The Dr. Edward Kambour NFL Football Ratings

2013 Season Ratings


Below are the ratings for NFL football. The first column is the team, followed by the estimated power rating and home-field advantage. To forecast the outcome of a game simply subtract the visiting team's rating from the sum of the home team's rating and the home team's home field advantage. The difference is approximately the forecasted point-spread. Thus, if the result is positive, the home team is predicted to win, while if the result is negative, the visiting team is predicted to win. The teams are ranked by their ratings.

Predictions of this weekend's games can be found here.

  
                        Rating  HomeAd
     San Francisco     78.8967  2.0467
     New England       78.7548  0.3574
     Denver            78.0970  4.8685
     Seattle           76.9048  9.5268
     Carolina          76.6833  2.4016
     New Orleans       73.6152 10.6292
     Cincinnati        73.5332  6.1088
     San Diego         72.6264  1.4991
     Kansas City       71.6238  1.0698
     Green Bay         71.4934  2.0271
     Philadelphia      71.4765  0.2124
     Miami             71.2146 -1.3729
     Dallas            70.7687  3.2544
     Indianapolis      70.3549  3.0452
     Pittsburgh        69.9529  2.9469
     Baltimore         69.7718  4.6458
     Chicago           69.6281  2.5968
     Arizona           69.4204  9.0186
     NY Giants         69.1415  0.7444
     Atlanta           68.8933  1.5667
     Detroit           68.3272  5.3707
     St Louis          68.0820  4.9056
     Minnesota         67.6368  1.5193
     Tennessee         67.5730  1.4399
     Tampa Bay         67.3008  1.6636
     Washington        65.4600 -0.1379
     NY Jets           65.2404  2.0295
     Houston           64.8653  0.3414
     Cleveland         64.7555  1.0584
     Oakland           63.8697 -0.9141
     Buffalo           63.5989 10.5801
     Jacksonville      60.4392 -4.4140



Note: Ratings include games through 1/19/14.
 







Note: These ratings are the result of a Dynamic Hierarchical Bayesian Linear Forecaster. The author has a Ph.D. in Statistics from Texas A&M. He specializes in Bayesian Forecasting. The forecasting method has been presented at four technical conferences, the 1997 and 1998 Conferences of Texas Statisticians, as an invited presentation at the 2001 Joint Statistical Meetings , and at a 2003 Houston INFORMS meeting. The powerpoint slides from the INFORMS talk are available here.

Email:edwardkambour@sbcglobal.net

Back to Ed and Theresa's Homepage

Visit the College Football page