Monday, February 11, 2008

Accuracy of 2007 Preseason Predictions

For the next couple weeks, I'm going to be auditing the various statistics and systems I use to see what works, what doesn't. First up, the win total projections based on plugging in preseason stats into a linear regression system trained on regular season stats and win totals. The offensive stats used were those for projected starters only, and the defensive stats were total defensive stats. Only rushing and passing yards per play stats were used.



Across the board, the preseason predictions were OK as far as preseason predictions go, which is to say not very good. The average absolute error was 2.66 games, the difference between 7-9 and 10-6. It called Miami's 1-15 season but was 7+ games short of New England's perfect regular season. Randy Moss, however, did not play in preseason. Hmm... I wonder what that bodes for next season...

The correlation coefficient comes out a little better at 0.40641. So the preseason win projections matched up somewhat strongly with actual win totals. It predicted Cleveland to have a good season, as well as Tennessee and Washington. It, however, also predicted New Orleans to be the best team in the league this season at 14-2. Again, as far as these things go, it was normal, having a mix of dead-on predictions and mile-wide misses. Looking at it from a divisional, rather than a league-wide perspective, shows pretty much the same thing.


















































TeamExpected WinsActual Wins
AFC East
BUF4.84747
MIA0.72791
NE8.426216
NYJ6.60774
AFC North
BAL6.00875
CIN5.33287
CLE8.365310
PIT13.821810
AFC South
HOU7.10548
IND9.799113
JAX11.510411
TEN8.797810
AFC West
DEN7.19727
KC3.32134
OAK9.43034
SD9.274511
NFC East
DAL11.579813
NYG4.031510
PHI12.63198
WAS9.73389
NFC North
CHI9.46757
DET10.16057
GB5.257413
MIN7.88108
NFC South
ATL7.33364
CAR8.84367
NO14.40207
TB3.52389
NFC West
ARI7.57988
STL4.56143
SF8.13665
SEA11.189610



For 4 out of the 8 divisions, the projected win totals had a very strong correlation with regular season standings. The only complete miss was the NFC North, where the order was reversed. But with the exception of Oakland, the AFC West predictions were also very good. The NFC East and South predictions were essentially a wash with weak correlations. So only 3 of 8 divisions were complete failures. The p-values, however, show that the correlation coefficients have a higher-than-desired probability of being achievable with random data. The small sample size (n=4) for each division plays a large role in this.











TeamCorr. Coef.P-valueMean Abs. Err.
AFC East0.80700.19303.1516
AFC North0.74240.25762.0331
AFC South0.70250.29751.4520
AFC West0.47540.52462.0079
NFC East-0.01040.98963.1886
NFC North-0.95530.04473.3724
NFC South-0.23030.76974.5139
NFC West0.88290.11711.5770


I think the lesson to take away from this, however, is that preseason does have some meaning. Most studies into the meaning of preseason have looked at win-loss records, which any football researcher would know is not the most accurate reflection of team ability, especially with a sample size of four. Skill is skill and should be visible even when the effort isn't 100%. Filtering out the play of benchwarmers from the statistics is important, and with some more development, it looks like reasonably good predictions can be made with preseason stats.

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Sunday, February 3, 2008

Super Bowl XLII Win Probability




Home TeamAway TeamP(Home Team Won) (%)Final Score Margin
NENYG44.5644-3


Despite the home team bias of the system given the neutral site, the Giants came out with the higher win probability. Their 2 fumbles (both recovered) and the one interception weren't enough to cancel out the Brady's fumble and the Patriots' poor performance in general.

As I pointed out in my preview, the two X factors that could play in the Giants' favor were the running game and pass protection. Both did play in their favor. The Giants gained 3.5 yards per carry compared to the Patriots' 2.8 ypc. And the Giants generated a ton of pressure on Brady the entire night, leading to 5 sacks. Eli also continued his hot streak, averaging 6.7 yards per pass, compared to 4.3 for Brady.

As a Dolfan, I'm ecstatic. As a blogger on predicting football games, I take pride in my ideas coming to fruition.

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Tuesday, January 29, 2008

Super Bowl XLII Breakdown - Pats vs. Giants

Stats used in the preview are unadjusted for opponent and cover the regular-season only.

Patriots Run Offense vs. Giants Run Defense
Pats' Run Off: 14th in league, 4.0998 yards per carry, 1.6663% VOLA (Value Over League Average)
Giants' Run Def: 9th, 5.7191 yards per carry, 3.8020% VOLA
Advantage: Giants, worth 0.4905 points

The interesting thing about the Patriots this season has been their seemingly mediocre running game. According to Football Outsiders, they have the best running offense in the league. Since Football Outsiders' stats are about gaining the yards you need, I'm thinking that the Patriots are put in an abnormally high proportion of short-yardage situations because their passing game is ridiculously good. Looking here, the Patriots are a paltry 26th in the league in running plays over 10 yards. With the threat of Randy Moss, it's quite possible that safeties cannot commit to run defense even in situations where they expect the run. My system does not see the Giants' advantage as being particularly large nor particularly valuable, but if the Patriots are stuck in numerous 3rd-and-4 or -5 situations, expect the passing game to bail them out.


Giants Run Offense vs. Patriots Run Defense
Giants' Run Off: 14th in league, 4.0998 yards per carry, 1.6663% VOLA
Pats' Run Def: 26th, 4.3733 yards per carry, -8.4481% VOLA
Advantage: Giants, worth 2.7902 points

My research into postseason success has shown that balanced teams (as in being good to very good at most things, not being equally good at everything) go the distance, which is why it's disconcerting to see the Patriots' run defense ranked so low. This might also be a function of their pass offense being so good. They can afford to give up big runs that eat up clock when ahead 20 points. Or their linebackers are old and just not very good. I'm inclined to go with the latter. A good game from Brandon Jacobs will go a long way towards keeping the Giants in it, since that will keep Tom Brady off the field. Jacob's high success rate is a very good omen. The advantage here could very well be worth more than 3 points.

