headhover"><b>Team</b></td><td class="headhover"><b>GPF</b></td><td class="headhover"><b>GWP</b></td><td class="headhover"><b>O Rank</b></td><td class="headhover"><b>D Rank</b></td><td class="headhover"><b>ANS Rank</b></td></tr><br /><tr/><td style="text-align: center;"> 1</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td>9</td><td>0.78</td><td>1</td><td>16</td><td>4</td></tr><br /><tr/><td style="text-align: center;"> 2</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/> GB</td><td>8.5</td><td>0.77</td><td>3</td><td>9</td><td>5</td></tr><br /><tr/><td style="text-align: center;"> 3</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO</td><td>7.5</td><td>0.74</td><td>2</td><td>17</td><td>3</td></tr><br /><tr/><td style="text-align: center;"> 4</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/> SF</td><td>5</td><td>0.68</td><td>13</td><td>1</td><td>13</td></tr><br /><tr/><td style="text-align: center;"> 5</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PHI/PHI_logo-20x20.gif"/> PHI</td><td>5</td><td>0.67</td><td>4</td><td>13</td><td>6</td></tr><br /><tr/><td style="text-align: center;"> 6</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td>4.5</td><td>0.66</td><td>11</td><td>3</td><td>9</td></tr><br /><tr/><td style="text-align: center;"> 7</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PIT/PIT_logo-20x20.gif"/> PIT</td><td>4</td><td>0.64</td><td>14</td><td>2</td><td>2</td></tr><br /><tr/><td style="text-align: center;"> 8</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ATL/ATL_logo-20x20.gif"/> ATL</td><td>4</td><td>0.64</td><td>8</td><td>8</td><td>12</td></tr><br /><tr/><td style="text-align: center;"> 9</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DAL/DAL_logo-20x20.gif"/> DAL</td><td>3</td><td>0.60</td><td>5</td><td>21</td><td>7</td></tr><br /><tr/><td style="text-align: center;"> 10</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SD/SD_logo-20x20.gif"/> SD</td><td>2.5</td><td>0.60</td><td>6</td><td>20</td><td>11</td></tr><br /><tr/><td style="text-align: center;"> 11</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYJ/NYJ_logo-20x20.gif"/> NYJ</td><td>2.5</td><td>0.59</td><td>12</td><td>7</td><td>16</td></tr><br /><tr/><td style="text-align: center;"> 12</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td>1.5</td><td>0.55</td><td>7</td><td>25</td><td>8</td></tr><br /><tr/><td style="text-align: center;"> 13</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/MIA/MIA_logo-20x20.gif"/> MIA</td><td>1.5</td><td>0.55</td><td>18</td><td>5</td><td>18</td></tr><br /><tr/><td style="text-align: center;"> 14</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DET/DET_logo-20x20.gif"/> DET</td><td>1</td><td>0.54</td><td>9</td><td>23</td><td>10</td></tr><br /><tr/><td style="text-align: center;"> 15</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SEA/SEA_logo-20x20.gif"/> SEA</td><td>1</td><td>0.53</td><td>16</td><td>10</td><td>24</td></tr><br /><tr/><td style="text-align: center;"> 16</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td>0</td><td>0.50</td><td>24</td><td>4</td><td>1</td></tr><br /><tr/><td style="text-align: center;"> 17</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CIN/CIN_logo-20x20.gif"/> CIN</td><td>0</td><td>0.50</td><td>17</td><td>14</td><td>15</td></tr><br /><tr/><td style="text-align: center;"> 18</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/WAS/WAS_logo-20x20.gif"/> WAS</td><td>-0.5</td><td>0.48</td><td>21</td><td>12</td><td>19</td></tr><br /><tr/><td style="text-align: center;"> 19</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td>-1</td><td>0.47</td><td>25</td><td>11</td><td>25</td></tr><br /><tr/><td style="text-align: center;"> 