Friday, December 16, 2011

Revisiting the Big Wins Index: the kind of wins today that do predict wins tomorrow

by Jim Glass

All wins count equally in the standings ñ but they don't count equally as a measure of team strength or indicator of probable future won-loss record.

Brian Burke has written that random chance determines more than 40% of NFL game outcomes. Thirty years ago Bill James showed that baseball teams that win many (or few) close game later consistently see their W-L record regress to their record in decisive games - indicating that close game outcomes are heavily luck, and teams with good W-L records based on luck see their luck run out. At the same time, teams with disappointing W-L records due to having a lot of close losses offsetting decisive wins are primed for a turn to the better. This has since also been well documented for football and across other sports.

Of course, all this goes 100% *against* the great popular belief in the importance of "clutch play" - but that's reality. Last year, I looked at the results of 15 years of NFL playoff games for all teams that had won 11 or more games during the regular season. Sorting them by record in terms of "big wins", by 10 points or more, and "clutch, close wins", by less, produced these numbers...

* Four teams had 10 or more "big" wins in a season. Their playoff record was 11-1 with three Super Bowl wins (the fourth team was the 18-1 Patriots). Twelve teams had 9 or more "big" wins. Their playoff record was 24-7 with five SB winners, plus three SB runners-up - so eight of the 12 teams were in the Super Bowl.

* Nine teams had won nine or more close games during the regular season. Their subsequent record in the playoffs: 8-9.

* The 15 teams with the best close-game records during the regular season were a combined 103-11, 90%, in them. In the playoffs they had a record of 15-14, 52%.

* The seven teams with the worst records in close games during the regular season went only 18-30, 38%, in them. In the playoffs these "very worst" clutch-game teams went 14-4, 78%, and won three Super Bowls. (To have such an 11-5 or better W-L with a losing record in close games, these teams had to dominate in one-sided games ñ they were superior "big win" teams.)

So much for "champions win close games"!

Systematizing Big Wins.
The fact that decisions in one-sided games much better reflect team strength than decisions in close games has been known since the 1980s. But as of last year, as far as I knew, nobody had quantified the effect in a rating system. Hey, the world is full of rating systems, why not another one?

So I whipped up the "Big Win Index", a system that is simplicity itself: "Big" wins and losses are counted as wins and losses, "close games" are counted as ties, these give each team a winning percentage, which is adjusted in light of strength of schedule. Done.

But there is a real point behind it. Teams should not be evaluated on the basis of their luck. Treating close games as ties eliminates the luck factor in them for rating purposes - and so *should* produce a W-L% for each team that more closely reflects its true strength than the regular W-L record does.

As the break point between "big" and "close" I use 9 points - that eliminates just about the closest 40% of all games (corresponding to the percentage of game outcomes determined by luck) and is the border between one-score games, in which just one play may change the outcome up until the very last moment (see any Tebow game this year) and two-plus score games, in which one play can't.

This is not a "beat the Vegas spread" rating system. BWI doesn't know that the Texans are down to their third QB or if a blizzard is going to blow into Buffalo for the Dolphins game. It does not make fine distinctions between teams, or divine strengths and weaknesses. Its purpose is simply to make clear to the naked eye when one may be misjudging a team by putting too much weight on a WL record compiled in close decisions (and when other people may be doing it too). And at this, it has proved pretty effective.

Seen via Big Wins
Last season after 14 games the media and punditry were all hailing the 12-2 Falcons as they marched to the first seed in the NFC, while the Packers were a mediocre 8-6 struggling in the fight for a wildcard spot. But the first version of the BWI tabbed the Packers as #1 in the NFC and the Falcons as fifth. We know how that turned out. When the Falcons fell decisively before the Pack in their playoff game "it was hilarious to watch ESPN's Sports Reporters Sunday and see the likes of Lupica and Albom struggle to comprehend such an upset [BB]", but BWI said simply, "Best team won". The Packers had taken their losses close, the Falcons had taken their victories close.

This season after eight games, when I first ran the BWI numbers for this year, here's how they were sobering for NYC football fans (like me)...

* The Giants were a sterling 6-2, and Giants fans here in NYC were talking "Super Bowl run". But BWI picked them as the team most likely to fall off a cliff. With both their losses big and five-of-six wins small, their BW% was only 46%, with the toughest second-half schedule in the league ahead of them. They've since gone 1-4.

* The Patriots had just lost two straight to fall to 5-3 and were Vegas underdogs in a showdown with the Jets. Us Jets fans here in NYC were thinking "we're finally about to dethrone the Pats!" But all the Pats' losses were small, BWI still had them as the top team in the AFC and the Jets as just a little over .500. The Pats won by 21, and have been putting air between themselves and the competition ever since.