Patriots Pass Offense vs. Giants Pass Defense
Pats' Pass Off: 1st in league, 7.6294 yards per pass, 26.1090% VOLA
Giants' Pass Def: 8th, 6.8706 yards per pass, 5.6341% VOLA
Advantage: Patriots, worth 3.7375 points

How can the advantage be worth only 4 points, you ask? Well, keep in mind that the prediction system is trained not to output extreme values because quite often they don't come true. Look at some of the close games the Pats had against teams like the Ravens. At any rate, I think it's clear that His Excellency, Field Marshall, Al-Haji, Dr. Wes Welker, Life President of Wide Receivers, conqueror of the National Football League, distinguished service order of the Military Cross, Victoria Cross and Professor of Geography will just freakin' dominate this game. Might I also be the first to suggest that Randy Moss' comeback is thanks entirely to human growth hormone? How else does a broken-down receiver make such a miraculous comeback? Tainted perfect season! McCarthyism! Join the fun! *!


Giants Pass Offense vs. Patriots Pass Defense
Giants' Pass Off: 23th in league, 5.5236 yards per pass, -8.6972% VOLA
Pats' Pass Def: 5th, 5.3106 yards per pass, 12.2180% VOLA
Advantage: Patriots, worth 4.0638 points

Eli Manning has been good in the playoffs, but in the regular season, he was crap. I would say go with the larger sample of data, but he played well against the Patriots the last time. The Giants can't win without a good game from Manning. The odds say that it won't happen. Momentum is nothing next to regression to the mean. If you're a mediocre quarterback, you'll eventually play like one.


Patriots Pass Rush vs. Giants Pass Protection
Pats' Sack Rate Made: 2nd in league, 8.2024% of pass plays, 35.9070% VOLA
Giants' Sack Rate Allowed: 8th, 4.9037% of pass plays, 18.7510% VOLA
Advantage: Patriots, 0.0232 points

I do not remember the Patriots' pass rush being this good, but the Giants' strong offensive line play has a good chance of neutralizing the pass rush.


Giants Pass Rush vs. Patriots Pass Protection
Giants' Sack Rate Made: 1st in league, 9.0592% of pass plays, 50.1030% VOLA
Patriots' Sack Rate Allowed: 4th, 3.4596% of pass plays, 42.6770% VOLA
Advantage: Giants, 0.0536 points

Similarly, the Pats' pass protection and Giants' pass rush cancel each other out. However, I will say that I saw Matt Light get abused in a few games against top-tier pass rushers (the Colts game comes to mind). Maybe Strahan has one last great game left in him.


Patriots 3rd Down Offense vs. Giants 3rd Down Defense
Pats' Conversion Rate Made: 2nd in league, 48.1674% conversion rate, 21.9020% VOLA
Giants' Conversion Rate Allowed: 5th, 34.5970% conversion rate, 12.4420% VOLA
Advantage: Patriots, 0.5455 points

Giants 3rd Down Offense vs. Patriots 3rd Down Defense
Giants' Conversion Rate Made: 12th in league, 41.7431% conversion rate, 5.6435% VOLA
Patriots' Conversion Rate Allowed: 4th, 33.6897% conversion rate, 14.7380% VOLA
Advantage: Patriots, 0.5241 points

The Patriots' success on third downs is a function of their passing game. Again, I think if the Giants can avoid 3rd-and-shorts, they can go toe-to-toe with the Patriots.

Patriots Interception Rate Given vs. Giants Interception Rate Taken
Pats' Interception Rate Given: 1st in league, 1.4827% of pass plays, 49.8100% VOLA
Giants' Interception Rate Taken: 26th, 2.4390% of pass plays, -17.4380% VOLA
Advantage: Patriots, 0.9639 points

Giants Interception Rate Given vs. Patriots Interception Rate Taken
Giants' Interception Rate Given: 26th, 3.5026% of pass plays, -18.5660% VOLA
Patriots' Interception Rate Taken: 8th, 3.3159% of pass plays, 12.2440% VOLA
Advantage: Patriots, 0.4416 points

Patriots Fumble Rate Given vs. Giants Fumble Rate Taken
Pats' Fumble Rate Given: 1st in league, 1.6000% of plays, 48.3080% VOLA
Giants' Fumble Rate Taken: 18, 3.2595% of plays, 5.3054% VOLA
Advantage: Patriots, 1.0120 points

Giants Fumble Rate Given vs. Patriots Fumble Rate Taken
Giants' Fumble Rate Given: 20th in league, 3.2581% of plays, -5.2632% VOLA
Patriots' Fumble Rate Taken: 16th, 3.3333% of plays, 7.6923% VOLA
Advantage: Patriots, 0.3050 points

The Giants defense isn't very good at creating turnovers, and they cough up the ball too often. This game could very easily be a 30-point blowout on the basis of a few Giants' turnovers.


Final Prediction: Patriots by 8 points (8.3633 to be exact)
This translates to about a 75% chance of winning the game. A lot of things have to go the Giants' way for them to even stay in it. That said, the '72 Dolphins did not have as many close calls as the Patriots have had. To me, this game is all about regression to the mean. Either Eli Manning regresses to the mean and the game ends 52-0 Patriots or the Patriots regress to the mean and finally lose a close game. Maybe the Patriots will experience some bad luck with injuries finally and lose somebody that matters.

Read More......

Sunday, January 20, 2008

Win Probabilities 2007 Conference Championships

These probabilities of victory are based on the box score stats, training on 1996-2006. Inputs include rushing and passing efficiency by yards per play, third down efficiency, sack rates, turnover rates and penalty yards. The difference between probability and result can stem from recovered fumbles, where the ball was turned over, special teams, among other things.





Home TeamAway TeamP(Home Team Won) (%)Final Score Margin
NESD68.75469
GBNYG33.1222-3


SD@NE - The two teams were about equal in rushing efficiency. They weren't that far apart in passing efficiency. New England had 3 picks and a recovered fumble; San Diego had 2 picks and a recovered fumble. New England, however, was much better on third downs, converting 53.84%, compared to San Diego's 25% efficiency. If San Diego had converted half of their third downs, they would have had a 57% chance of winning the game.

NYG@GB - Similarly, in this game, the Packers were the more efficient team overall but converted only 1 of 10 third downs. Despite 5 fumbles by the Giants (though only one was lost), Green Bay still had less than a 1 in 3 shot of winning the game. Converting 3 third downs would have given them a 51% chance of winning the game. Without Favre's 2 interceptions, however, Green Bay would have had a 68% chance of winning.

Read More......

Monday, January 14, 2008

Predictions 2007 Conference Championships






Predictions based on opponent-adjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
SD @ NE7.314872.2577
NYG @ GB4.143664.2149


Looks like another Pats-Packers Super Bowl coming up.

Read More......

