The Dr. Edward Kambour NFL Football Ratings

2016 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           79.8013  3.5707
     Kansas City       78.5957  1.1017
     Cincinnati        78.1230  0.4774
     New England       78.0815  2.5837
     Carolina          77.4841  1.9216
     Denver            76.7706  2.3895
     Arizona           75.4273  5.1770
     Pittsburgh        75.0748  4.3022
     Green Bay         74.1235  5.3808
     Minnesota         72.4630  3.2106
     Buffalo           70.3739  5.0641
     Houston           69.4189  1.6631
     NY Jets           69.3846  3.6524
     Philadelphia      69.3075  0.3541
     Detroit           69.1809  4.1299
     Chicago           68.4367  0.0101
     Baltimore         68.2745  4.2145
     NY Giants         68.2332  1.1136
     San Diego         68.0348  2.1522
     Dallas            67.8992  0.4403
     Miami             67.8296 -0.5072
     Los Angeles       67.8241  4.1230
     Washington        67.3657  0.6935
     Oakland           67.0070  0.6744
     Atlanta           66.7910  2.8864
     Indianapolis      66.2057  4.0431
     New Orleans       65.8512  4.0057
     San Francisco     65.3805  3.3814
     Tampa Bay         64.4488 -1.0018
     Cleveland         64.1612  1.0038
     Jacksonville      61.6489  3.1826
     Tennessee         60.9976 -0.2027



Note: Ratings don't include any games from 2016 (yet).
 







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