Team Efficiency Rankings - Week 6

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:


RANK
TEAM
LAST WK
GWP
Opp GWP
O RANK
D RANK
1
IND
1
0.86
0.49
1
2
2
NYG
4
0.78
0.35
4
8
3
NO
2
0.77
0.48
3
7
4
DEN
3
0.74
0.40
7
3
5
PHI
5
0.71
0.39
10
10
6
PIT
6
0.67
0.47
6
16
7
DAL
11
0.66
0.46
2
29
8
ATL
19
0.62
0.42
5
30
9
NYJ
8
0.55
0.54
23
5
10
CHI
12
0.55
0.49
21
6
11
GB
16
0.54
0.43
8
20
12
TEN
9
0.53
0.61
18
4
13
JAC
7
0.52
0.56
13
18
14
NE
18
0.50
0.55
12
13
15
SD
15
0.49
0.43
9
27
16
ARI
14
0.49
0.56
16
11
17
MIN
20
0.49
0.33
15
23
18
CIN
22
0.48
0.53
17
12
19
BAL
10
0.48
0.38
14
28
20
SEA
24
0.47
0.51
19
15
21
HOU
13
0.46
0.45
11
32
22
WAS
21
0.46
0.37
22
21
23
MIA
25
0.42
0.58
20
14
24
SF
17
0.40
0.45
27
9
25
BUF
23
0.37
0.42
28
22
26
CAR
26
0.34
0.61
30
1
27
DET
27
0.28
0.59
24
26
28
KC
28
0.23
0.56
29
24
29
TB
29
0.22
0.60
26
25
30
STL
32
0.21
0.47
25
31
31
CLE
30
0.20
0.51
31
17
32
OAK
31
0.17
0.54
32
19




TEAM
OPASS
ORUN
OINT%
OFUM%
DPASS
DRUN
DINT%
PENRATE
ARI
6.4
3.1
2.4
2.1
7.3
2.9
1.9
0.42
ATL
7.7
3.5
1.6
1.5
5.8
4.9
2.0
0.43
BAL
6.5
4.9
2.7
0.8
7.0
3.0
4.4
0.55
BUF
5.2
4.6
4.0
0.4
5.1
4.7
2.3
0.52
CAR
5.1
3.8
6.8
2.6
5.5
5.0
1.8
0.31
CHI
6.2
3.8
3.9
1.1
5.4
3.8
1.9
0.40
CIN
5.9
4.4
3.6
1.6
6.0
4.2
2.3
0.38
CLE
4.1
3.8
5.1
0.8
5.8
5.1
1.2
0.35
DAL
7.5
5.9
2.4
0.4
6.5
4.2
1.1
0.53
DEN
6.9
4.6
0.6
1.1
4.9
3.3
3.8
0.35
DET
5.4
3.7
3.7
1.5
7.2
4.9
1.9
0.48
GB
6.6
4.2
0.8
0.0
6.8
3.5
5.6
0.46
HOU
7.3
3.0
2.2
2.0
6.5
5.2
1.2
0.31
IND
8.9
3.3
2.2
1.2
4.6
4.1
2.1
0.32
JAC
5.9
4.6
0.6
0.8
7.3
3.8
2.2
0.34
KC
4.7
3.5
1.3
2.0
7.5
4.4
1.2
0.44
MIA
5.2
4.8
2.1
0.7
7.3
3.4
2.1
0.40
MIN
6.5
4.1
1.3
1.1
6.1
3.8
3.6
0.30
NE
6.2
3.6
1.0
0.4
6.1
4.4
1.2
0.38
NO
7.5
5.0
1.6
1.3
5.2
3.7
6.6
0.42
NYG
8.2
4.5
1.3
1.1
3.7
4.8
4.0
0.38
NYJ
5.8
4.1
3.7
1.2
5.4
4.2
2.3
0.38
OAK
3.9
3.3
3.3
1.5
7.2
4.3
2.8
0.44
PHI
7.1
4.2
2.8
1.0
4.6
3.7
6.6
0.50
PIT
7.4
3.9
2.9
0.7
5.5
3.8
1.1
0.46
SD
7.4
2.7
2.0
0.0
6.6
4.6
3.2
0.37
SF
5.0
4.2
1.4
0.9
5.9
3.3
3.2
0.44
SEA
5.8
3.7
2.0
1.4
5.9
4.8
1.2
0.27
STL
4.8
4.4
1.9
1.7
7.7
4.0
2.1
0.53
TB
4.8
4.2
3.7
1.8
8.1
4.7
3.1
0.37
TEN
5.4
5.3
3.7
0.4
7.1
2.8
2.1
0.40
WAS
6.3
3.7
3.4
0.8
5.7
4.0
2.1
0.38
Avg
6.2
4.1
2.6
1.1
6.2
4.1
2.6
0.41

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10 Responses to “Team Efficiency Rankings - Week 6”

  1. Anonymous says:

    Hi Brian. Opp GWP is that future schedule or past?

    Juri

  2. Bruno says:

    this is, but do u think you could do some more with fantasy football?

  3. Anonymous says:

    Interesting to see the Titans (0-5) ahead of the Vikings (5-0).

  4. Anonymous says:

    Two factors -- close games (the Titans could easily be 3-2) and strength of schedule.

  5. Anonymous says:

    "Two factors -- close games (the Titans could easily be 3-2)"

    Pretty misleading thing to say. The Titans have a -55 point differential. I don't think anybody disagrees that they are running bad, but they'd need an insane amount of good luck to be 3-2, given their last two losses have been utter blowouts. Every Efficiency Ranking formula like this will have certain data points that just don't make sense. This is one of them.

  6. Andy says:

    I'm a little surprised that the correlation between rank and previous opponent quality is so high. The correlation is p=.36 and is significant. The correlation between own GWP and opponent GWP is similarly negative and significant. Higher ranked teams are playing worse teams than lower ranked teams, at least according to your metric.

    Perhaps I'm misunderstanding the methodology but isn't your construction attempting to control for opponent quality in measuring efficiency? Shouldn't the expected correlation between your efficiency measure and opponent quality thus be 0, at least in expectation? If so, what should we make of this correlation - a problem with the methodology or just noise?

  7. Brian Burke says:

    Andy-Very good analysis. I'll have to check on the routine that does the opponent adjustment and make sure it's working properly. I've built a new tool this year that does all this stuff automatically so there may be some glitches.

  8. Brian Burke says:

    I looked everything over and ran some tests. I could do a few more passes to reduce the correlation slightly, but it won't change the rankings very much. There will always be some correlation because the sample of opponents is not random. A team can never play itself, so a good team has one less good team as a possible opponent and vice versa.

  9. FBO Ramburgler says:

    I regretfully don't understand why you rank Tennessee defense 4th, when they have allowed 7.1 yds per pass (among the worst) and 2.8 yds per carry (THE best, but small sample size). Their run defense is comparable to Arizona's run defense, in the fact that both have TERRIBLE pass defenses so running the ball is no more than a simple strategy to pull the safeties and cornerbacks in. Further explanation of the rankings would be much appreciated.

  10. Brian Burke says:

    Great question. It's due primarily to strength of opponent.

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