Football


I was able to watch big chunks of four games this last weekend. I saw some of the Atlanta – New Orleans game, pretty close for a half. I saw Dallas – Minnesota, the Sunday night and Monday night games. All three of these were entertaining and competitive. In terms of good teams, PIT, KC and NO look good. None of the 3 loss teams have particularly good stats. TB and BAL still look good despite four losses.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
161        85     52.8      29.94        19.55     10.39

Calculated Pythagorean Exponent:  3.67


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PIT      8.0    10  10   0   0 100.0  87.8   8.86  12.40 -3.54
2     KC      11.5    10   9   1   0  90.0  81.6   9.91  10.70 -0.79
3     NO       4.5    10   8   2   0  80.0  73.9   9.05   7.30  1.75
4     GB       8.0    10   7   3   0  70.0  65.7   4.80   5.00 -0.20
5     SEA      6.0    10   7   3   0  70.0  59.3   3.33   3.10  0.23
6     IND      6.0    10   7   3   0  70.0  73.8   4.18   6.80 -2.62
7     LA       5.0    10   7   3   0  70.0  70.3   4.59   5.10 -0.51
8     CLE      4.0    10   7   3   0  70.0  41.6  -3.27  -2.30 -0.97
9     BUF      3.0    10   7   3   0  70.0  52.4   0.84   0.70  0.14
10    TEN      2.5    10   7   3   0  70.0  56.8   1.57   2.00 -0.43
11    TB       7.0    11   7   4   0  63.6  70.3   8.19   6.09  2.10
12    BAL      8.0    10   6   4   0  60.0  76.2   7.30   7.30 -0.00
13    MIA      5.5    10   6   4   0  60.0  72.7   4.44   6.20 -1.76
14    LV       4.5    10   6   4   0  60.0  53.3   3.83   1.00  2.83
15    ARI      2.5    10   6   4   0  60.0  66.5   3.02   4.90 -1.88
16    CHI     -1.0    10   5   5   0  50.0  41.8  -0.36  -1.80  1.44
17    MIN     -1.0    10   4   6   0  40.0  45.3  -1.60  -1.40 -0.20
18    DEN     -3.5    10   4   6   0  40.0  27.9  -4.32  -6.10  1.78
19    NE      -4.0    10   4   6   0  40.0  38.3  -2.02  -2.90  0.88
20    SF      -4.5    10   4   6   0  40.0  51.6   0.85   0.40  0.45
21    DET     -5.0    10   4   6   0  40.0  29.7  -5.65  -6.00  0.35
22    CAR     -3.0    11   4   7   0  36.4  43.4   1.03  -1.73  2.76
23    PHI     -3.5    10   3   6   1  35.0  37.1  -4.43  -3.40 -1.03
24    ATL     -2.5    10   3   7   0  30.0  42.1  -2.41  -2.30 -0.11
25    NYG     -2.5    10   3   7   0  30.0  33.2  -4.60  -4.10 -0.50
26    LAC     -3.0    10   3   7   0  30.0  45.5  -0.99  -1.30  0.31
27    WAS     -3.0    10   3   7   0  30.0  38.6  -4.92  -2.70 -2.22
28    DAL     -6.0    10   3   7   0  30.0  24.8  -8.44  -8.30 -0.14
29    HOU     -6.5    10   3   7   0  30.0  34.0  -3.79  -4.50  0.71
30    CIN     -3.5    10   2   7   1  25.0  29.5  -6.12  -5.70 -0.42
31    JAX     -9.0    10   1   9   0  10.0  19.4  -9.25  -9.60  0.35
32    NYJ    -14.0    10   0  10   0   0.0   7.0 -13.62 -15.30  1.68

I caught a bit of New England Baltimore and most of Minnesota – Chicago, both worth watching. For those wanting to use the data below to figure out the best team in the NFL, I’d say it gives you about 5 candidates. Kansas City looks like the best of these. Pythagoreans favor Pittsburgh, and the other three are some mix of New Orleans, Tampa Bay and Baltimore. Green Bay lags a little behind and Miami is rising with a bullet.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
147        76     51.7      30.21        19.66     10.55