Win Probabilities 2007 Divisional Round

These probabilities of victory are based on the box score stats, training on 1996-2006. Inputs include rushing and passing efficiency by yards per play, third down efficiency, sack rates, turnover rates and penalty yards. The difference between probability and result can stem from recovered fumbles, where the ball was turned over, special teams, among other things.

As you can see, all of the victories were pretty decisive this week, though Sunday's games were closer than the box score stats would indicate.







Home TeamAway TeamP(Home Team Won) (%)Final Score Margin
GBSEA99.353422
NEJAX96.785511
DALNYG8.6389-4
INDSD1.2989-4


SD@IND - Peyton Manning played really well. 8.4 yards per pass is way above average, and San Diego's pass defense was top-10 this year to begin with. Keep in mind, however, that just because something is unlikely doesn't mean it won't happen. I would put the probability of Rivers average 13.6 yards per pass against a top-5 defense as next to zero. Play that game over 1000 times and it might happen that one time. But it did happen. This game was not Manning's fault. If the interception at the end of the first didn't happen, that would have increased their probability of winning to 2.2%. It made that little difference. You're just not going to win with your pass defense that porous.

NYG@DAL - Ignoring the recovered fumble boosts Dallas' win probability to 13.5%, but penalties and turnovers made a big difference. Even without those, however, Romo and the passing game just didn't perform up to snuff.

Read More......

Monday, January 7, 2008

Predictions 2007 Divisional Round








Predictions based on opponent-adjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
JAX @ NE5.210565.7171
SD @ IND7.574774.7456
NYG @ DAL6.428770.6450
SEA @ GB4.250064.4811


Last week, my predictions and the system's predictions went 2 for 4.

Let's take a look at the matchups I didn't see coming.

NYG @ DAL
Rush Off: NYG - 4.5940 yards per carry (3rd), DAL - 4.1799 ypc (9th)
Rush Def: NYG - 3.8020 ypc (9th), DAL - 3.9816 ypc (14th)
Pass Off: NYG - 5.5236 yards per pass (23rd), DAL - 7.3662 ypp (2nd)
Pass Def: NYG - 6.8706 ypp (8th), DAL - 5.4370 ypp (7th)

The Giants have the better running game, but the Cowboys have the better passing game, which is more important. That Eli Manning performed so well against the #2 pass defense in the wild card round is promising, and Terrell Owens' injury could severely limit Dallas' passing game. Tony Romo is not exactly a proven playoff quarterback either, but I'd expect some regression to the mean for Eli. The probability of him performing so well against 2 top 10 pass defenses is just really low. I'm still picking Dallas to advance.

SEA @ GB
Rush Off: SEA - 3.7837 ypc (24th), GB - 4.1160 ypc (13th)
Rush Def: SEA - 3.8957 ypc (13th), GB - 3.8732 ypc (12th)
Pass Off: SEA - 6.33233 ypp (13th), GB - 7.2752 ypp (3rd)
Pass Def: SEA - 5.7178 ypp (10th), GB - 5.9208 ypp (12th)

The Packers have a much better offense than the Seahawks, though their defenses are pretty much the same statistically. The Seahawks did plenty well against a superior pass defense in the Redskins game, and I could see an upset happening, but Brett Favre has just been too good this season. Packers win.

Read More......

Sunday, January 6, 2008

Win Probabilities 2007 - Wild Card







Home TeamAway TeamP(Home Team Won) (%)Final Score Margin
PITJAX71.8961-2
SEAWAS77.948521
TBNYG10.7964-10
SDTEN90.368911


Teams that "should have" won but didn't
Pittsburgh Steelers (vs. Jaguars), Win Prob = 71.8961% Pittsburgh was more efficient passing (6.2 yards per pass vs. 4.2) and on 3rd downs. Despite the fact that Pittsburgh threw 3 picks and gave up a fumble, they ran 20 more plays overall, weighing down their turnover rates compared to the Jags' 2 picks on 25 pass plays.

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Friday, January 4, 2008

Football Professor Podcast Interview - 2007 Playoffs Edition

After the article I posted on Wednesday, Doug Walters over at the Football Professor blog and I decided to do another podcast about our expectations for the 2007 playoffs. Listen to it here or on Doug's blog.

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Wednesday, January 2, 2008

2007 Playoff Predictions (Full Bracket)

As my prediction system is going to be picking all the home teams from this point out, I thought I'd go through each round and pick games using the system's predictions, reasoning based on past research, and maybe a smidgen of personal bias. (No, the tattoo is German for "The Brady, The.")


WILD CARD ROUND








Predictions based on unadjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
JAX @ PIT4.552865.8528
TEN @ SD5.198966.2033
NYG @ TB4.850767.0733
WAS @ SEA1.859757.9650


This year, my prediction system using unadjusted stats was wrong more often than not when the projected probability of the home team winning was between 50 and 60%. Therefore, I'm picking Seattle to lose to Washington.
When the project probability of the home team winning was between 60 and 70%, the system was correct 2 out of 3 times. There are 3 such games in the wild card round. Since Pittsburgh's starting running back is out and they have the lowest probability of winning of the three, I'm picking Jacksonville to beat Pittsburgh.
San Diego and Tampa Bay should win their games as predicted.

DIVISIONAL ROUND







Predictions based on opponent-adjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
JAX @ NE5.210565.7171
SD @ IND7.574774.7456
WAS @ DAL4.612966.0576
TB @ GB2.250857.1654


Surprisingly, Green Bay is not seen as a very heavy favorite against Tampa Bay. The weather might tilt things more heavily in Green Bay's favor. But Tampa Bay is seen as the better team overall, despite their 9-7 record (a GB@TB game is given a 61% probability of a Bucs win). So that's the one upset I'd pick.


CONFERENCE CHAMPIONSHIP






Predictions based on opponent-adjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
IND @ NE4.210063.4600
TB @ DAL4.536064.1551


In this article, I looked into the relative importance of defense in the postseason. In short, teams with good offenses tend to make the playoffs, so having a good defense in addition will get you deeper into the playoffs. The Patriots' pass offense has looked ridiculously good, but they are ranked 14th in rush offense VOLA and 26th in rush defense VOLA. Indy is ranked 21st and 7th, in the same categories respectively. Rush defense has shown to be of more importance in winning the Super Bowl than rush offense (though Baltimore and Tampa Bay might be skewing the sample there). Pass defense is essential, and they are both about equally good. Indy is 4th and New England is 5th in unadjusted pass defense VOLA. Indy's pass offense has also been hampered by injuries, weighing down their numbers. New England has the weather advantage over the dome team, but I'll go with the slightly better balanced Colts upsetting the Pats, leaving them at 17-1.

