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
     Cincinnati        78.2310  2.3008
     Seattle           78.0203  7.2675
     Denver            77.2415  3.1433
     San Francisco     76.3417  2.8907
     San Diego         74.9495  2.0057
     New England       74.9478  0.7783
     Carolina          73.6941 -0.7755
     Kansas City       72.8267  1.6099
     Dallas            72.4509  3.3059
     Baltimore         72.2249  7.3021
     Indianapolis      72.1927  2.5860
     New Orleans       71.9569  6.7657
     Philadelphia      71.7708  0.2641
     Green Bay         71.7690  2.9131
     Arizona           71.4400  7.0394
     Miami             70.7455 -1.1561
     Detroit           70.4423  5.1763
     NY Giants         70.3780  0.2690
     Atlanta           70.3192  3.2743
     Chicago           69.8288  1.6719
     Pittsburgh        69.8092  3.0124
     Minnesota         69.0701  2.9027
     Cleveland         66.4755  1.6192
     Houston           66.3780  2.7098
     Buffalo           65.6164  7.9039
     Tennessee         65.5297  1.7093
     St Louis          65.2614  3.1665
     Washington        64.8341  0.6691
     NY Jets           64.2105  2.5540
     Tampa Bay         64.2039  2.1050
     Oakland           61.3994 -0.4212
     Jacksonville      55.4404  0.3307



Note: Ratings include games through 9/29/14.
 







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