Calculated Pythagorean Exponent:  3.83


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PIT      7.0     9   9   0   0 100.0  85.4   7.72  11.11 -3.39
2     KC      14.0     9   8   1   0  88.9  84.7   9.94  11.44 -1.50
3     GB       9.0     9   7   2   0  77.8  69.3   5.79   5.89 -0.10
4     NO       3.0     9   7   2   0  77.8  71.6   8.98   6.44  2.53
5     TB      10.5    10   7   3   0  70.0  73.8   8.51   7.00  1.51
6     BUF      3.0    10   7   3   0  70.0  52.5   0.79   0.70  0.09
7     BAL     14.0     9   6   3   0  66.7  81.7   8.43   8.78 -0.35
8     MIA      8.0     9   6   3   0  66.7  77.4   6.40   7.67 -1.27
9     IND      8.0     9   6   3   0  66.7  76.8   4.19   7.22 -3.03
10    LA       7.0     9   6   3   0  66.7  72.4   3.69   5.33 -1.65
11    SEA      5.0     9   6   3   0  66.7  58.2   2.89   2.67  0.22
12    LV       5.0     9   6   3   0  66.7  55.4   3.43   1.56  1.87
13    ARI      3.0     9   6   3   0  66.7  71.2   3.67   6.22 -2.56
14    CLE      3.0     9   6   3   0  66.7  38.5  -3.88  -3.11 -0.77
15    TEN      2.0     9   6   3   0  66.7  55.5   0.22   1.56 -1.33
16    CHI     -1.0    10   5   5   0  50.0  41.5  -0.41  -1.80  1.39
17    MIN     -1.0     9   4   5   0  44.4  45.6  -0.35  -1.22  0.87
18    NE      -3.0     9   4   5   0  44.4  39.6  -1.05  -2.44  1.40
19    DET     -4.0     9   4   5   0  44.4  34.9  -3.85  -4.44  0.60
20    SF      -4.5    10   4   6   0  40.0  51.6   1.07   0.40  0.67
21    PHI     -2.0     9   3   5   1  38.9  37.5  -4.39  -3.22 -1.17
22    ATL     -1.0     9   3   6   0  33.3  46.9  -2.26  -0.89 -1.37
23    DEN     -5.0     9   3   6   0  33.3  23.3  -6.20  -7.56  1.36
24    NYG     -2.5    10   3   7   0  30.0  32.5  -5.13  -4.10 -1.03
25    CAR     -3.5    10   3   7   0  30.0  35.6  -0.10  -3.90  3.80
26    CIN     -3.0     9   2   6   1  27.8  31.5  -5.10  -5.11  0.01
27    LAC     -3.0     9   2   7   0  22.2  42.3  -0.15  -2.11  1.97
28    WAS     -3.0     9   2   7   0  22.2  32.4  -6.06  -4.22 -1.84
29    DAL     -7.0     9   2   7   0  22.2  20.6  -9.97  -9.56 -0.42
30    HOU     -7.0     9   2   7   0  22.2  29.2  -4.49  -5.78  1.28
31    JAX     -8.0     9   1   8   0  11.1  23.5  -8.16  -8.00 -0.16
32    NYJ    -18.0     9   0   9   0   0.0   4.5 -14.16 -16.33  2.18

Of the games that had an effect on 9th week stats, probably the biggest was Saints-Bucs. The Saints blowout took the Bucs out of the ‘statistical darling’ category. Baltimore seems more darling now than anyone else.

In terms of COVID effects, the lack of fans has gutted the home field advantage. Yes, it has been smaller than the traditional 60% for many years, but it has not been effectively zero, usually going 52% or more annually.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
133        65     48.9      30.41        19.90     10.50

