The Dr. Edward Kambour NFL Football Ratings

2015 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
     Seattle           79.8304  3.4976
     Kansas City       78.4137  1.1815
     New England       78.0153  2.5469
     Cincinnati        77.9959  0.6403
     Carolina          77.9714  2.1734
     Denver            75.8048  3.0596
     Arizona           75.5872  4.9433
     Pittsburgh        74.9659  4.2022
     Green Bay         74.2382  5.0737
     Minnesota         72.4917  3.0422
     Buffalo           70.4557  4.9151
     NY Jets           69.3938  3.6601
     Philadelphia      69.3788  0.2792
     Houston           69.3058  2.0569
     Detroit           68.9689  4.3016
     NY Giants         68.4236  0.8418
     Chicago           68.3243  0.0895
     Baltimore         68.2170  4.4635
     San Diego         68.1601  1.8119
     Dallas            67.9179  0.5890
     St Louis          67.8862  3.9336
     Miami             67.6836 -0.3829
     Washington        67.4314  0.6308
     Oakland           66.9653  0.6967
     Atlanta           66.9639  2.7503
     Indianapolis      66.3292  3.9643
     New Orleans       66.1506  3.6741
     San Francisco     65.1609  3.7633
     Tampa Bay         64.5502 -1.0811
     Cleveland         64.1013  1.0010
     Jacksonville      61.7314  3.0479
     Tennessee         61.1857 -0.3154



Note: Ratings include games up to 1/24/16
 







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

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