Dallas is simply a much better team than the Bucs.

SUPER BOWL





Predictions based on opponent-adjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
DAL @ IND4.945865.7789
IND @ DAL3.729863.1363


Indy is seen as a stronger team. Given the neutral site, I'm picking the Colts to repeat as champions.

Read More......

Predicitons 2007 Wild Card Round and End of Year Accuracy Report








Predictions based on opponent-adjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
JAX @ PIT3.649362.5294
TEN @ SD4.585064.7420
NYG @ TB4.375165.1118
WAS @ SEA0.293451.9924










Predictions based on unadjusted stats
GamePredicted Final Score MarginP(Home Team Wins)
JAX @ PIT4.552865.8528
TEN @ SD5.198966.2033
NYG @ TB4.850767.0733
WAS @ SEA1.859757.9650



Final Accuracy Numbers for 2007 Season (weeks 3-17)
OPPONENT ADJUSTED
Linear regression
Win prediction accuracy: 66.9643%
Mean absolute error: 11.3762 points
Correlation with result: 0.4032
% of games predicted as home team wins: 71.8750%
Logistic regression
Win prediction accuracy: 66.0714%
Correlation with result: 0.3939
% of games predicted as home team wins: 73.6607%
Win prediction accuracy when 20%≤P(home team wins)<30%: 100.0000
Win prediction accuracy when 30%≤P(home team wins)<40%: 76.1905
Win prediction accuracy when 40%≤P(home team wins)<50%: 60.0000
Win prediction accuracy when 50%≤P(home team wins)<60%: 50.0000
Win prediction accuracy when 60%≤P(home team wins)<70%: 74.5763
Win prediction accuracy when 70%≤P(home team wins)<80%: 65.8537
Win prediction accuracy when 80%≤P(home team wins)<90%: 90.9091

UNADJUSTED
Linear regression
Win prediction accuracy: 65.1786%
Mean absolute error: 11.4125 points
Correlation with result: 0.3864
% of games predicted as home team wins: 70.0893%
Logistic regression
Win prediction accuracy: 62.9464%
Correlation with result: 0.3775
% of games predicted as home team wins: 70.5357%
Win prediction accuracy when 10%≤P(home team wins)<20%: 100.0000
Win prediction accuracy when 20%≤P(home team wins)<30%: 60.0000
Win prediction accuracy when 30%≤P(home team wins)<40%: 70.0000
Win prediction accuracy when 40%≤P(home team wins)<50%: 52.6316
Win prediction accuracy when 50%≤P(home team wins)<60%: 46.5116
Win prediction accuracy when 60%≤P(home team wins)<70%: 66.1017
Win prediction accuracy when 70%≤P(home team wins)<80%: 76.1905
Win prediction accuracy when 80%≤P(home team wins)<90%: 69.2308
Win prediction accuracy when 90%≤P(home team wins)<100%: 100.0000

Read More......

Power Rankings 2007 Week 17

The power rankings for this site were developed in this article. The idea behind them is simple: if each team played one home game and one away game against every other team in the league, who would be the most successful?

The power rankings use logistic regression to predict the probability of winning. The score you see along with the rankings is the expected win total over a 16-game season based on the expected winning percentages over the 62 games (i.e. the sum of those probabilities).




































Power Rankings, Opponent-adjusted
RankTeamExpected Wins
1NE10.5759
2IND10.3170
3DAL10.1534
4PIT9.8614
5TB9.5910
6JAX9.5862
7GB9.2658
8WAS9.1119
9MIN9.1075
10PHI9.0675
11SD8.7100
12NYG8.6673
13TEN8.4478
14SEA8.3719
15DEN8.2001
16HOU7.9178
17CLE7.7195
18CIN7.5846
19CAR7.4754
20ARI7.3438
21BUF7.2895
22NO7.2215
23ATL7.1775
24DET7.1663
25BAL6.7068
26NYJ6.6356
27CHI6.5820
28STL6.4483
29KC6.2941
30MIA6.1462
31SF5.6674
32OAK5.5888





































Power Rankings, Unadjusted
RankTeamExpected Wins
1NE10.5837
2PIT10.2658
3IND10.1597
4DAL10.0700
5TB9.8437
6MIN9.6704
7GB9.5724
8JAX9.5190
9SEA8.8647
10SD8.8134
11PHI8.7488
12WAS8.7349
13NYG8.5790
14TEN8.4120
15DEN8.2860
16CLE8.2273
17CIN7.9928
18ARI7.8841
19HOU7.6742
20NO7.3013
21CAR7.1811
22DET7.0157
23ATL6.9466
24BUF6.8609
25NYJ6.6046
26BAL6.5961
27STL6.4422
28KC6.1708
29CHI6.1171
30MIA5.7952
31OAK5.5368
32SF5.5296


Read More......

The Value of Homefield Advantage 2007 Week 17

All Games
Home Team Win %: 56.6667%
Avg. Final Score Margin: 2.7000

Interconference
Home Team Win %: 65.0000%
Avg. Final Score Margin: 5.6000

Interdivision, Intraconference
Home Team Win %: 63.0435%
Avg. Final Score Margin: 3.2935

Intradivsion
Home Team Win %: 44.3182%
Avg. Final Score Margin: 0.1023

Read More......

Stats (Raw and VOLA) 2007 Week 17

These are the final statistical rankings of 2007. The stats included are what I use in my predictions.





































