Efficiency Rankings - Week 10

The team rankings below are 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 offensive generic win probability, which 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, defensive interception rates, and team penalty rates. If you're scratching your head wondering why a team is ranked where it is, just scroll down to the second table to see the stats of all 32 teams.

Click on the table headers to sort.


RANKTEAMLAST WKGWPOpp GWPO RANKD RANK
1 SD10.810.4218
2 PIT30.800.5442
3 NYG20.790.4623
4 TEN40.710.5751
5 GB70.700.50610
6 PHI100.650.4974
7 KC60.610.49206
8 IND50.610.541312
9 MIA80.610.571915
10 BAL130.600.521613
11 NYJ120.580.50217
12 NO180.560.421411
13 HOU90.560.60328
14 MIN150.550.491517
15 CHI140.510.45279
16 NE110.510.561125
17 CLE220.510.551718
18 WAS170.480.512219
19 CIN200.470.522520
20 ATL190.450.491027
21 DAL160.450.58926
22 OAK210.410.461814
23 TB270.390.441230
24 DEN230.360.47831
25 SF240.350.442322
26 DET250.350.572421
27 BUF280.340.552829
28 JAC260.300.572632
29 STL300.290.393016
30 CAR290.280.49325
31 SEA310.220.472923
32 ARI320.200.463124

Below are each team's efficiency stats.


TEAMOPASSORUNOINT%OFUM%DPASSDRUNDINT%PENRATE
ARI4.74.34.71.26.64.43.10.42
ATL6.24.21.70.27.04.14.80.37
BAL6.63.62.30.96.04.23.10.38
BUF5.34.33.21.16.64.80.40.32
CAR4.33.65.32.55.53.84.10.39
CHI5.73.94.90.35.53.53.50.35
CIN6.03.72.51.26.34.43.70.36
CLE6.24.23.51.86.73.93.30.40
DAL6.63.64.00.07.04.42.20.52
DEN7.02.91.61.77.14.62.30.52
DET5.63.52.61.06.34.73.30.56
GB6.84.23.00.55.54.54.40.37
HOU6.55.12.60.27.64.01.70.33
IND6.73.71.10.95.95.12.30.36
JAC5.94.24.91.07.94.43.10.37
KC6.05.01.90.55.83.82.30.40
MIA6.23.93.91.26.43.82.00.24
MIN6.44.64.91.06.23.82.30.45
NE6.34.11.90.07.04.13.10.36
NO6.43.83.20.85.24.22.20.42
NYG7.04.74.11.65.03.53.60.43
NYJ6.04.72.01.75.83.31.80.56
OAK6.04.93.31.35.64.51.90.69
PHI6.35.11.40.75.53.94.50.63
PIT7.04.03.71.15.92.63.60.36
SD8.04.02.41.75.43.62.90.41
SF6.03.93.61.16.63.63.00.56
SEA5.03.63.50.06.64.02.00.47
STL5.13.62.70.25.54.32.70.44
TB6.24.11.90.86.65.05.50.40
TEN6.74.22.41.15.64.14.10.55
WAS6.04.12.81.16.14.62.60.38
Avg6.24.13.00.96.24.13.00.43

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10 Responses to “Efficiency Rankings - Week 10”

  1. Dave says:

    Good stuff. For some reason the headers only sort Descending when I click on them. I can't figure out how to make them Ascending.

  2. Brian Burke says:

    That happens to me too, but only on Firefox on my work computer. On all my other computers, it works normally.

  3. Dave says:

    ...Touché Mr Burke...

  4. David says:

    Isn't there any easy way to get to your weekly Win Probabilities from this chart? Like you take the GWP's for each team and make an adjustment for home field advantage.

    If team A were at home, would it be:

    Team A Win Chances = (GWPa*(.57/.50)) / (GWPa*(.57/.50)+GWPb*(.43/.50))

  5. Dave says:

    Never mind. I looked into it and it's a bit more complicated.

  6. Brian Burke says:

    David-Yes, and it's not too hard. Do a search for 'how the model works' in the site's search box above. That post should tell explain.

  7. Anonymous says:

    49ers at #25 is the best in the NFC West. The other 3 West teams make up 3 of the bottom 4 teams in the overall efficiency chart.

    One of these teams will make the playoffs and likely host a game against a superior NFC East wild card team, such as PHI or NYG. LOL.

  8. Anonymous says:

    Brian,

    I can imagine that the problem with yards per attempt is that some teams may get a 3 and out repeatedly, others might march halfway up the field and then punt repeatedly, and both still have 0 points, but the one which got halfway up the field will have a much higher efficiency.

    Have u ever thought of utilizing other variables which may account for such discrepancies. For example, I would think the number of punts or 4th downs per possesion (minus possessions ending in turnovers and end of halves)could be helpful. I was just curious about whether or not you have ever looked into the statistical significance of these stats.

  9. Brian Burke says:

    Dave-Sorting should be working now.

  10. Dave says:

    Thanks Brian, sorting is working great.

    Also- I tried to make a spreadsheet that replicates your Game Probabilities calculations based on your explanation here: http://www.advancednflstats.com/2009/01/how-model-works-detailed-example.html

    Although most of my answers are close to your published numbers on the Fifth Down, none of them are exact and I was wondering if you've changed the coefficients in your formula or if there is something else going on. The most egregious example is NYJ vs CLE, I kept getting NYJ as a 61%/39% favorite while you had CLE as a 53% favorite.

    Here are my calcs:
    CLE Logit = 0.46*6.2+0.25*4.2+-19.4*0.035+-19.4*0.018+-0.62*6.7+-0.25*3.9+-1.53*0.4 = -2.8672
    NYJ Logit = 0.46*6+0.25*4.7+-19.4*0.02+-19.4*0.017+-0.62*5.8+-0.25*3.3+-1.53*0.56 = -2.0606

    CLE GWP = e^(-.36+.72-2.8672+2.0606)/(1+e^(-.36+.72-2.8672+2.0606)) = 39%

    NYJ GWP e^(-.36-2.0606+2.8672)/(1+e^(-.36-2.0606+2.8672)) = 61%

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