Calculated Pythagorean Exponent:  3.79


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PIT      6.0     8   8   0   0 100.0  80.7   6.91   9.25 -2.34
2     KC      14.0     9   8   1   0  88.9  84.5   9.96  11.44 -1.49
3     BUF      3.0     9   7   2   0  77.8  53.6   0.24   1.00 -0.76
4     BAL     14.0     8   6   2   0  75.0  85.5  10.67  10.62  0.05
5     GB      11.5     8   6   2   0  75.0  69.3   6.76   6.12  0.63
6     SEA      6.0     8   6   2   0  75.0  61.2   3.40   3.88 -0.47
7     NO       3.0     8   6   2   0  75.0  68.0   7.71   5.50  2.21
8     TEN      2.5     8   6   2   0  75.0  63.3   2.12   3.88 -1.76
9     TB       7.0     9   6   3   0  66.7  68.8   6.66   5.22  1.44
10    MIA      7.0     8   5   3   0  62.5  77.2   5.81   7.62 -1.82
11    IND      6.0     8   5   3   0  62.5  73.0   2.93   6.00 -3.07
12    LA       5.5     8   5   3   0  62.5  71.2   2.95   5.12 -2.17
13    LV       4.5     8   5   3   0  62.5  45.3   0.93  -1.38  2.30
14    CLE      4.0     8   5   3   0  62.5  37.0  -3.92  -3.88 -0.04
15    ARI      3.5     8   5   3   0  62.5  73.0   3.94   6.75 -2.81
16    CHI      1.0     9   5   4   0  55.6  43.8  -0.08  -1.33  1.25
17    SF      -4.0     9   4   5   0  44.4  57.8   1.57   2.00 -0.43
18    PHI     -1.0     8   3   4   1  43.8  40.9  -2.76  -2.38 -0.38
19    MIN     -1.0     8   3   5   0  37.5  42.9  -0.59  -2.12  1.53
20    DEN     -3.5     8   3   5   0  37.5  30.2  -4.60  -5.38  0.78
21    NE      -4.0     8   3   5   0  37.5  35.6  -3.14  -3.50  0.36
22    DET     -5.0     8   3   5   0  37.5  32.1  -4.13  -5.38  1.24
23    ATL     -1.0     9   3   6   0  33.3  46.9  -1.67  -0.89 -0.78
24    CAR     -3.0     9   3   6   0  33.3  43.1   1.07  -1.78  2.84
25    CIN     -3.0     8   2   5   1  31.2  40.8  -3.01  -2.50 -0.51
26    LAC     -3.0     8   2   6   0  25.0  45.1  -0.16  -1.38  1.21
27    HOU     -7.5     8   2   6   0  25.0  29.8  -3.91  -6.12  2.22
28    WAS     -8.5     8   2   6   0  25.0  31.4  -5.85  -4.38 -1.47
29    NYG     -3.0     9   2   7   0  22.2  26.8  -6.37  -5.67 -0.71
30    DAL     -7.0     9   2   7   0  22.2  20.9  -9.93  -9.56 -0.37
31    JAX     -9.0     8   1   7   0  12.5  22.8  -9.03  -8.50 -0.53
32    NYJ    -18.0     9   0   9   0   0.0   4.7 -14.45 -16.33  1.88

I’m noticing the Pythagorean expectation getting smaller over time, and this is a side effect of the distribution of winning teams slowly becoming less bimodal and more like a bell curve. At week 7, we had 12 teams with 5 wins or more and 12 teams with 2 wins or less. That left 8 teams in the middle. Not exactly bell-like.

The best teams haven’t changed much, despite Tampa Bay’s near loss and Baltimore’s loss. The three worst teams at this time are clearly the Jets, the Cowboys, and the Jags. Of these teams, I know the Cowboys best so will speak a little about their issues.

I’ll start with the statement that Dick Nolan is a “good enough” DC and when he has the horses he puts up good defenses. The blogger falcfans has said that if Nolan has a pass rush, he’s okay. That would be consistent with the experience in 2013 and 2014, when losing John Abraham had a marked effect on the Falcons defense. It’s not consistent with Dallas, where the biggest issue is that the run defense has collapsed. The passing defense is giving up points but is in better shape overall. I’d point out that the most passing yards given up by Dallas so far is 295 yards. You’re not seeing 400+ yard blowouts as was seen the last time Dallas changed defensive philosophy back in 2013.

I suspect the issue is the character of a Tampa 2 front as opposed to a “multiple” defense of the kind Nolan prefers. Tampa fronts are the lightest in the game and it takes a special person to coach them. At this point, Nolan probably needs at least one real 2 gapper and perhaps 2. These are not interconvertible pieces. The former Dallas DE Pat Toomay is on Facebook, accessible, and has played both 3 and 4 man lines. He compares the 2 gap body type to spark plugs and the 1 gap type to greyhounds. Tom Landry, a 1 gap specialist, liked his lineman tall and lean.

If you think back to Mike Smith, the Falcons head coach who hired Nolan, he was a 4 man line guy, but his tackles in Jacksonville, when he was a DC there, were massive. John Henderson and Marcus Stroud were as big and tough as they come.