Rush offense, Unadjusted (League Avg = 4.0326)
RankTeamVOLA (%)Actual Stat
1MIN31.95505.3212
2PHI16.27404.6888
3NYG13.92204.5940
4JAX13.22704.5660
5DEN13.12304.5618
6CLE7.38274.3303
7PIT5.22134.2431
8SD4.25394.2041
9DAL3.65214.1799
10TB3.38944.1693
11OAK2.61584.1381
12SF2.59564.1373
13GB2.06814.1160
14NE1.66634.0998
15CAR0.29174.0443
16BUF-0.36524.0179
17MIA-1.12513.9872
18DET-2.02513.9509
19ATL-2.09623.9481
20TEN-3.68513.8840
21IND-5.14493.8251
22NYJ-5.42293.8139
23HOU-5.68433.8034
24SEA-6.17133.7837
25STL-6.27093.7797
26WAS-6.97023.7515
27NO-7.10293.7462
28CIN-7.24593.7404
29ARI-10.55403.6070
30BAL-18.38503.2912
31KC-19.40603.2500
32CHI-22.03803.1439




































Rush defense, Unadjusted (League Avg = 4.0326)
RankTeamVOLA (%)Actual Stat
1BAL29.00502.8629
2MIN22.93003.1079
3PIT22.64703.1193
4WAS7.82993.7168
5CAR7.04683.7484
6SF6.71233.7619
7IND6.54323.7687
8TB5.72393.8018
9NYG5.71913.8020
10PHI5.50793.8105
11ARI4.03723.8698
12GB3.95143.8732
13SEA3.39363.8957
14DAL1.26483.9816
15TEN1.14313.9865
16NO-0.04294.0343
17JAX-2.06074.1157
18STL-2.52814.1345
19SD-2.64944.1394
20NYJ-3.41294.1702
21CIN-4.54934.2160
22ATL-5.44324.2521
23DET-5.77904.2656
24KC-7.69864.3430
25CHI-8.00544.3554
26NE-8.44814.3733
27HOU-8.52844.3765
28BUF-8.78424.3868
29CLE-11.69904.5044
30MIA-11.95604.5147
31DEN-12.95204.5549
32OAK-19.09204.8025




































Pass offense, Unadjusted (League Avg = 6.0498)
RankTeamVOLA (%)Actual Stat
1NE26.10907.6294
2DAL21.76007.3662
3GB20.25507.2752
4IND16.10907.0244
5HOU12.52606.8076
6CIN11.99306.7754
7JAX10.34006.6754
8ARI9.04066.5967
9CLE8.80186.5823
10DEN8.30276.5521
11NO6.77536.4597
12TB5.49316.3821
13SEA4.66896.3323
14PIT3.73086.2755
15WAS2.08146.1757
16SD0.34556.0707
17DET0.28906.0673
18PHI-0.84975.9984
19MIN-3.39615.8443
20TEN-3.89545.8141
21CHI-7.46265.5983
22BUF-7.56145.5924
23NYG-8.69725.5236
24ATL-9.15685.4958
25STL-11.08205.3794
26NYJ-11.79405.3363
27OAK-12.15605.3144
28KC-14.78105.1556
29MIA-15.69405.1004
30BAL-15.82705.0923
31CAR-16.67705.0409
32SF-32.42704.0880




































Pass defense, Unadjusted (League Avg = 6.0498)
RankTeamVOLA (%)Actual Stat
1PIT15.28305.1252
2TB13.56005.2295
3TEN13.27505.2467
4IND13.14205.2547
5NE12.21805.3106
6WAS10.58905.4092
7DAL10.12905.4370
8NYG6.87065.6341
9SD5.77935.7002
10SEA5.48825.7178
11JAX2.70105.8864
12GB2.13285.9208
13PHI1.22365.9758
14KC-0.17256.0602
15CLE-0.40426.0743
16CAR-1.09536.1161
17ARI-1.30436.1287
18MIN-2.41976.1962
19DEN-4.15916.3014
20NYJ-4.26786.3080
21SF-4.41786.3171
22HOU-5.03926.3547
23CHI-5.14106.3608
24BUF-6.46426.4409
25DET-6.85946.4648
26ATL-7.26506.4893
27STL-8.38306.5570
28CIN-8.41206.5587
29MIA-11.89506.7694
30BAL-12.23006.7897
31OAK-13.78106.8835
32NO-16.65807.0576




































Sack rate made, Unadjusted (League Avg = 6.0353%)
RankTeamVOLA (%)Actual Stat
1NYG50.10309.0592
2NE35.90708.2024
3KC23.10407.4297
4SEA21.63307.3410
5DAL21.55907.3365
6CHI19.57107.2165
7SD16.56607.0352
8MIA13.48706.8493
9DEN11.36006.7210
10PIT8.25536.5336
11TEN6.28196.4145
12JAX5.51746.3683
13BAL4.54686.3098
14PHI3.19846.2284
15GB2.09826.1620
16TB1.37876.1185
17ARI-1.56985.9406
18OAK-1.67805.9341
19NYJ-3.89945.8000
20DET-4.06015.7903
21NO-4.63845.7554
22STL-10.11405.4249
23SF-10.51505.4007
24HOU-11.13505.3633
25IND-11.80005.3232
26MIN-15.09305.1244
27WAS-16.23805.0553
28CLE-23.44304.6205
29ATL-26.29404.4484
30BUF-30.02904.2230
31CAR-31.94804.1072
32CIN-35.13903.9146




































Sack rate allowed, Unadjusted (League Avg = 6.0353%)
RankTeamVOLA (%)Actual Stat
1NO62.90502.2388
2CIN52.42002.8716
3GB47.17903.1879
4NE42.67703.4596
5CLE41.34803.5398
6ARI35.34003.9025
7HOU33.84403.9927
8IND33.60804.0070
9DAL22.65804.6679
10SD19.66504.8485
11NYG18.75104.9037
12WAS15.95405.0725
13BUF8.53595.5202
14SEA4.71465.7508
15DEN3.06945.8501
16JAX0.38636.0120
17TEN-0.41866.0606
18CAR-1.63196.1338
19BAL-8.42186.5436
20MIA-10.83006.6890
21TB-13.40106.8441
22CHI-18.74507.1667
23ATL-26.81807.6539
24PHI-29.69407.8275
25MIN-30.71607.8892
26DET-32.24107.9812
27STL-32.33207.9867
28OAK-41.15608.5192
29KC-45.01308.7520
30NYJ-55.42709.3805
31SF-57.52309.5070
32PIT-58.92809.5918




































Third down % converted, Unadjusted (League Avg = 39.5132%)
RankTeamVOLA (%)Actual Stat
1IND24.670049.2611
2NE21.902048.1674
3PIT18.487046.8180
4NO17.079046.2616
5CIN16.806046.1538
6JAX15.562045.6622
7HOU12.771044.5594
8GB8.283042.7861
9PHI7.199842.3581
10DAL6.827842.2111
11CLE6.690642.1569
12NYG5.643541.7431
13TEN3.797841.0138
14WAS3.023740.7080
15DEN2.254640.4041
16SD-0.660239.2523
17TB-2.570138.4977
18BAL-2.661538.4615
19NYJ-4.815037.6106
20MIA-5.965737.1560
21ATL-8.165036.2869
22CAR-8.460436.1702
23SEA-8.938535.9813
24OAK-8.980035.9649
25STL-9.209035.8744
26ARI-9.437035.7843
27MIN-12.687034.5002
28KC-13.822034.0517
29CHI-13.868034.0335
30BUF-15.640033.3333
31DET-17.416032.6316
32SF-20.625031.3636




