20</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CAR/CAR_logo-20x20.gif" /> CAR</td><td>-1</td><td>0.47</td><td>10</td><td>26</td><td>23</td></tr><br /><tr/><td style="text-align: center;"> 21</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/TEN/TEN_logo-20x20.gif"/> TEN</td><td>-1.5</td><td>0.44</td><td>23</td><td>15</td><td>21</td></tr><br /><tr/><td style="text-align: center;"> 22</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ARI/ARI_logo-20x20.gif"/> ARZ</td><td>-2</td><td>0.43</td><td>22</td><td>19</td><td>22</td></tr><br /><tr/><td style="text-align: center;"> 23</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CHI/CHI_logo-20x20.gif" /> CHI</td><td>-2</td><td>0.42</td><td>27</td><td>6</td><td>17</td></tr><br /><tr/><td style="text-align: center;"> 24</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/OAK/OAK_logo-20x20.gif"/> RAI</td><td>-3.5</td><td>0.38</td><td>15</td><td>29</td><td>14</td></tr><br /><tr/><td style="text-align: center;"> 25</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BUF/BUF_logo-20x20.gif"/> BUF</td><td>-4.5</td><td>0.35</td><td>20</td><td>28</td><td>20</td></tr><br /><tr/><td style="text-align: center;"> 26</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/MIN/MIN_logo-20x20.gif"/> MIN</td><td>-4.5</td><td>0.35</td><td>19</td><td>30</td><td>32</td></tr><br /><tr/><td style="text-align: center;"> 27</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/KC/KC_logo-20x20.gif"/> KC</td><td>-5</td><td>0.33</td><td>31</td><td>18</td><td>27</td></tr><br /><tr/><td style="text-align: center;"> 28</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CLE/CLE_logo-20x20.gif"/> CLE</td><td>-5.5</td><td>0.31</td><td>30</td><td>22</td><td>26</td></tr><br /><tr/><td style="text-align: center;"> 29</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/TB/TB_logo-20x20.gif"/> TB</td><td>-7</td><td>0.27</td><td>26</td><td>31</td><td>30</td></tr><br /><tr/><td style="text-align: center;"> 30</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/STL/STL_logo-20x20.gif"/> STL</td><td>-7</td><td>0.27</td><td>32</td><td>24</td><td>29</td></tr><br /><tr/><td style="text-align: center;"> 31</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/JAC/JAC_logo-20x20.gif"/> JAC</td><td>-7.5</td><td>0.26</td><td>29</td><td>27</td><td>28</td></tr><br /><tr/><td style="text-align: center;"> 32</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/IND/IND_logo-20x20.gif"/> IND</td><td>-8</td><td>0.24</td><td>28</td><td>32</td><td>31</td></tr><br /></tbody></table></div></div><br /><span style="line-height: 1.6;"> <br />A couple things to note:<br /><br />• These should match the previous Week 16 rankings, but they don’t. I think there were line movements prior to Sunday which shuffled the rankings a bit.<br />• Both the top 3 offenses (NE, NO, GB) and the top 3 defenses (SF, PIT, BAL) pass the sniff test.<br /><br />Here’s another view which shows the oGPF and the dGPF explicitly (the baseline League Average scoring is 22.0 points).</span><br /><style type="text/css">.nobrtable br { display: none }</style><br /><div class="nobrtable"><br /><style type="text/css"><br />.logonobrtable br {display: none} table {border-collapse: collapse; border-width: 1px;<br /> border-style: solid; width:450px;} th {padding: 3px} td {text-align: center; padding: 3px;} #logocell {padding: 0px 3px 0px 3px; }<br /> #colorcol {background-color:#ffffe0} tr.myClass:hover {background-color: #e1ecff;} #logo {border:0; vertical-align:middle}<br /> td.headhover:hover {text-decoration: underline; cursor: pointer; cursor: hand}<br /></style><br /><br /><br /><br /><div class="logonobrtable"><table align="center" border="1" class="sortable" style="width: 450px;"><col id="colorcol"></col> <br /> <br /> <tbody><br /><tr style="background-color: #aad5ff;"><td class="headhover"><b>Rank</b></td><td class="headhover"><b>Team</b></td><td class="headhover"><b>GPF</b></td><td class="headhover"><b>oGPF</b></td><td class="headhover"><b>dGPF</b></td></tr><br /><br /><tr/><td style="text-align: center;"> 1</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td>9</td><td>8.5</td><td>0</td></tr><br /><tr/><td style="text-align: center;"> 2</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/> GB</td><td>8.5</td><td>7.0</td><td>1.5</td></tr><br /><tr/><td style="text-align: center;"> 3</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO</td><td>7.5</td><td>7.5</td><td>0</td></tr><br /><tr/><td style="text-align: center;"> 4</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/> SF</td><td>5</td><td>0.5</td><td>4.5</td></tr><br /><tr/><td style="text-align: center;"> 5</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PHI/PHI_logo-20x20.gif"/> PHI</td><td>5</td><td>3.5</td><td>1</td></tr><br /><tr/><td style="text-align: center;"> 6</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td>4.5</td><td>1.0</td><td>3.5</td></tr><br /><tr/><td style="text-align: center;"> 7</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PIT/PIT_logo-20x20.gif"/> PIT</td><td>4</td><td>0.5</td><td>4</td></tr><br /><tr/><td style="text-align: center;"> 8</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ATL/ATL_logo-20x20.gif"/> ATL</td><td>4</td><td>2.5</td><td>2</td></tr><br /><tr/><td style="text-align: center;"> 9</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DAL/DAL_logo-20x20.gif"/> DAL</td><td>3</td><td>3.5</td><td>-0.5</td></tr><br /><tr/><td style="text-align: center;"> 10</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SD/SD_logo-20x20.gif"/> SD</td><td>2.5</td><td>3.0</td><td>0</td></tr><br /><tr/><td style="text-align: center;"> 11</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYJ/NYJ_logo-20x20.gif"/> NYJ</td><td>2.5</td><td>1.0</td><td>2</td></tr><br /><tr/><td style="text-align: center;"> 12</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td>1.5</td><td>2.5</td><td>-1.5</td></tr><br /><tr/><td style="text-align: center;"> 13</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/MIA/MIA_logo-20x20.gif"/> MIA</td><td>1.5</td><td>-0.5</td><td>2</td></tr><br /><tr/><td style="text-align: center;"> 14</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DET/DET_logo-20x20.gif"/> DET</td><td>1</td><td>2.5</td><td>-1</td></tr><br /><tr/><td style="text-align: center;"> 15</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SEA/SEA_logo-20x20.gif"/> SEA</td><td>1</td><td>-0.5</td><td>1</td></tr><br /><tr/><td style="text-align: center;"> 16</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> TEX</td><td>0</td><td>-2.0</td><td>2</td></tr><br /><tr/><td style="text-align: center;"> 17</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CIN/CIN_logo-20x20.gif"/> CIN</td><td>0</td><td>-0.5</td><td>0.5</td></tr><br /><tr/><td style="text-align: center;"> 18</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/WAS/WAS_logo-20x20.gif"/> WAS</td><td>-0.5</td><td>-2.0</td><td>1</td></tr><br /><tr/><td style="text-align: center;"> 19</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td>-1</td><td>-2.0</td><td>1</td></tr><br /><tr/><td style="text-align: center;"> 20</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CAR/CAR_logo-20x20.gif" /> CAR</td><td>-1</td><td>1.5</td><td>-2.5</td></tr><br /><tr/><td style="text-align: center;"> 21</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/TEN/TEN_logo-20x20.gif"/> TEN</td><td>-1.5</td><td>-2.0</td><td>0.5</td></tr><br /><tr/><td style="text-align: center;"> 22</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ARI/ARI_logo-20x20.gif"/> ARZ</td><td>-2</td><td>-2.0</td><td>0</td></tr><br /><tr/><td style="text-align: center;"> 23</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CHI/CHI_logo-20x20.gif" /> CHI</td><td>-2</td><td>-4.0</td><td>2</td></tr><br /><tr/><td style="text-align: center;"> 24</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/OAK/OAK_logo-20x20.gif"/> RAI</td><td>-3.5</td><td>0.0</td><td>-3</td></tr><br /><tr/><td style="text-align: center;"> 25</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BUF/BUF_logo-20x20.gif"/> BUF</td><td>-4.5</td><td>-1.0</td><td>-3</td></tr><br /><tr/><td style="text-align: center;"> 26</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/MIN/MIN_logo-20x20.gif"/> MIN</td><td>-4.5</td><td>-1.0</td><td>-3.5</td></tr><br /><tr/><td style="text-align: center;"> 27</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/KC/KC_logo-20x20.gif"/> KC</td><td>-5</td><td>-5.0</td><td>0</td></tr><br /><tr/><td style="text-align: center;"> 28</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CLE/CLE_logo-20x20.gif"/> CLE</td><td>-5.5</td><td>-4.5</td><td>-1</td></tr><br /><tr/><td style="text-align: center;"> 29</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/TB/TB_logo-20x20.gif"/> TB</td><td>-7</td><td>-3.5</td><td>-3.5</td></tr><br /><tr/><td style="text-align: center;"> 30</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/STL/STL_logo-20x20.gif"/> STL</td><td>-7</td><td>-6.0</td><td>-1.5</td></tr><br /><tr/><td style="text-align: center;"> 31</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/JAC/JAC_logo-20x20.gif"/> JAC</td><td>-7.5</td><td>-4.5</td><td>-3</td></tr><br /><tr/><td style="text-align: center;"> 32</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/IND/IND_logo-20x20.gif"/> IND</td><td>-8</td><td>-4.5</td><td>-3.5</td></tr><br /></tbody></table></div></div><br /><span style="line-height: 1.6;"> <br />What jumped out at me most here was how much wider the variation was in the oGPF than in the dGPF. The standard deviation of the oGPF is 3.6 points, while it is 2.2 points for dGPF. In the comments on the ANS Week 17 Efficiency Rankings, there was a discussion with respect to the variability of offensive and defensive stats, with the conclusion that team defensive stats are more variable week to week because the defenses are at the mercy somewhat of what the offenses can do. I think the data above supports that conclusion, but I may not have thought it through entirely.<br /><br />Also, there is a correlation between the oGPF and dGPF, which probably goes beyond bad teams just being bad on both sides of the ball. The correlation coefficient is 0.24 (it varies from 0.05 to 0.50 when looking at past seasons, but it’s always positive)<br /><br />I’m hoping to do an updated ranking (including the oGPF and dGPF split) featuring just the 12 playoff teams and the latest lines, but I may not have time to get it out before the Wildcard round starts.<br /><br />Also, you can use the chart above to build point spreads and over/unders for any matchup. </span>Unknownnoreply@blogger.com5tag:blogger.com,1999:blog-5204092591876211047.post-36266222570076792972012-01-05T22:37:00.008-05:002012-01-05T23:37:47.730-05:00Respect Randomness, K.I.S.S., Beat Vegas.<a onblur="try {parent.deselectBloggerImageGracefully();} catch(e) {}" href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnPNX6dd71VkcfyU80sfKslJtnt5RTIeR0s4b_JtuxL8g9-M4O51A129BfUSWcqWbwtUGi_Fh09_fuIB-4Ur4Uqy3tc5a6s4NEipzrq5pjLqpHyDcsQ9glldy5E50ZEzWDXd8KsKotzY8a/s1600/LasVegasSign.jpg"><img style="float:left; margin:0 10px 10px 0;cursor:pointer; cursor:hand;width: 320px; height: 255px;" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnPNX6dd71VkcfyU80sfKslJtnt5RTIeR0s4b_JtuxL8g9-M4O51A129BfUSWcqWbwtUGi_Fh09_fuIB-4Ur4Uqy3tc5a6s4NEipzrq5pjLqpHyDcsQ9glldy5E50ZEzWDXd8KsKotzY8a/s320/LasVegasSign.jpg" border="0" alt=""id="BLOGGER_PHOTO_ID_5694363356924866834" /></a>by Jim Glass<br /><br />The 2011 end-of-season result is in for BigWin% - the team rating system that treats games decided by one score, 8 points or less, as ties in computing each team's W-L%, then adds a strength-of-schedule adjustment, that is all. (Rationale and background explained <a href="http://community.advancednflstats.com/2011/12/revisiting-big-wins-index-kind-of-wins.html">previously</a>.)