2011-12 National Football League
Computer Ratings
Introduction

This is my first rough attempt at a computer rating that can, among other things, come somewhat close to predicting final game scores. The actual computer rating, which describes team performance based on games played to date, is found under the "Rating" column. To determine a hypothetical margin of victory, use the "Pts" column. You can the calculation for some upcoming games on the right. Don't forget to add in home "field" advantage, which is listed just below the current predictions on the right. 

Ratings last updated Monday 01/09/12, 09:24 AM ET

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                                                        BCS-Style 
 Rank  Team                      W  L   Rating    Pts     Rank    
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   1  New Orleans              14  3    3.977    11.84       2
   2  Green Bay                15  1    3.558     8.25       1
   3  New England              13  3    2.906     8.77       4
   4  San Francisco            13  3    2.708     6.28       3
   5  Baltimore                12  4    2.388     5.97       5
   6  Detroit                  10  7    2.220     7.11       7
   7  Pittsburgh               12  5    2.105     5.26       6
   8  Houston                  11  6    1.659     5.34       8
   9  Philadelphia              8  8    1.309     5.16      10
  10  NY Giants                10  7    1.132     2.86       9
  11  NY Jets                   8  8    0.400     2.28      17
  12  San Diego                 8  8    0.292     1.19      13
  13  Atlanta                  10  7    0.160     0.50      14
  14  Chicago                   8  8    0.077     0.36      16
  15  Arizona                   8  8    0.013    -1.01      11
  16  Dallas                    8  8   -0.059     0.41      18
  17  Miami                     6 10   -0.068     1.75      22
  18  Tennessee                 9  7   -0.145    -1.16      15
  19  Seattle                   7  9   -0.153     0.38      20
  20  Denver                    9  8   -0.572    -4.26      12
  21  Cincinnati                9  8   -0.606    -2.32      19
  22  Carolina                  6 10   -1.067    -1.98      24
  23  Washington                5 11   -1.282    -2.45      25
  24  Oakland                   8  8   -1.359    -5.74      21
  25  Buffalo                   6 10   -1.630    -3.98      26
  26  Minnesota                 3 13   -1.882    -3.40      30
  27  Cleveland                 4 12   -2.060    -4.12      31
  28  Kansas City               7  9   -2.220    -8.81      23
  29  Jacksonville              5 11   -2.445    -6.77      28
  30  St Louis                  2 14   -2.661    -8.22      27
  31  Tampa Bay                 4 12   -2.796    -8.60      29
  32  Indianapolis              2 14   -3.900   -10.90      32
(The "BCS style" ranking is one based entirely on wins and losses, similar to what is used in college football.)

 

                     PREDICTIONS FOR UPCOMING GAMES

   Date       Away Team                  Home Team                    Prediction
----------    ------------------------   ------------------------   --------------


Current home field advantage is:  3.44

MAE for games to date:  9.84

These ratings fit to produce 0.70 of the correct winners.
Pct when predicted MOV is above 6.87:  0.82

A favored away team rarely loses when favored by more than -5.69.

A favored home team rarely loses when favored by more than 7.48.
Above are some statistics about the ratings model. Home "field" advantage is shown first. MAE is the mean absolute error of the ratings fit to all the games played to date. This number is usually larger than you think it should be, but to me it's a good measure of how variable (or maybe "predictable") game outcomes can be.

Immediately below that, you can see how this best fit does in retro-predicting (there's a better word I'm sure) just the game winners. My favorite stats are the last two--when the home or away team is favored by the given margin, they only lose 30 percent of the time. This is the kind of information that people in the sports wagering world might find useful.

About the author

I have a Ph.D. in Atmospheric Science from the University of Alabama in Huntsville. I now work in Boulder, Colorado, in the broad areas of science education and numerical weather prediction (that is, forecasting the weather using computer models). Contact me using this email form if you have questions or non-hateful comments.