Now the further question is, can Dallas pay the price to close up the run gap? Typically, Dallas drafts from the outside in, as opposed to the inside out. I’m not sure of the whole cause (and notably they stopped doing this on the OL), though one side of me suspects that Jerry Jones likes his shiny new wide receivers. We’ll see in the 2021 draft what influence Mike McCarthy has on Dallas’s draft philosophy, as this is seriously in play here.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
119        60     50.4      30.34        19.66     10.67

Calculated Pythagorean Exponent:  3.55


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PIT      7.0     7   7   0   0 100.0  80.3   8.83   9.86 -1.03
2     KC      14.0     8   7   1   0  87.5  85.9  10.87  12.62 -1.75
3     SEA      7.0     7   6   1   0  85.7  66.0   5.29   5.86 -0.57
4     TB      10.5     8   6   2   0  75.0  80.7  10.07  10.25 -0.18
5     BUF      3.0     8   6   2   0  75.0  49.6  -1.38  -0.12 -1.25
6     BAL     14.0     7   5   2   0  71.4  82.1  10.34  10.14  0.20
7     GB       9.0     7   5   2   0  71.4  63.6   4.09   4.57 -0.48
8     IND      8.0     7   5   2   0  71.4  79.1   3.48   8.86 -5.37
9     ARI      4.0     7   5   2   0  71.4  76.3   4.35   8.14 -3.79
10    NO       3.0     7   5   2   0  71.4  54.0   2.83   1.29  1.55
11    TEN      2.0     7   5   2   0  71.4  60.7   1.34   3.43 -2.09
12    LA       5.5     8   5   3   0  62.5  70.0   3.15   5.12 -1.98
13    CLE      4.0     8   5   3   0  62.5  37.8  -3.81  -3.88  0.06
14    CHI      2.5     8   5   3   0  62.5  47.3   0.22  -0.62  0.84
15    MIA     11.0     7   4   3   0  57.1  78.7   6.13   8.29 -2.16
16    LV       4.0     7   4   3   0  57.1  42.8   0.15  -2.29  2.43
17    SF       2.0     8   4   4   0  50.0  65.8   3.67   4.38 -0.71
18    PHI     -1.0     8   3   4   1  43.8  41.5  -2.27  -2.38  0.10
19    DEN     -2.0     7   3   4   0  42.9  31.5  -3.01  -5.14  2.13
20    DET     -4.0     7   3   4   0  42.9  36.9  -3.76  -4.14  0.39
21    CAR     -3.5     8   3   5   0  37.5  43.4  -0.24  -1.75  1.51
22    CIN     -3.0     8   2   5   1  31.2  41.4  -2.97  -2.50 -0.47
23    MIN     -1.0     7   2   5   0  28.6  36.5  -2.80  -4.43  1.63
24    LAC     -3.0     7   2   5   0  28.6  47.1   0.32  -0.86  1.17
25    NE      -5.0     7   2   5   0  28.6  32.6  -1.33  -4.43  3.10
26    WAS    -14.0     7   2   5   0  28.6  31.8  -5.30  -4.57 -0.73
27    ATL     -2.5     8   2   6   0  25.0  43.9  -2.94  -1.88 -1.06
28    DAL     -9.0     8   2   6   0  25.0  21.6 -11.05 -10.12 -0.92
29    HOU     -8.0     7   1   6   0  14.3  27.9  -3.95  -7.29  3.33
30    JAX    -10.0     7   1   6   0  14.3  22.0  -9.34  -9.43  0.08
31    NYG     -3.5     8   1   7   0  12.5  24.6  -5.84  -6.75  0.91
32    NYJ    -19.0     8   0   8   0   0.0   3.6 -15.16 -18.00  2.84

There is only 1 undefeated team keft, as Pittsburgh defeated Tennessee this week. Arizona beat Seattle after Seattle at first had obtained a commanding lead. The Best one loss teams appear to be Kansas City and Baltimore, and the best two loss team, perhaps the best team in football, are the Tampa Bay Bucs.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
105        53     50.5      30.59        19.72     10.87