<br /><br />Here are game prediction and efficiency results for the final eight weeks of the season. ("Efficiency" = correct game predictions divided by expected correct predictions. E.g., if among a week's 16 predictions the average predicted winner is a .750 favorite then 12 correct predictions would be expected. If the actual number is 10 then efficiency is .833, if 11 then efficiency is .917, etc.)<a name='more'></a><br /><br /><style type="text/css">.nobrtable br { display: none }</style><br /><div class="nobrtable"><br /><style type="text/css"><br />.logonobrtable br {display: none} table {border-collapse: collapse; border-width: 1px;<br /> border-style: solid; width:450px;} th {padding: 3px} td {text-align: center; padding: 3px;} #logocell {padding: 0px 3px 0px 3px; }<br /> #colorcol {background-color:#ffffe0} tr.myClass:hover {background-color: #e1ecff;} #logo {border:0; vertical-align:middle}<br /> td.headhover:hover {text-decoration: underline; cursor: pointer; cursor: hand}<br /></style><br /><br /><br /><br /><div class="logonobrtable"><table align="center" border="1" class="sortable" style="width: 450px;"><col id="colorcol"></col> <br /> <br /> <tbody><br /><tr style="background-color: #aad5ff;"><td class="headhover"><b> </b></td><td class="headhover"><b>Won-Lost</b></td><td class="headhover"><b>PCT</b></td><td class="headhover"><b>Efficiency</b></td></tr><br /><br /><tr/><td style="text-align: center;"> Big Win Index </td><td>82-40</td><td>.672</td><td>1.003</td></tr><br /><tr/><td style="text-align: center;"> Las Vegas</td><td>81-43</td><td>.653</td><td>.985</td></tr></table></div></div><br /><span style="line-height: 1.6;"> <br />(Game counts don't match because of no-favorite predictions and "push" results.)<br /><br />OK, this isn't really a method to "beat Vegas", that was just a bit of hyperbole.<br /> <br />But it's remarkable that such a simple, bare bones rating-and-picking system can so equally match Vegas while dismissing 51% of all game outcomes as being 50-50, split-the-difference, random chance. And while being applied purely mechanically, with no knowledge of teams being down to their third-string QBs, special match-ups, teams resting starters, or any of the other game-specific information known to Vegas.<br /><br />Of the 126 games played during these eight weeks, 64 were decided by less than 9 points. That is 50.8%, or slightly more than the 42% of game outcomes that are determined <a href="http://www.advancednflstats.com/2010/11/randomness-of-win-loss-records.html">by random chance</a> according to Brian Burke. These game outcomes were dismissed, treated as "ties" by BigWin%. <br /><br />Disregarding more than half of all game decisions may seem like the loss of a lot of information when evaluating teams, but sometimes less is more. Or, more may be less when what is considered more information really is just random noise. <br /><br />The idea behind BigWin% simply was to filter out the 42% of game decisions that Brian says are decided by chance to get team W-L records much less distorted by chance. It works!<br /><br />One can draw much larger lessons from this exercise about sport, life, fate, and the great amounts of work and resources that are spent in our time on parsing noise, but I shall resist.