Bassett Football Model

The Bassett football model is a system for ranking the relative strengths of football teams. A key feature of this model is that it recognizes that if two teams could play more than once the same team would not always win (there is an element of chance involved). The system is based on a simple model of a football game. For a given match-up of two teams, a number of model games are simulated by a computer and the average scores and the percentage of times each team wins is computed. Each week during the football season the best fit of offensive and defensive strengths is found for each team consistent with the actual scores. I do include considerations for home field advantage and for the possibility that teams may score less than expected in a blow-out if they choose to run out time instead of score more points in the latter part of a game.

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The purpose of this football web page is to provide an unbiased analysis of the teams: how they compare with each other and what sort of results to expect from upcoming games. It is not my intention, however, to encourage gambling with this information. I have purposely presented the information in a way that will minimize its usefulness in this regard while still providing useful entertainment, etc. Comments on how to avoid the misuse of these web pages for gambling are most welcome.

Enjoy!

2022 College Football Forecast (NCAA Div IA & IAA)

Bassett Model rankings:

The Stephenson Earned Rank shows what a team has earned from its wins. It ranks by how much better a given team's winning record is when compared against how all other teams would have faired if they had played the same schedule. (Available after the 5th week in the season.) The Power Rankings measure the strength of each team by how well they have played on average, going by point performance.

11 Jan 2023: Stephenson Earned Rank (NCAA Div I & IAA)
(Team wins subtracted by average number of wins if all other teams played their schedule as simulated by the Bassett Football Model)

11 Jan 2023: Average Model Power Rankings (NCAA Div I & IAA)
(average power ranking for entire season)

2022 Model Performance: 

All Div I games               forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:        231     420     425     385      58       0    1519
number right:       117     271     311     336      55       0    1090
number expected:  127.5   272.8   309.1   334.3    53.1     0.0  1096.9
right/expected:    0.92    0.99    1.01    1.00    1.04    0.00    0.99

Breakdown by Conference and Division:
Conference games              forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:        143     236     274     267      41       0     961
number right:        70     136     186     234      39       0     665
number expected:   79.0   153.4   199.6   232.0    37.5     0.0   701.4
right/expected:    0.89    0.89    0.93    1.01    1.04    0.00    0.95

Non-Conference games          forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:         70     138     117      98      16       0     439
number right:        39      97      91      84      15       0     326
number expected:   38.5    89.5    84.8    85.2    14.7     0.0   312.7
right/expected:    1.01    1.08    1.07    0.99    1.02    0.00    1.04

Non-Division games            forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:         18      46      34      20       1       0     119
number right:         8      38      34      18       1       0      99
number expected:   10.0    30.0    24.7    17.2     0.9     0.0    82.8
right/expected:    0.80    1.27    1.38    1.05    1.10    0.00    1.20

actual/expected = 1 -- model right on
actual/expected > 1 -- model probabilities too low (more wins than expected)
actual/expected < 1 -- model probabilities too high (less wins than expected)

Past Seasons

2022 NFL Forecast

31 Jan 2023: Average model rankings (NFL) (average rank over entire season)

2022 Model Performance: 

All games                     forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:         90     132      47      14       0       0     283
number right:        43      77      31      11       0       0     162
number expected:   50.1    83.5    34.9    11.7     0.0     0.0   180.1
right/expected:    0.86    0.92    0.89    0.94    0.00    0.00    0.90

Breakdown by Division and Conference:
Division games                forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:         31      47      17       5       0       0     100
number right:        17      25      13       3       0       0      58
number expected:   17.0    29.8    12.7     4.2     0.0     0.0    63.7
right/expected:    1.00    0.84    1.03    0.72    0.00    0.00    0.91

Non-Division games            forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:         36      45      18       4       0       0     103
number right:        17      27       9       4       0       0      57
number expected:   20.1    28.4    13.3     3.3     0.0     0.0    65.1
right/expected:    0.85    0.95    0.68    1.21    0.00    0.00    0.88

Non-Conference games          forecast probabilities
                 50-59%  60-69%  70-79%  80-89%  90-99%    100%     all
total games:         23      40      12       5       0       0      80
number right:         9      25       9       4       0       0      47
number expected:   12.9    25.3     8.9     4.2     0.0     0.0    51.3
right/expected:    0.70    0.99    1.02    0.95    0.00    0.00    0.92

actual/expected = 1 -- model right on
actual/expected > 1 -- model probabilities too low (more wins than expected)
actual/expected < 1 -- model probabilities too high (less wins than expected)

Past Seasons

Links of interest

Please email comments or questions to bfm@BassettFootball.net