Third down % allowed, Unadjusted (League Avg = 39.5132%)
RankTeamVOLA (%)Actual Stat
1KC20.530031.4011
2CHI17.153032.7355
3GB16.447033.0145
4NE14.738033.6897
5NYG12.442034.5970
6WAS9.031135.9447
7BAL7.354636.6072
8CLE7.007836.7442
9SEA6.588536.9099
10ATL5.998837.1429
11PHI5.965737.1560
12STL1.298839.0000
13OAK1.178339.0476
14SD0.447239.3365
15DAL0.408339.3519
16JAX-0.728439.8010
17MIN-1.664640.1709
18SF-1.862140.2490
19PIT-2.409140.4651
20TB-2.813840.6250
21ARI-3.797841.0138
22NO-5.654841.7476
23HOU-6.089141.9192
24TEN-6.733842.1739
25NYJ-6.749442.1801
26CAR-7.503042.4779
27DEN-8.123442.7230
28CIN-8.283042.7861
29BUF-14.112045.0893
30IND-14.373045.1924
31DET-15.252045.5397
32MIA-19.240047.1155




































Int. Rate Given, Unadjusted (League Avg = 2.9542%)
RankTeamVOLA (%)Actual Stat
1NE49.81001.4827
2TB48.51601.5209
3JAX45.73101.6032
4WAS32.54401.9928
5SEA29.70402.0767
6BAL20.48502.3490
7GB20.48502.3490
8PHI18.88902.3962
9IND17.43802.4390
10ATL15.51502.4958
11MIA9.43022.6756
12NO9.05842.6866
13DEN7.17422.7422
14PIT3.28442.8571
15BUF-0.61712.9724
16MIN-1.04622.9851
17CAR-6.96243.1599
18SF-7.27263.1690
19SD-9.41573.2323
20KC-9.72603.2415
21NYJ-13.83303.3628
22CIN-14.36003.3784
23DAL-15.46803.4111
24TEN-16.25403.4343
25CHI-18.47703.5000
26NYG-18.56603.5026
27CLE-19.82503.5398
28DET-21.84003.5994
29HOU-29.01303.8113
30ARI-32.09903.9024
31OAK-37.32404.0568
32STL-57.70604.6589




































Int. Rate Taken, Unadjusted (League Avg = 2.9542%)
RankTeamVOLA (%)Actual Stat
1SD70.10305.0251
2IND41.58004.1825
3OAK33.91403.9560
4TEN22.48503.6184
5JAX16.52503.4423
6CIN14.44103.3808
7GB13.23203.3451
8NE12.24403.3159
9SEA10.44203.2626
10STL10.18203.2550
11BAL10.03003.2505
12TB10.03003.2505
13MIA8.19783.1963
14BUF2.92373.0405
15DAL2.57723.0303
16NYJ1.55143.0000
17ARI0.54592.9703
18DEN-3.48142.8513
19ATL-3.62862.8470
20KC-4.83802.8112
21CLE-5.03992.8053
22DET-9.94402.6604
23CHI-12.75702.5773
24CAR-15.37402.5000
25MIN-15.74602.4890
26NYG-17.43802.4390
27NO-20.85302.3381
28WAS-25.13302.2117
29SF-29.23202.0906
30PIT-32.42201.9964
31HOU-35.57901.9031
32PHI-35.57901.9031




































Fum. Rate Given, Unadjusted (League Avg = 3.0952%)
RankTeamVOLA (%)Actual Stat
1NE48.30801.6000
2IND45.10801.6990
3JAX30.85202.1403
4SD30.47702.1519
5ATL28.39202.2164
6TB27.39802.2472
7SEA22.80102.3895
8DAL21.80302.4204
9CIN19.83202.4814
10PIT19.23102.5000
11NYJ16.13602.5958
12BUF12.32602.7137
13PHI9.38092.8049
14KC8.05062.8461
15CLE6.96742.8796
16NO0.94343.0660
17STL-0.21003.1017
18GB-2.23953.1646
19CAR-5.03153.2510
20NYG-5.26323.2581
21HOU-7.00643.3121
22MIN-7.55443.3291
23ARI-11.40603.4483
24MIA-12.15003.4713
25TEN-16.32303.6005
26BAL-22.11303.7797
27DEN-23.15503.8119
28WAS-33.81904.1420
29CHI-35.98904.2092
30DET-47.44504.5638
31SF-65.07605.1095
32OAK-67.72805.1916




































Fum. Rate Taken, Unadjusted (League Avg = 3.0952%)
RankTeamVOLA (%)Actual Stat
1DET42.48204.4102
2MIN36.23704.2169
3DEN35.11204.1820
4CHI27.22603.9379
5SEA25.19203.8750
6TB23.78403.8314
7PIT19.65803.7037
8CAR16.35403.6014
9NO13.73003.5202
10BUF12.34103.4772
11TEN10.81803.4301
12SD9.58643.3920
13DAL9.37503.3854
14WAS8.38713.3548
15IND8.09273.3457
16NE7.69233.3333
17CIN5.86263.2767
18NYG5.30543.2595
19STL-2.34453.0227
20HOU-4.15522.9666
21ARI-7.57752.8607
22MIA-16.75302.5767
23JAX-17.71502.5469
24ATL-19.42302.4941
25OAK-19.75902.4836
26KC-22.68902.3930
27CLE-25.86402.2947
28GB-27.25402.2517
29PHI-31.26002.1277
30SF-37.58701.9318
31NYJ-41.96201.7964
32BAL-49.71601.5564




