<br /><br />For the record, here are the season-end BigWin% ratings of all the teams to make the playoffs:</span><br /><br /><style type="text/css">.nobrtable br { display: none }</style><br /><div class="nobrtable"><br /><style type="text/css"><br />.logonobrtable br {display: none} table {border-collapse: collapse; border-width: 1px;<br /> border-style: solid; width:450px;} th {padding: 3px} td {text-align: center; padding: 3px;} #logocell {padding: 0px 3px 0px 3px; }<br /> #colorcol {background-color:#ffffe0} tr.myClass:hover {background-color: #e1ecff;} #logo {border:0; vertical-align:middle}<br /> td.headhover:hover {text-decoration: underline; cursor: pointer; cursor: hand}<br /></style><br /><br /><br /><br /><div class="logonobrtable"><table align="center" border="1" class="sortable" style="width: 450px;"><col id="colorcol"></col> <br /> <br /> <tbody><br /><tr style="background-color: #aad5ff;"><td class="headhover"><b>RANK</b></td><td class="headhover"><b>Team</b></td><td class="headhover"><b>Big Win%</b></td></tr><br /><br /><tr/><td style="text-align: center;"> 1</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/GB/GB_logo-20x20.gif"/> GB</td><td>0.776</td></tr><br /><tr/><td style="text-align: center;"> 2</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NE/NE_logo-20x20.gif"/> NE</td><td>0.743</td></tr><br /><tr/><td style="text-align: center;"> 3</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NO/NO_logo-20x20.gif"/> NO</td><td>0.710</td></tr><br /><tr/><td style="text-align: center;"> 4</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/BAL/BAL_logo-20x20.gif"/> BAL</td><td>0.647</td></tr><br /><tr/><td style="text-align: center;"> 5</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/SF/SF_logo-20x20.gif"/> SF</td><td>0.639</td></tr><br /><tr/><td style="text-align: center;"> 6</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/PIT/PIT_logo-20x20.gif"/> PIT</td><td>0.623</td></tr><br /><tr/><td style="text-align: center;"> 7</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/HOU/HOU_logo-20x20.gif"/> HOU</td><td>0.600</td></tr><br /><tr/><td style="text-align: center;"> 8</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DET/DET_logo-20x20.gif"/> DET</td><td>0.581</td></tr><br /><tr/><td style="text-align: center;"> 9</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/CIN/CIN_logo-20x20.gif"/> CIN</td><td>0.580</td></tr><br /><tr/><td style="text-align: center;"> ...</td><td> ...</td><td>...</td></tr><br /><tr/><td style="text-align: center;"> 12</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/ATL/ATL_logo-20x20.gif"/> ATL</td><td>0.544</td></tr><br /><tr/><td style="text-align: center;"> ...</td><td> ...</td><td>...</td></tr><br /><tr/><td style="text-align: center;"> 17</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/NYG/NYG_logo-20x20.gif"/> NYG</td><td>0.507</td></tr><br /><tr/><td style="text-align: center;"> ...</td><td> ...</td><td>...</td></tr><br /><tr/><td style="text-align: center;"> 25</td><td><img id="logo" src="http://static.nfl.com/static/site/img/teams/DEN/DEN_logo-20x20.gif"/> DEN</td><td>0.399</td></tr></table></div></div><br /><span style="line-height: 1.6;"> <br /><br /><br />Yes, Denver is down at #25. BigWin% considers Denver's record during the 11 games with Tebow starting to be 4.5-6.5 (1-3 in two-score games plus seven close games divided 3.5-3.5) against .476 strength opposition, or .385 overall. <br /><br />One of the life lessons exercises like this teach is to not confuse luck with a repeatable skill, but I've beaten that drum <a href="http://community.advancednflstats.com/2011/12/will-tim-tebow-be-denvers-dick-jauron.html">before</a>.</span>Unknownnoreply@blogger.com2