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.
Quick menu:
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!
2020 College Football Forecast (NCAA Div IA & IAA)
- Week 1 (28 Aug - 7 Sep):
Forecast ,
Results
- Week 2 (10-12 Sep):
Forecast ,
Results
- Week 3 (18-19 Sep):
Forecast ,
Results
- Week 4 (24-26 Sep):
Forecast ,
Results
- Week 5 (2-3 Oct):
Forecast ,
Results
- Week 6 (7-10 Oct):
Forecast ,
Results
- Week 7 (14-17 Oct):
Forecast ,
Results
- Week 8 (22-24 Oct):
Forecast ,
Results
- Week 9 (29-31 Oct):
Forecast ,
Results
- Week 10 (5-7 Nov):
Forecast ,
Results
- Week 11 (13-14 Nov):
Forecast ,
Results
- Week 12 (20-21 Nov):
Forecast ,
Results
- Week 13 (27-28 Nov):
Forecast ,
Results
- Week 14 (1-5 Dec):
Forecast ,
Results
- Week 15 (10-12 Dec):
Forecast ,
Results
- Week 16 (17-19 Dec):
Forecast ,
Results
- Bowl Games:
Forecast ,
Results
- FBS & FCS Championship Games:
Forecast ,
Results
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. The Current Model Power Rankings are the best
indicator of how well a team will play in the future.
The 2020 Bassett Model rankings, filtered for active teams, can be found at
College Football Ranking Comparasion
2020 Model Performance:
All Div I games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 80 303 61 65 73 0 582
number right: 42 200 48 54 68 0 412
number expected: 44.2 197.6 45.9 55.9 68.4 0.0 412.0
right/expected: 0.95 1.01 1.05 0.97 0.99 0.00 1.00
Breakdown by Conference and Division:
Conference games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 63 227 45 49 55 0 439
number right: 31 147 35 42 51 0 306
number expected: 34.7 148.0 33.8 42.1 51.5 0.0 310.1
right/expected: 0.89 0.99 1.03 1.00 0.99 0.00 0.99
Non-Conference games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 11 59 13 11 15 0 109
number right: 7 38 10 7 14 0 76
number expected: 6.2 38.4 9.8 9.5 14.2 0.0 78.0
right/expected: 1.14 0.99 1.02 0.74 0.99 0.00 0.97
Non-Division games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 6 17 3 5 3 0 34
number right: 4 15 3 5 3 0 30
number expected: 3.3 11.2 2.3 4.3 2.8 0.0 23.9
right/expected: 1.20 1.34 1.32 1.15 1.07 0.00 1.25
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)
2020 NFL Forecast
- Week 1 (10-14 Sep):
Forecast ,
Results
- Week 2 (17-21 Sep):
Forecast ,
Results
- Week 3 (24-28 Sep):
Forecast ,
Results
- Week 4 (1-5 Oct):
Forecast ,
Results
- Week 5 (8-12 Oct):
Forecast ,
Results
- Week 6 (15-19 Oct) - updated 17 Oct:
Forecast ,
Results
- Week 7 (22-26 Oct):
Forecast ,
Results
- Week 8 (29 Oct - 2 Nov):
Forecast ,
Results
- Week 9 (5-9 Nov):
Forecast ,
Results
- Week 10 (12-16 Nov):
Forecast ,
Results
- Week 11 (19-23 Nov):
Forecast ,
Results
- Week 12 (26-30 Nov):
Forecast ,
Results
- Week 13 (3-7 Dec):
Forecast ,
Results
- Week 14 (10-14 Dec):
Forecast ,
Results
- Week 15 (17-21 Dec):
Forecast ,
Results
- Week 16 (25-28 Dec):
Forecast ,
Results
- Week 17 (3 Jan):
Forecast ,
Results
- Postseason: Wild Card (9-10 Jan):
Forecast ,
Results
- Postseason: Divisional (16-17 Jan):
Forecast ,
Results
- Postseason: Conference (24 Jan):
Forecast ,
Results
- Super Bowl (7 Feb):
Forecast
2020 Model Performance:
All games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 39 173 31 25 0 0 268
number right: 22 106 17 23 0 0 168
number expected: 21.5 107.2 23.1 20.8 0.0 0.0 172.6
right/expected: 1.02 0.99 0.74 1.11 0.00 0.00 0.97
Breakdown by Division and Conference:
Division games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 13 66 11 9 0 0 99
number right: 8 39 5 9 0 0 61
number expected: 7.2 41.0 8.2 7.5 0.0 0.0 63.8
right/expected: 1.12 0.95 0.61 1.21 0.00 0.00 0.96
Non-Division games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 13 68 18 6 0 0 105
number right: 6 44 11 6 0 0 67
number expected: 7.2 42.0 13.5 5.0 0.0 0.0 67.7
right/expected: 0.84 1.05 0.82 1.20 0.00 0.00 0.99
Non-Conference games forecast probabilities
50-59% 60-69% 70-79% 80-89% 90-99% 100% all
total games: 13 39 2 10 0 0 64
number right: 8 23 1 8 0 0 40
number expected: 7.2 24.1 1.4 8.3 0.0 0.0 41.1
right/expected: 1.11 0.95 0.71 0.96 0.00 0.00 0.97
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)
Links of interest
Please email comments or questions to
bfm@BassettFootball.net