Calculated Pythagorean Exponent:  3.68


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PIT      8.0     6   6   0   0 100.0  83.4   7.48  10.83 -3.35
2     KC      14.0     7   6   1   0  85.7  82.5  11.12  10.71  0.40
3     BAL     15.5     6   5   1   0  83.3  88.0  10.41  12.50 -2.09
4     GB      11.5     6   5   1   0  83.3  68.7   7.24   6.33  0.90
5     SEA      6.0     6   5   1   0  83.3  64.8   3.12   5.17 -2.05
6     TEN      2.5     6   5   1   0  83.3  68.1   3.19   5.83 -2.64
7     TB      14.0     7   5   2   0  71.4  83.8  13.57  11.43  2.14
8     LA       8.0     7   5   2   0  71.4  78.4   3.74   7.43 -3.69
9     CLE      5.0     7   5   2   0  71.4  40.9  -4.46  -3.00 -1.46
10    ARI      4.0     7   5   2   0  71.4  77.1   4.73   8.14 -3.41
11    CHI      4.0     7   5   2   0  71.4  48.7   0.79  -0.29  1.07
12    BUF      3.0     7   5   2   0  71.4  47.9  -1.86  -0.57 -1.29
13    IND      6.0     6   4   2   0  66.7  75.8   0.34   7.00 -6.66
14    NO       3.0     6   4   2   0  66.7  53.1   5.17   1.00  4.17
15    SF       8.0     7   4   3   0  57.1  74.1   4.07   6.43 -2.35
16    MIA      7.5     6   3   3   0  50.0  78.2   4.26   7.83 -3.57
17    LV      -1.5     6   3   3   0  50.0  37.3   0.51  -4.33  4.85
18    DET     -1.5     6   3   3   0  50.0  44.9  -0.72  -1.50  0.78
19    CAR     -3.0     7   3   4   0  42.9  46.7   2.43  -0.86  3.29
20    PHI     -2.0     7   2   4   1  35.7  33.7  -3.85  -4.71  0.86
21    LAC     -3.0     6   2   4   0  33.3  47.0   2.00  -0.83  2.83
22    DEN     -3.5     6   2   4   0  33.3  26.6  -3.15  -6.17  3.02
23    NE      -5.5     6   2   4   0  33.3  31.0  -1.34  -4.67  3.32
24    DAL     -7.0     7   2   5   0  28.6  23.4 -11.08  -9.57 -1.50
25    WAS    -14.0     7   2   5   0  28.6  31.2  -5.80  -4.57 -1.23
26    CIN     -3.0     7   1   5   1  21.4  34.5  -5.79  -4.43 -1.36
27    MIN     -5.0     6   1   5   0  16.7  31.3  -5.10  -6.17  1.06
28    ATL     -4.0     7   1   6   0  14.3  39.3  -3.76  -3.29 -0.48
29    NYG     -4.0     7   1   6   0  14.3  21.3  -8.09  -7.43 -0.66
30    HOU     -8.0     7   1   6   0  14.3  27.2  -3.74  -7.29  3.55
31    JAX    -10.0     7   1   6   0  14.3  21.2  -9.49  -9.43 -0.07
32    NYJ    -18.0     7   0   7   0   0.0   3.9 -15.92 -16.86  0.93

Green Bay has fallen from the ranks of the unbeaten and Tampa Bay has had marked increases in its SRS rating. Atlanta won a game (thank goodness) and the NFC East remains both uncompetitive and a land of constant constant injury.

The data are not consistent on a best team. The formal rating my data set shows is just record followed by median point spread. But Baltimore tops Pythagoreans and Tampa Bay tops SRS. A true dominant team has not emerged.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
91         47     51.6      30.52        19.76     10.76

Calculated Pythagorean Exponent:  4.16


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     PIT      9.0     5   5   0   0 100.0  89.2   7.48  12.40 -4.92
2     SEA      7.0     5   5   0   0 100.0  71.8   5.41   6.80 -1.39
3     TEN      3.0     5   5   0   0 100.0  75.0   4.13   7.60 -3.47
4     BAL     15.5     6   5   1   0  83.3  90.6   9.06  12.50 -3.44
5     KC      11.5     6   5   1   0  83.3  79.2  10.82   8.00  2.82
6     CHI      4.0     6   5   1   0  83.3  60.1   2.38   2.00  0.38
7     GB       9.0     5   4   1   0  80.0  65.4   6.73   4.60  2.13
8     TB      10.5     6   4   2   0  66.7  82.5  12.60   9.17  3.44
9     ARI      9.5     6   4   2   0  66.7  83.7   3.06   9.00 -5.94
10    CLE      7.0     6   4   2   0  66.7  36.1  -5.56  -4.00 -1.56
11    IND      6.0     6   4   2   0  66.7  78.5   0.25   7.00 -6.75
12    LA       5.5     6   4   2   0  66.7  76.8  -0.07   6.33 -6.40
13    BUF      3.0     6   4   2   0  66.7  42.3  -0.84  -2.00  1.16
14    LV       4.0     5   3   2   0  60.0  49.3   4.57  -0.20  4.77
15    NO       3.0     5   3   2   0  60.0  52.1   5.77   0.60  5.17
16    MIA      7.5     6   3   3   0  50.0  81.0   4.76   7.83 -3.08
17    SF       2.0     6   3   3   0  50.0  63.2  -1.32   3.00 -4.32
18    CAR      0.5     6   3   3   0  50.0  47.8   3.14  -0.50  3.64
19    DEN     -2.0     5   2   3   0  40.0  40.2   0.38  -2.00  2.38
20    DET     -4.0     5   2   3   0  40.0  42.5  -0.30  -2.00  1.70
21    NE      -5.0     5   2   3   0  40.0  49.0   4.99  -0.20  5.19
22    DAL     -5.0     6   2   4   0  33.3  27.6  -9.26  -7.50 -1.76
23    CIN     -3.5     6   1   4   1  25.0  30.6  -6.23  -4.67 -1.56
24    PHI     -5.5     6   1   4   1  25.0  28.9  -5.95  -5.67 -0.29
25    LAC     -3.0     5   1   4   0  20.0  37.0   2.22  -3.00  5.22
26    MIN     -5.0     6   1   5   0  16.7  29.1  -4.42  -6.17  1.74
27    ATL     -5.5     6   1   5   0  16.7  37.0  -3.00  -3.67  0.66
28    NYG     -6.0     6   1   5   0  16.7  15.4 -10.40  -8.50 -1.90
29    HOU     -7.5     6   1   5   0  16.7  28.5  -3.05  -6.00  2.95
30    JAX    -12.0     6   1   5   0  16.7  17.6  -9.41  -9.33 -0.07
31    WAS    -14.0     6   1   5   0  16.7  15.6 -10.64  -9.00 -1.64
32    NYJ    -19.0     6   0   6   0   0.0   2.3 -17.29 -18.33  1.05

