Week 5 Efficiency Rankings

NFL team efficiency rankings are back for 2008. The ratings are listed below in terms of generic win probability. The GWP is the probability a team would beat the league average team at a neutral site. Each team's opponent's average GWP is also listed, which can be considered to-date strength of schedule, and all ratings include adjustments for opponent strength.

Offensive rank (ORANK) is based on offensive generic win probability is based on each team's offensive efficiency stats only. In other words, it's the team's GWP assuming it had a league-average defense. DRANK is is a team's generic win probability rank assuming it had a league-average offense.

GWP is based on a logistic regression model applied to current team stats. The model includes offensive and defensive passing and running efficiency, offensive turnover rates, and team penalty rates. A full explanation of the methodology can be found here. This year, however, I've made one important change based on research that strongly indicates that defensive interception rates are highly random and not consistent throughout the year. Accordingly, I've removed them from the model and updated the weights of the remaining stats.






































RANKTEAMLAST WKGWPOpp GWPORANKDRANK
1 WAS10.860.7014
2 NYG30.840.4223
3 SD20.790.64413
4 PHI50.760.6167
5 CAR40.750.5451
6 MIA180.740.61820
7 DAL60.700.49311
8 ARI80.680.641017
9 CHI120.670.5292
10 NYJ140.640.642010
11 DEN150.590.50728
12 BUF90.580.412314
13 NO70.580.581315
14 PIT130.570.42175
15 MIN100.560.551412
16 OAK160.520.542216
17 TB190.520.55169
18 TEN110.510.40248
19 ATL200.500.391124
20 IND210.470.491222
21 BAL230.440.39256
22 NE270.440.492723
23 GB260.420.481819
24 SF170.410.413018
25 JAX220.390.521527
26 HOU250.380.501926
27 SEA240.330.532631
28 CIN290.290.542821
29 STL280.270.632130
30 KC300.200.573229
31 CLE310.160.502925
32 DET320.130.513132


To give everyone an insight into why the rankings are what they are, here are the team efficiency stats.




















































TEAMOPASSORUNOINTRATEOFUMRATEDPASSDRUNDINTRATEPENRATE
ARI7.13.30.0220.0256.54.10.0210.36
ATL5.95.50.0230.0046.34.60.0300.34
BAL4.93.80.0380.0224.12.80.0600.55
BUF6.73.70.0210.0285.34.00.0180.25
CAR6.93.80.0140.0204.63.80.0190.50
CHI6.23.80.0260.0184.93.70.0280.39
CIN4.53.30.0430.0355.94.50.0140.37
CLE4.03.50.0510.0246.74.10.0570.52
DAL8.05.00.0310.0325.73.90.0060.51
DEN7.64.50.0210.0237.15.20.0120.28
DET4.74.40.0470.0248.95.00.0000.35
GB6.84.00.0240.0345.75.10.0540.66
HOU5.74.40.0420.0396.84.50.0180.15
IND6.13.60.0320.0066.24.90.0200.31
JAX5.44.00.0270.0087.14.20.0310.41
KC3.84.60.0490.0307.65.00.0220.23
MIA6.54.30.0080.0196.73.30.0090.30
MIN5.34.10.0180.0246.32.80.0230.41
NE5.53.70.0250.0186.14.90.0470.22
NO8.23.20.0310.0386.34.50.0220.60
NYG7.25.80.0080.0094.43.70.0160.48
NYJ6.43.80.0390.0216.63.10.0340.34
OAK5.64.80.0100.0416.14.00.0390.50
PHI6.73.50.0160.0205.63.30.0260.34
PIT5.83.70.0220.0294.52.80.0360.49
SD7.83.80.0290.0146.14.40.0250.27
SF6.24.60.0430.0326.13.80.0430.34
SEA4.74.70.0320.0107.24.60.0080.38
STL4.84.00.0250.0308.24.70.0090.43
TB5.15.30.0390.0086.23.70.0480.49
TEN6.03.60.0360.0204.63.70.0590.37
WAS6.34.40.0000.0006.04.10.0290.30
AVG6.04.10.0280.0226.14.10.0280.39

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11 Responses to “Week 5 Efficiency Rankings”

  1. Josh Engleman says:

    Anytime the Redskins are at the top of a set of rankings, I should just leave well enough alone, but I'm curious as to how much a few turnover will hurt them. With them having fumble and interception rates at zero, even with regression to the mean factored in, they are still leaps and bounds ahead of the pack. Do you see a big drop after they pick up a few of each?

    Also, I'm not sure if you ever click my link, but I put up soccer probabilities last week and I realized I had no idea how to grade the results. I'm not a big time stats whiz so I was wondering if you had any thoughts on how to determine the quality of the picks.

  2. Brian Burke says:

    Josh-The Redskins have played very well against the most difficult schedule by far. They'll eventually have some turnovers and lose some games, but if you're a fan there's every reason to be optimistic. Their problem is their division.

    For grading probabilities, one method is to use squared errors. For example, if you predict a .90/.10 game and get it wrong, that's a .9-0=.9 error. If you predict a .6/.4 game and get it right, that's a 1-.6=.4 error. You square all the errors then add them up, then take the square root. There's no "good" or "bad" error number. It's all relative depending on how predictable your subject is. It's useful for comparing various models. The idea is not only to identify the favorite, but to estimate the confidence level in the model.

  3. Josh Engleman says:

    Brian,

    I guess I should have been a bit clearer. My problem with the soccer matches is the fact that there are ties. Since the probabilities are something like 40/35/25, is it still the same situation? I'm guessing it just makes the error higher, which isn't necessarily bad.

  4. Brian says:

    Question on FUMRATE. I noticed that Washington has a FUMRATE of 0. In week 2, however, Antwaan Randle-El fumbled a punt. Does this efficiency stat only account for fumbles that occur on offense and not on special teams?

  5. Brian Burke says:

    Yes, it accounts for all fumbles. But technically the Randle-El play was ruled a muffed punt and not a fumble because he was judged to not have possession.

  6. SportsPicksSystem says:

    The official boxscore on NFL.com states that the redskins fumbled the ball once. http://www.nfl.com/gamecenter/boxscore?game_id=29551&displayPage=tab_box_score&season=2008&week=REG2

  7. Anonymous says:

    I was curious about the following statement: "The GWP is the probability a team would beat the league average team at a neutral site." Is there a way for your audience to tweek these numbers if a team is playing a little bit better of a team then average? Not necessarily a good team but a team that's just better then the average

  8. Canadian Elvis says:

    I absolutely love this site. Your work brings a bit of science to a field that feels like it's filled with carnival con men.

    Your site has caused me to start diving into learning more about regressions for the first time since my stats classes back at school. Would you have any suggestions on software to use for working on this type of problem. I've started playing around with R and elrm but was interested to see if there was anything else you would suggest.

    Thanks again for the great content.

  9. SportsPicksSystem says:

    You can use R which can also be used into Excel. You also have Gretl.

  10. Josh Engleman says:

    Anonymous,

    To find out the probability for Team A playing Team B, you would take both teams win% and put them into the log5 equation.

    (A*(1-B)) / ((A*(1-B))+(B*(1-A)))

    Example:

    The Saints (58%) vs. The Raiders (52%)

    (.58*(1-.52)) / ((.58*(1-.52)) + (.52*(1-.58)))

    (.2784) / ((.2784)+(.2184))

    =.5604

    Saints win 56% of the time.

  11. Brian Burke says:

    Yup. What Josh said. But I'll have game probabilities for week 6 up shortly so you don't have to do the math. But you can do hypothetical match-ups using that method.

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