Rush offense, Adjusted (League Avg = 4.0326)
RankTeamVOLA (%)Actual Stat
1MIN27.32505.1345
2PHI16.99304.7178
3NYG13.27704.5680
4JAX13.19904.5648
5DEN11.96004.5149
6CLE9.92524.4328
7SF7.71534.3437
8DAL5.26204.2448
9TB3.94104.1915
10PIT3.66974.1806
11ATL2.73874.1430
12CAR1.98094.1125
13GB1.23914.0826
14NE0.57034.0556
15BUF0.25544.0429
16SD-0.56334.0099
17STL-1.13663.9867
18SEA-1.85673.9577
19DET-2.62713.9266
20OAK-2.68133.9245
21MIA-3.09293.9079
22CIN-4.27733.8601
23NYJ-4.88783.8355
24NO-5.34703.8170
25WAS-5.46723.8121
26ARI-6.76923.7596
27TEN-6.86373.7558
28IND-7.01573.7497
29HOU-9.25233.6595
30BAL-17.73403.3174
31CHI-20.98603.1863
32KC-23.25403.0948




































Rush defense, Adjusted (League Avg = 4.0326)
RankTeamVOLA (%)Actual Stat
1BAL28.36102.8889
2MIN22.24503.1355
3PIT19.90803.2298
4WAS11.50803.5685
5NYG7.83463.7166
6IND6.75173.7603
7CAR6.04223.7889
8SF5.55843.8084
9PHI4.86293.8365
10GB4.19483.8634
11DAL4.16123.8648
12TB3.13383.9062
13TEN1.05143.9902
14ARI0.74624.0025
15CHI-0.33734.0462
16SEA-0.36094.0471
17SD-0.91004.0693
18DET-1.47814.0922
19NO-1.77434.1041
20JAX-3.90564.1901
21NYJ-3.98964.1935
22ATL-4.17894.2011
23STL-4.90664.2304
24KC-5.48094.2536
25BUF-5.51604.2550
26HOU-7.25514.3252
27CIN-7.35244.3291
28NE-10.25604.4462
29MIA-11.80804.5088
30DEN-12.39504.5324
31CLE-16.52604.6990
32OAK-18.29004.7701




































Pass offense, Adjusted (League Avg = 6.0498)
RankTeamVOLA (%)Actual Stat
1NE27.85307.7349
2DAL22.36107.4026
3GB18.88607.1924
4IND16.43407.0440
5HOU14.76006.9428
6CIN12.66006.8157
7JAX10.81106.7039
8DEN8.36186.5557
9NO7.89646.5275
10ARI7.53656.5058
11CLE6.02986.4146
12WAS5.00806.3528
13TB3.56056.2652
14DET1.09256.1159
15SEA1.03826.1126
16PHI0.77816.0969
17PIT-0.19616.0379
18SD-0.70726.0070
19TEN-3.47095.8398
20MIN-4.75395.7622
21NYG-6.70855.6440
22BUF-6.72475.6430
23CHI-7.35035.6051
24ATL-9.83925.4546
25NYJ-10.23505.4306
26OAK-11.76605.3380
27STL-11.76605.3380
28MIA-15.19505.1305
29KC-15.36105.1205
30BAL-15.58405.1070
31CAR-15.76105.0963
32SF-33.01104.0527




































Pass defense, Adjusted (League Avg = 6.0498)
RankTeamVOLA (%)Actual Stat
1TEN15.91905.0867
2PIT15.18705.1310
3IND13.90305.2087
4TB12.11805.3167
5WAS11.71005.3414
6NE10.18005.4339
7DAL8.48155.5367
8NYG7.47725.5975
9SD7.26595.6102
10PHI4.69905.7655
11JAX4.39475.7839
12KC2.99355.8687
13SEA2.86295.8766
14CAR1.82535.9394
15GB-0.94446.1069
16CHI-1.81116.1594
17BUF-2.78656.2184
18CLE-3.66326.2714
19DEN-4.17126.3022
20HOU-4.25106.3070
21MIN-4.25986.3075
22SF-4.30136.3100
23NYJ-5.81306.4015
24DET-6.11676.4199
25ARI-6.98666.4725
26MIA-7.24536.4881
27ATL-7.71356.5165
28STL-8.92626.5898
29BAL-10.79006.7026
30OAK-11.02506.7168
31CIN-14.40806.9215
32NO-19.48607.2287




































Sack rate made, Adjusted (League Avg = 6.0353%)
RankTeamVOLA (%)Actual Stat
1NE39.67308.4297
2KC36.47008.2364
3NYG32.81808.0160
4CHI28.29007.7427
5DAL27.46207.6928
6TB25.64607.5832
7PIT20.14207.2510
8PHI18.91607.1770
9TEN17.19107.0729
10MIA16.67907.0420
11BAL16.52907.0329
12SD10.76706.6852
13SEA9.90826.6333
14JAX3.13626.2246
15IND0.09096.0408
16OAK-4.77625.7471
17DEN-6.48605.6439
18HOU-6.70015.6310
19DET-8.31385.5336
20NYJ-8.61185.5156
21STL-9.55895.4584
22GB-9.89285.4383
23ARI-10.31905.4126
24NO-12.10605.3047
25SF-12.16905.3009
26WAS-15.33505.1098
27ATL-21.66204.7280
28MIN-21.97204.7093
29BUF-32.43904.0775
30CLE-35.66603.8828
31CAR-36.15103.8535
32CIN-39.07603.6770




































Sack rate allowed, Adjusted (League Avg = 6.0353%)
RankTeamVOLA (%)Actual Stat
1NO63.68102.1920
2CIN55.79202.6681
3GB49.44203.0513
4NE45.18203.3085
5CLE41.30203.5426
6IND33.94503.9866
7HOU33.15304.0344
8ARI28.45704.3179
9SD26.31704.4470
10DAL25.00104.5264
11BUF22.19504.6958
12WAS21.02604.7663
13NYG16.37905.0468
14DEN3.39925.8302
15CAR-4.94426.3337
16JAX-5.93886.3938
17SEA-7.16796.4679
18TEN-7.82926.5079
19CHI-8.91046.5731
20MIA-12.45306.7869
21BAL-17.45107.0886
22MIN-17.85407.1129
23PHI-19.02707.1837
24TB-26.23407.6187
25DET-28.65507.7648
26ATL-31.34307.9270
27STL-32.28407.9838
28OAK-33.48508.0563
29KC-46.76608.8578
30NYJ-52.06509.1776
31PIT-61.68209.7581
32SF-67.929010.1351




