In a news week when the compound fracture of Dak Prescott’s ankle was the lead news story, hard to say too much more about the NFL. I’ll note KC is no longer unbeaten. Green Bay leads the league in median point spread and wins, Baltimore is otherwise the statistical darling of the moment. Las Vegas is ranked as good, though most of that is strength of schedule. Atlanta changed coaches. Many fans thought the change should have been done at the end of last season.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
77         40     51.9      30.53        20.27     10.26

Calculated Pythagorean Exponent:  4.95


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     GB      11.5     4   4   0   0 100.0  88.3  12.19  12.75 -0.56
2     PIT      8.0     4   4   0   0 100.0  81.9   0.23   7.75 -7.52
3     SEA      7.0     5   5   0   0 100.0  75.2   8.23   6.80  1.43
4     TEN      2.5     4   4   0   0 100.0  81.8   4.95   8.00 -3.05
5     BAL     17.0     5   4   1   0  80.0  96.5  14.39  14.60 -0.21
6     KC      14.0     5   4   1   0  80.0  81.8  13.66   7.80  5.86
7     CLE      9.0     5   4   1   0  80.0  55.7   0.99   1.40 -0.41
8     LA       8.0     5   4   1   0  80.0  88.5   1.65   9.20 -7.55
9     CHI      4.0     5   4   1   0  80.0  56.0  -1.55   1.00 -2.55
10    BUF      3.0     5   4   1   0  80.0  47.4  -1.01  -0.60 -0.41
11    IND      8.0     5   3   2   0  60.0  85.5   2.56   7.60 -5.04
12    TB       7.0     5   3   2   0  60.0  74.4   5.38   5.40 -0.02
13    CAR      5.0     5   3   2   0  60.0  54.1   1.86   0.80  1.06
14    LV       4.0     5   3   2   0  60.0  49.2   5.54  -0.20  5.74
15    ARI      4.0     5   3   2   0  60.0  75.5  -2.20   5.20 -7.40
16    NO       3.0     5   3   2   0  60.0  52.4   4.71   0.60  4.11
17    NE       2.5     4   2   2   0  50.0  56.5   9.49   1.25  8.24
18    DAL     -3.0     5   2   3   0  40.0  38.0  -4.63  -3.40 -1.23
19    MIA     -3.0     5   2   3   0  40.0  71.4   5.55   4.60  0.95
20    SF      -4.0     5   2   3   0  40.0  60.3  -5.77   2.00 -7.77
21    CIN     -3.0     5   1   3   1  30.0  26.0  -4.74  -4.80  0.06
22    PHI     -9.0     5   1   3   1  30.0  22.6 -10.06  -6.40 -3.66
23    DEN     -3.5     4   1   3   0  25.0  29.3  -6.30  -4.00 -2.30
24    DET     -5.0     4   1   3   0  25.0  22.6  -3.71  -7.00  3.29
25    MIN     -1.0     5   1   4   0  20.0  33.2   1.32  -4.00  5.32
26    LAC     -3.0     5   1   4   0  20.0  34.7   1.17  -3.00  4.17
27    HOU     -8.0     5   1   4   0  20.0  23.3  -1.32  -6.00  4.68
28    JAX     -8.0     5   1   4   0  20.0  18.5  -6.20  -7.60  1.40
29    WAS    -14.0     5   1   4   0  20.0   9.0  -9.65 -10.60  0.95
30    ATL     -7.0     5   0   5   0   0.0  20.2  -4.58  -7.80  3.22
31    NYG     -8.0     5   0   5   0   0.0   7.9 -12.41 -10.40 -2.01
32    NYJ    -18.0     5   0   5   0   0.0   2.2 -19.74 -17.20 -2.54


