The Dr. K. NCAA Football Forecasts

New Year's Bowl Games

 
 
 

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.

     

     Nebraska (+9)                     31
     Georgia (O 60)                    40          0.6994     0.5105     0.7177     

     UNLV (U 54.5)                     20
     North Texas (-6.5)                31          0.7745     0.6257     0.5556     

     Wisconsin (-1.5)                  24
     South Carolina (U 51)             20          0.6150     0.5747     0.6134     

     Iowa (U 49)                       17
     LSU (-7.5)                        28          0.7669     0.5846     0.5623     

********************************************************************************
*  Best Bet against the Over/Under
*    Michigan St (U 42.5)              13
*    Stanford (-6.5)                   20          0.6907     0.5033     0.7471     
********************************************************************************

     C Florida (+17)                   31
     Baylor (O 70.5)                   44          0.7798     0.5996     0.5720     

     Oklahoma (U 51.5)                 17
     Alabama (-15.5)                   33          0.8645     0.5125     0.6258     

     Oklahoma St (+1)                  31
     Missouri (U 61.5)                 30          0.5168     0.5423     0.5173     

     Clemson (+3)                      35
     Ohio St (O 69.5)                  37          0.5395     0.5332     0.5371     

     Houston (+2.5)                    26
     Vanderbilt (O 53.5)               28          0.5444     0.5213     0.5305     

     Arkansas St (+7.5)                28
     Ball St (U 64.5)                  35          0.6655     0.5200     0.5686     

********************************************************************************
*  Best Bet against the Point Spread
*    Auburn (U 67.5)                   21
*    Florida St (-8.5)                 40          0.8802     0.7375     0.6160     
********************************************************************************



2013 Record
                    Straight-up                  vs. Spread                Over/Under 
Last Week         13-4-0    0.765             11-6-0      0.647          11-6-0     0.647
Season           550-166-0  0.768            368-338-10   0.521         384-322-10  0.542
 
                                        
                            Best Bet (Spread)         Best Bet (Over/Under)         
Last Week                     1-0-0   1.000                1-0-0  1.000            
Season                        9-9-0   0.500               12-6-0  0.667           

      
Email:mailto:edwardkambour@sbcglobal.net

"Printer-friendly page"

"Points spread page (sorted by probability of beating the spread)"

"Over/Under page (sorted by probability of beating the over/under)"

"Predicted scores for all Bowls, as of 12/14/13"

To take a look at the underlying rankings click here.

To review previous weeks predictions: 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 Pre-Xmas Bowls Xmas to New Year Bowls

To check out the NFL 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.