As to the hot topic of the moment, BWI is not impressed by the Tebow Broncos. It has the five-game Orton Broncos as a .475 team, the eight-game Tebow Broncos as a .468 team.

Perhaps this explains the mystery of Tebow's "missing stats", the Tebow "intangibles" that must exist in great amount to lift a 1-4 team up to being a 7-1 team, yet somehow can't be captured by any statistical system.

Broncos/Tebow fans treat close games as big ones, and so think Tebow has lifted the Broncos an immense distance, from being a .200 team to a .875 team, which would indeed be a tremendous accomplishment! If Tebow's huge contribution driving that immense improvement can't be seen in his numbers, then mere numbers simply must miss many very important things that go into winning football games.

But BWI says the Broncos with Orton were a 47% team, and with Tebow are still 47% team. There's no "magic" at all to explain in that. One doesn't have to work miracles to get a 47% team to a 47% level. How will this turn out in the end? We shall see.

Now I'll add that while BWI is in no way meant to serve as a "beat Vegas" metric, of course I do track it against the Vegas line (and other prediction systems) ñ and it has done surprisingly well.

The point spreads of the Vegas line and percentage win prediction of BWI are convertible into each other using Pythagorean and Log5. So in addition to tallying winning/losing picks, I also tally "efficiency", the number of favorites that win relative to the number that should win by the probabilities generated by the system. (For instance, say 10 of 16 picks win, .625. If the average pick was a 75% favorite then spreads are too high, efficiency is .625/.75 = .833, as 12 picks should have been winners and 10/12 =.833. The desired number is of course 1.00.)


Results for the five weeks of games 9 through 13.












FavoritesWon-LostPCTEfficiency
Vegas50-26.65899%
BWI52-25.675102%





(Numbers don't match exactly because of "pick 'ems" and pushes.)

Pretty good! BWI is 1.5 games ahead of Vegas without even trying to be. Well, that's only by a hair, and this is a quite small sample size, so I don't expect it to last.

But I find it very interesting that a system that uses such extremely minimal information and calculations can be competitive with the most data-loaded and sophisticated of all. More on that another time, perhaps

Now, for any who've read this far and so may be interested, the current BWI.

2011 Big Win Ratings after Game 13
This table gives each team's BigW% (its expected winning percentage against average opposition), the corresponding number of games expected to have won currently out of 13, the average strength of its full-season opposition (including the final three games of the season) and its projected final result starting from today's actual record.











































RANKTeamBig Win%Expected WinsS-O-SProjected Final
1 GB0.7810.190.46615.4
2 NE0.749.640.4612.3
3 BAL0.739.470.49312.2
4 HOU0.688.870.47812.2
5 PIT0.688.840.5012.3
6 NO0.678.720.47612.1
7 CIN0.628.090.4969.0
8 SF0.617.890.45211.9
9 TEN0.587.580.4978.9
10 ATL0.557.190.5069.7
11 DET0.557.190.5229.5
12 DAL0.557.120.4618.9
13 NYJ0.547.060.4979.7
14 CHI0.547.00.5128.4
15 SD0.536.830.4987.4
16 PHI0.486.270.4836.5
17 SEA0.486.20.4829.4
18 NYG0.476.150.5078.5
19 DEN0.476.110.5089.4
20 CAR0.465.920.5055.2
21 MIA0.445.760.4985.1
22 MIN0.435.610.5123.2
23 BUF0.435.580.5156.1
24 JAC0.425.520.5275.4
25 WAS0.374.870.4845.2
26 ARI0.374.850.4837.2
27 OAK0.364.670.5078.1
28 KC0.354.50.5075.9
29 TB0.314.090.5484.9
30 CLE0.283.690.5324.6
31 IND0.263.440.5480.7
32 STL0.243.110.5352.5



There are no dramatic contrasts like last year's Green Bay-Atlanta. But for the record, measuring by the difference between actual WL% and BW%, the most overrated teams by regular WL% currently are:


* 0.217 Green Bay

* 0.179 Oakland

* 0.163 San Francisco

* 0.145 Denver


The Packers of course also are the best team by BW%, proving once more that being very good *and* lucky is the unbeatable combination.

The most underrated teams are ...

* -0.117 Jacksonville

* -0.135 Miami

* -0.148 Carolina

* -0.264 Indianapolis

* -0.277 Minnesota

There's always next year!

3 comments:

Boston Chris said...

Love the BWI, will we be getting an update before the playoffs?

Will said...

Jim, it strikes me that a simple modification of the SRS to adjust any win/loss of 10 points or less to zero points (and probably something to smooth out blowouts) would be a good way to systematize this.

Pat Laffaye said...

Jim, your analysis is exceptional. Not sure if it was stated previously, but how do you adjust raw BW% for SOS? Are you using SRS to iterate?

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