I watched a bit of the Atlanta – Green Bay game, and though I thought Atlanta played hard, they once again lost. This is a team that needs one good pass rusher that performs each season, and needs more help in the backfield. I had thought they had solved their backfield issues at the end of last year, but now they seem to have started again.

I watched a bit of Tampa Bay, which I guess is many people’s alternate team. They looked good, and did well against a tough opponent. The QB from Oregon, Justin Hebert, is playing better than a rookie usually does. And the Bengals won a game.

Are QBs important? Perhaps you should ask New England.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
63         31     49.2      30.19        20.40      9.79

Calculated Pythagorean Exponent:  5.84


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     KC      14.0     4   4   0   0 100.0  95.2  16.86  11.75  5.11
2     GB      11.5     4   4   0   0 100.0  91.6  10.75  12.75 -2.00
3     SEA      7.5     4   4   0   0 100.0  82.4   9.32   8.25  1.07
4     PIT      7.0     3   3   0   0 100.0  86.7  -1.22   7.33 -8.56
5     BUF      5.0     4   4   0   0 100.0  77.0   3.40   5.75 -2.35
6     TEN      2.0     3   3   0   0 100.0  61.2  -2.99   2.00 -4.99
7     BAL     15.5     4   3   1   0  75.0  95.2  13.17  12.25  0.92
8     IND     12.5     4   3   1   0  75.0  97.2   4.86  11.75 -6.89
9     TB      10.5     4   3   1   0  75.0  82.5   7.49   7.00  0.49
10    CLE      8.0     4   3   1   0  75.0  47.7  -0.70  -0.50 -0.20
11    LA       5.5     4   3   1   0  75.0  83.8   1.00   6.50 -5.50
12    CHI      4.0     4   3   1   0  75.0  57.0  -3.43   1.00 -4.43
13    SF       7.0     4   2   2   0  50.0  91.6  -0.80   9.00 -9.80
14    NE       2.5     4   2   2   0  50.0  57.7   9.31   1.25  8.06
15    CAR      0.5     4   2   2   0  50.0  45.7   2.21  -0.75  2.96
16    ARI      0.5     4   2   2   0  50.0  59.1  -1.12   1.50 -2.62
17    NO      -0.5     4   2   2   0  50.0  50.0   4.08   0.00  4.08
18    LV      -1.5     4   2   2   0  50.0  38.8   2.50  -2.25  4.75
19    CIN     -1.5     4   1   2   1  37.5  50.0  -2.70   0.00 -2.70
20    PHI     -5.0     4   1   2   1  37.5  19.6  -8.24  -5.75 -2.49
21    DEN     -3.5     4   1   3   0  25.0  26.1  -7.29  -4.00 -3.29
22    LAC     -4.0     4   1   3   0  25.0  31.3   2.96  -3.00  5.96
23    DAL     -5.0     4   1   3   0  25.0  29.7  -3.79  -5.00  1.21
24    MIN     -5.0     4   1   3   0  25.0  27.6  -2.84  -4.75  1.91
25    DET     -5.0     4   1   3   0  25.0  18.9  -4.43  -7.00  2.57
26    JAX     -5.5     4   1   3   0  25.0  22.9  -4.82  -5.50  0.68
27    MIA     -5.5     4   1   3   0  25.0  45.4   3.55  -0.75  4.30
28    WAS    -14.0     4   1   3   0  25.0  11.5  -7.47  -8.25  0.78
29    ATL     -8.5     4   0   4   0   0.0  17.7  -4.79  -8.00  3.21
30    NYG     -9.0     4   0   4   0   0.0   1.5 -13.36 -12.25 -1.11
31    HOU    -11.0     4   0   4   0   0.0   6.6  -5.01 -11.50  6.49
32    NYJ    -14.0     4   0   4   0   0.0   1.6 -16.46 -16.50  0.04

I didn’t expect my tools to resolve data after just three games. Many of the values will be wild (Pythags over 5) and will begin to calm down after a couple more weeks of play. The more data, the more accurate SRS becomes.

