The Dr. Edward Kambour NFL Football Ratings

2014 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
     New England       80.4176  1.4693
     Denver            76.7207  4.4800
     Seattle           75.4109  7.1806
     Miami             75.2789 -0.0713
     Green Bay         74.8401  5.4556
     San Francisco     74.6437  2.3996
     Kansas City       74.5170  2.2063
     Indianapolis      73.8776  3.1566
     Philadelphia      73.6193  1.7797
     Cincinnati        73.3407  1.3440
     Baltimore         73.2395  7.0267
     Dallas            71.9534  2.1974
     San Diego         71.8503  3.0176
     New Orleans       71.1820  5.5988
     Arizona           71.1579  6.9753
     Carolina          70.2089 -0.7065
     Detroit           69.6605  4.8714
     Pittsburgh        69.0174  4.6723
     Houston           68.6501  1.7843
     Buffalo           68.6084  6.3599
     Chicago           67.9259  2.1390
     Cleveland         67.9057  1.6215
     NY Giants         67.4073  1.0152
     Atlanta           67.3635  2.9496
     Minnesota         66.9166  2.7014
     St Louis          66.4312  3.7367
     Washington        65.7776 -0.6127
     Tennessee         64.1119  1.2662
     Tampa Bay         64.0379  0.7204
     Oakland           63.9450 -0.5267
     NY Jets           61.4446  3.2140
     Jacksonville      58.5379  1.2692


Note: Ratings include games through 11/24/14.
 







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