Third down % converted, Adjusted (League Avg = 39.5132%)
RankTeamVOLA (%)Actual Stat
1IND24.118049.0430
2NE18.040046.6414
3PIT17.415046.3944
4CIN15.738045.7318
5NO15.437045.6128
6GB12.214044.3393
7JAX11.906044.2176
8HOU11.485044.0513
9PHI11.103043.9003
10DAL9.416143.2338
11NYG9.293043.1852
12CLE4.022541.1026
13WAS3.706940.9779
14SD2.117640.3499
15DEN1.680840.1773
16TEN-0.126439.4632
17NYJ-3.865837.9857
18MIA-4.544337.7176
19TB-5.526337.3296
20BAL-5.900737.1816
21SEA-7.322436.6199
22STL-7.895136.3936
23MIN-8.695836.0772
24ARI-8.899835.9966
25CAR-9.570235.7317
26OAK-10.376035.4133
27ATL-10.730035.2734
28CHI-11.389035.0130
29DET-12.347034.6345
30BUF-15.552033.3681
31KC-15.875033.2405
32SF-21.151031.1558




































Third down % allowed, Adjusted (League Avg = 39.5132%)
RankTeamVOLA (%)Actual Stat
1KC21.960030.8361
2NE15.653033.3282
3CHI14.723033.6957
4NYG10.899035.2066
5GB10.452035.3833
6BAL8.928535.9853
7WAS8.159236.2892
8ATL6.614936.8994
9CLE6.388236.9890
10SEA6.295537.0256
11PHI6.259537.0399
12JAX2.330138.5925
13OAK1.239239.0235
14SD0.676739.2458
15DAL0.592839.2790
16TB-0.201439.5928
17STL-0.225339.6022
18HOU-1.444140.0838
19TEN-2.095540.3412
20PIT-2.971840.6874
21NYJ-3.298740.8166
22CAR-3.718840.9826
23SF-4.327341.2230
24MIN-6.238841.9783
25BUF-6.953142.2606
26ARI-7.534342.4902
27DEN-9.455743.2494
28CIN-10.795043.7786
29NO-11.064043.8849
30IND-12.073044.2836
31MIA-16.335045.9677
32DET-21.144047.8679




































Int. Rate Given, Adjusted (League Avg = 2.9542%)
RankTeamVOLA (%)Actual Stat
1NE57.94901.2423
2TB47.37901.5545
3JAX44.80901.6304
4IND36.92801.8633
5WAS33.04601.9779
6BAL26.30202.1772
7PHI25.07202.2135
8SEA21.09002.3311
9ATL18.10002.4195
10DEN16.12402.4778
11GB12.04002.5985
12MIA10.42402.6462
13PIT7.82412.7230
14NO4.33822.8260
15SD1.00882.9244
16BUF0.68302.9340
17KC0.17302.9491
18HOU-2.77523.0362
19MIN-9.80003.2437
20CIN-10.91303.2766
21CAR-14.67703.3878
22TEN-15.44603.4105
23SF-16.56603.4436
24NYJ-18.46203.4996
25DET-20.39503.5567
26CLE-20.76603.5676
27CHI-28.64203.8003
28NYG-32.66703.9192
29DAL-34.64303.9776
30OAK-39.32104.1158
31ARI-44.07904.2563
32STL-54.71104.5704




































Int. Rate Taken, Adjusted (League Avg = 2.9542%)
RankTeamVOLA (%)Actual Stat
1IND77.04105.2301
2SD64.44204.8579
3MIA42.62204.2133
4OAK38.68204.0969
5JAX24.12303.6668
6CIN23.53203.6493
7TEN16.20103.4328
8NE14.66703.3875
9STL14.41703.3801
10NYJ11.19603.2849
11TB10.60503.2675
12BAL6.54793.1476
13DAL4.64863.0915
14GB1.55993.0003
15BUF-0.27732.9460
16NO-0.89972.9276
17ATL-4.03542.8350
18SEA-5.61732.7882
19CLE-7.08632.7448
20KC-9.55112.6720
21CHI-12.03102.5988
22ARI-14.27402.5325
23DEN-15.67502.4911
24CAR-16.41702.4692
25DET-20.22802.3566
26NYG-23.72802.2532
27MIN-25.34702.2054
28SF-26.00702.1859
29PIT-29.80902.0736
30WAS-31.78002.0153
31PHI-34.00301.9497
32HOU-41.78501.7198




































Fum. Rate Given, Adjusted (League Avg = 3.0952%)
RankTeamVOLA (%)Actual Stat
1NE48.38101.5977
2IND42.81901.7699
3ATL39.33701.8777
4JAX33.21702.0671
5SD31.47302.1211
6TB24.30302.3430
7DAL24.23502.3451
8KC17.69602.5475
9PHI14.92402.6333
10NYJ13.20602.6865
11SEA12.37702.7121
12GB11.66002.7343
13BUF8.13422.8435
14PIT3.21212.9958
15NO2.66083.0129
16CIN2.12693.0294
17CLE-2.38373.1690
18CAR-3.65613.2084
19STL-6.85663.3075
20NYG-7.40603.3245
21HOU-8.49263.3581
22MIN-11.18103.4413
23ARI-16.83003.6162
24BAL-17.85703.6480
25DEN-18.38103.6642
26CHI-19.60803.7022
27MIA-19.91303.7116
28TEN-22.94103.8053
29DET-35.22504.1855
30WAS-35.37004.1900
31SF-56.42304.8417
32OAK-58.64804.9105




































Fum. Rate Taken, Adjusted (League Avg = 3.0952%)
RankTeamVOLA (%)Actual Stat
1CAR29.09303.9957
2TB28.49103.9771
3DET26.73003.9226
4PIT24.02903.8390
5NE22.99603.8070
6DEN22.67703.7971
7BUF20.32003.7242
8SEA19.03703.6845
9TEN18.20803.6588
10MIN17.76803.6452
11CHI15.59303.5779
12NO15.11603.5631
13DAL14.67903.5496
14HOU11.06303.4377
15WAS9.44953.3877
16IND6.67513.3018
17CIN0.40713.1078
18SD-0.61643.0762
19STL-0.91383.0670
20NYG-2.15913.0284
21MIA-8.02492.8468
22ARI-9.06412.8147
23ATL-12.29102.7148
24OAK-18.07002.5359
25JAX-21.10302.4421
26KC-22.11602.4107
27CLE-26.01802.2899
28SF-31.06102.1338
29GB-33.09902.0707
30PHI-36.94301.9518
31NYJ-39.35001.8773
32BAL-45.68101.6813

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