MRE - Measure of Random Events through week 5

by Bruce D

MRE = (good luck points)-(bad luck points), so positive numbers are the luckiest teams.

For a more in-depth explanation of what "luck" points are, go to a previous post here.

If random events can't be repeated, then past points due to MRE can NOT be considered as being due to skill. Likewise, past performance due to MRE can't be included in analyzing future performance. In a nutshell, "lucky" teams can't be expected to be so "lucky", and "unlucky" teams are better than we may think.

Points for(+) the lucky team, are the same amount of points against(-) the unlucky team.

MRE is valued as follows:

punts blocked=3
interceptions=2.5
fumbles lost=2.5
field goal miss/block=2.5
punt returns for a TD=4.5
ko returns for a TD=4.5

NFL QBR Differential after week 5

by Jeff Anderton

After reading several articles about Passer Rating Differential being the most relevant stat correlated to winning NFL football games, I decided to see what the current year to date QBR Differentials were for the NFL. For those that don't know, QBR is the "new" rating that ESPN developed and introduced this summer(2011). ESPN was looking to build off the "traditional" passer rating formula and take into account specific things that happen during a play.

For example, a QB makes a bad pass on a 5 yard "out route" but the receiver makes amazing catch, the Defensive Back falls down, and the receiver then turns it up field for a 30 yard gain. Under the QBR system the QB would not get as many "points" for this play since he made a bad throw, the DB fell down, there were a lot of yards after the catch, and the receiver made an amazing catch. There are also factors that figure out how to differentiate between "garbage time" and clutch scenarios, taking into account the current score, time left in the game, type of defense being used(prevent defense dink and dumps score low), etc.

So with that quick background behind us, lets take a look at what I did to compile these numbers. I took the individual QBR rating for each teams opponent for every week of the year, then simply added them up and divided by games played. I then took the team's own QBR rating(what their man under center scored for the year so far) and subtracted what they "got" from what they "gave up". Nothing major here in terms of math, just some down and dirty research.

For games that involved teams who used 2 QB's I simply added both ratings together for that game and divided by 2. I realize there could be some flaws with this method if we look at it from a "weighted performance perspective", but it would be such a small variance I don't think it much matters.

Not a whole lot of suprises as most of the good teams are at the top and the bad teams are at the bottome, but still interesting to see where a few teams fell. I was surprised that the Texans and Eagles were this high, and also surprised that the Jets, Bears, Falcons and Redskins were this low. These numbers are through and including week 5 and account for teams that had a bye week already.


Team by Team QBR Differential through and including week 5 of the 2011 NFL Season

Team	QB Differential
Cowboys	47.56
Packers	43.48
Titans	42.2
Saints	37.96
Bills	32.48
Texans	30.84
Lions	30.12
Patriots	29.76
Chargers	29.37
Panthers	24.12
Eagles	22.52
Giants	19.78
Broncos	18.79
Ravens	14.27
Steelers	13.62
Raiders	12.36
Chiefs	10.84
49ers	10.32
Falcons	9.2
Bucs	6.72
Browns	2.54
Redskins	2.02
Bengals	0.95
Jets	-4.22
Vikings	-5.12
Seahawks	-6.73
Bears	-8.14
Cardinals	-15.24
Jaguars	-15.78
Dolphins	-18.8
Colts	-28
Rams	-35.98

Joe's numbers, and the moral of the story

Appreciating how the Old Ones played. Or: Joe Namath in the 2000s. Part III -- by Jim Glass.

Part I explained what is going on here and why. Part II presented the statistical background behind this comparison of the 1970s and 2000s.

Namath in the 2000s

"Namath's numbers were shockingly bad. You tend to remember Namath as this seminal figure, and of course he was, and then you see those stats and just go: 'Yuck.'" -- Joe Posnanski, Sports Illustrated.

This has become a popular notion among many football fans who never saw Namath play, and who have a little knowledge of football statistics - but not enough.

"Joe Namath is in the Hall of Fame because of his celebrity - getting a big contract, winning one famous game, being the first pro football player to wear pantythose in public - not for achievements on the football field." - comment at Football Outsiders.

Appreciating how the Old Ones played. Or: Joe Namath in the 2000s, continuing...

by Jim Glass

If you haven't read Part I of this, you probably should to get the context and some details about the numbers being used here.

[] Passing game changes, 1970s to 2000s. These numbers for passing statistic averages and standard deviations show how passing norms have changed since the 1970s.

("SD%" = the standard deviation divided by the average for the stat. For instance, for yards-per-completion the SD% of .128 for is the SD of 1.47 divided by the average of 11.53)

The bulk of the difference between eras results from rule changes. In 1978 the NFL adopted major rule changes to favor the passing game (see "The Top Ten Things that Changed the Game") and has steadily followed up on them since. The result has been shorter, safer, higher-percentage passing, and more of it.

Appreciating how the Old Ones played. Or: Joe Namath in the 2000s.

by Jim Glass

The way NFL football is played has changed over the decades. Statistics in part reflect this, as seen in the steady inflation of passer rating.

But more importantly, what wins games has changed – and this is not reflected in commonly used rating and ranking stats. So even using "inflation adjusted" ratings leads to mistaken conclusions about players of the past when the ratings are based on performance measures that matter the most to us today – but not the ones that mattered most to them.

This article opens with a little rant, then presents the results of multivariate regressions run for the periods 1971-5 and 2006-10 to identify changes in performance measures that matter most to winning.

To illustrate how big these changes have been, it ends by translating Joe Namath's passing numbers – particularly for his 1972 season - into 2010 terms.

MRE - Measure of Random Events through week 4

by Bruce D

MRE = (good luck points)-(bad luck points), so positive numbers are the luckiest teams.

For a more in-depth explanation of what "luck" points are, go to a previous post here.

If random events can't be repeated, then past points due to MRE can NOT be considered as being due to skill. Likewise, past performance due to MRE can't be included in analyzing future performance. In a nutshell, "lucky" teams can't be expected to be so "lucky", and "unlucky" teams are better than we may think.

Points for(+) the lucky team, are the same amount of points against(-) the unlucky team.

MRE is valued as follows:

punts blocked=3
interceptions=2.5
fumbles lost=2.5
field goal miss/block=2.5
punt returns for a TD=4.5
ko returns for a TD=4.5