The Dr. K. NFL Football Forecasts

Super Bowl

The following predictions are based completely on the Kambour football ratings .

The results are sorted by start time.

The small numbers in parentheses represent the point-spread. The over/under pick is in parentheses with a U or O.

The next 3 columns represent the estimated probabilities. The first number is the probability that the team picked to win actually wins. The second is the probability that the team picked to beat the spread beats the spread. The third is the probability that we beat the over/under.

Printer friendly links and links with games sorted by value according to spread and over/ under are listed at the bottom of the page. 


***********************************************************************************
*  Best Bet against the Point Spread and Over/Under
*     NY Giants (U 55.5)                24
*     New England (-2.5)                31          0.6920     0.6245     0.5342        
***********************************************************************************


Record

                      Straight-up                  vs. Spread                  Over/Under          
Last Week            1-1-0    0.500              0-2-0     0.000             2-0-0     1.000      
Season             178-88-0   0.669            158-103-5   0.606           155-108-3   0.588    

 
                               Best Bet vs Spread         Best Bet vs O/U         
Last Week                       0-1-0      0.000            1-0-0     1.000            
Season                          9-10-1     0.475           14-6-0     0.700
Email:edwardkambour@sbcglobal.net

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"Points spread page (sorted by value)"

"Over/Under page (sorted by value)"

To take a look at the underlying rankings click here.

To examine previous weeks results: week 1 week 2 week 3 week 4 week 5 week 6 week 7 week 8 week 9 week 10 week 11 week 12 week 13 week 14 week 15 week 16 week 17 week 18 week 19 week 20

To check out the NCAA page click here.

Note: The 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.