The best undefeated team is Kansas City. The best 2-1 team could be any of San Francisco, Baltimore, or Indianapolis. Of the 1-2 teams, the best appears to be Miami. Of the 0-3 team, the best appears to be the Atlanta Falcons.

Global Statistics:
Games  Home Wins HwPct Winning_Score Losing_Score Margin
48         25     52.1      29.98        20.02      9.96

Calculated Pythagorean Exponent:  5.43


Rank  Team    Median  GP   W   L   T  Pct   Pred   SRS    MOV   SOS
------------------------------------------------------------------------
1     KC      14.0     3   3   0   0 100.0  90.6   9.84  10.33 -0.49
2     GB       9.0     3   3   0   0 100.0  87.7  12.57  12.33  0.23
3     SEA      7.0     3   3   0   0 100.0  80.0  14.39   8.33  6.06
4     PIT      7.0     3   3   0   0 100.0  85.1  -1.75   7.33 -9.09
5     CHI      4.0     3   3   0   0 100.0  72.3  -2.04   4.00 -6.04
6     BUF      3.0     3   3   0   0 100.0  73.6   4.81   5.33 -0.52
7     TEN      2.0     3   3   0   0 100.0  60.4  -0.81   2.00 -2.81
8     SF      18.0     3   2   1   0  66.7  97.0   5.05  13.67 -8.62
9     BAL     17.0     3   2   1   0  66.7  93.3   8.81  11.67 -2.86
10    IND     17.0     3   2   1   0  66.7  96.7   8.19  13.00 -4.81
11    TB      14.0     3   2   1   0  66.7  83.3   6.64   7.00 -0.36
12    NE      10.0     3   2   1   0  66.7  81.8  17.25   7.00 10.25
13    CLE      5.0     3   2   1   0  66.7  29.6 -11.39  -4.33 -7.05
14    LV       4.0     3   2   1   0  66.7  47.0   7.05  -0.67  7.72
15    ARI      4.0     3   2   1   0  66.7  78.0   0.38   5.33 -4.95
16    LA       3.0     3   2   1   0  66.7  77.3   2.10   6.00 -3.90
17    DAL     -3.0     3   1   2   0  33.3  37.1   2.10  -3.00  5.10
18    MIA     -3.0     3   1   2   0  33.3  59.9   9.32   1.67  7.66
19    JAX     -3.0     3   1   2   0  33.3  27.1   0.90  -4.67  5.57
20    LAC     -3.0     3   1   2   0  33.3  37.8  -3.26  -1.67 -1.59
21    DET     -4.0     3   1   2   0  33.3  18.5  -3.70  -7.33  3.64
22    CAR     -4.0     3   1   2   0  33.3  27.9  -0.85  -4.33  3.48
23    NO      -7.0     3   1   2   0  33.3  41.1   6.75  -2.00  8.75
24    WAS    -14.0     3   1   2   0  33.3  19.0 -16.21  -6.33 -9.87
25    CIN     -3.0     3   0   2   1  16.7  34.9 -13.75  -2.67 -11.09
26    PHI    -10.0     3   0   2   1  16.7  10.8 -18.62  -9.33 -9.29
27    ATL     -4.0     3   0   3   0   0.0  27.1  -1.18  -6.00  4.82
28    DEN     -5.0     3   0   3   0   0.0   8.3  -6.97  -8.33  1.36
29    MIN     -9.0     3   0   3   0   0.0  15.8  -2.35  -9.00  6.65
30    NYG    -10.0     3   0   3   0   0.0   1.8 -13.25 -13.67  0.42
31    HOU    -14.0     3   0   3   0   0.0   5.9  -7.04 -12.67  5.63
32    NYJ    -18.0     3   0   3   0   0.0   0.6 -12.98 -19.00  6.02

The methodology for this prediction is here.

I managed to watch big chunks of both conference games. The Titans made a game of it for one half. They ran out of steam in the third quarter and ended up losing, but the team overall looked good. The Packers were crushed. The score doesn’t really show how bad the game actually was.

Last I read, Kansas City was favored by one point in the odds. My system favors them by a lot more, more like 5 points.

Super Bowl Odds
Home Team Visiting Team Score Diff Win Prob Est. Point Spread
Kansas City Chiefs San Francisco 49ers 0.683 0.66 5.1

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