Talisman Red's College Football Computer Ratings

The Wilson Formula

One of the first rating systems I ever saw the source code for was one by Mr. David Wilson (Wilson Performance Ratings; UW-Milwaukee '65, '66, UW-Madison '67). I loved its simplicity, and I have adapted it for numerous sports over the last 20 years. David passed away in January 2024 at the age of 80, and he left an important mark on the early days of the college football internet (see more in the About page). I am happy to continue producing his ratings to honor that legacy.

Wilson's system does *not* produce predictions, point spreads, etc.; it only serves as a way to rate teams based on games played. All games are weighted evenly (although his code can be set up to count postseason games twice -- I'll do that here too), and game locations and points scored/allowed do not matter.

Brief Methodology

I'm working on writing up a more detailed description of David's formula (his website was scrubbed from the UW servers a few years ago, but god bless the Internet Archive). In the meantime, it is pretty much this:

"For each game a team plays it gets a Game Performance Rating. This is equal to the opponent's rating plus 100 if the team won or minus 100 if the team lost. The team's Performance Rating is the average of its Game Performance Ratings. All of the Game Performance Ratings are recalculated each week based on the latest ratings for the opponents."

The bottom line: if you win against strong teams, you get a higher rating. If you lose against weaker teams, you get a lower rating. Sum up the results, and that's it.

Something new this year: Using the Wilson system to rate conferences based on their non-conference games. Here are the D 1 results, treating all teams in a conference as a single team.

--- Division I FBS ---
                        W  L  T
                        -  -  -
  1  Indiana            6  0     992
  2  Georgia            6  0     973
  3  Miami (FL)         5  0     967
  4  Notre Dame         6  0     944
  5  Texas Tech         5  0     924
  6  Alabama            5  1     922
  7  Texas              4  1     920
  8  Brigham Young      5  0     919
  9  Utah               5  0     917
 10  Ohio State         5  1     912
 11  Mississippi        4  1     909
 12  Oklahoma           3  2     904
 13  Iowa               5  1     898
 14  Wake Forest        5  1     896
 15  Oregon             3  2     887
 16  UCLA               5  0     884
     Mississippi St.    4  1     884
 18  Arizona            5  1     876
 19  Southern Cal       6  1     870
 20  Houston            5  1     868
 21  Kentucky           5  1     864
 22  Wisconsin          4  1     861
 23  Michigan           3  2     859
     Missouri           5  1     859
 25  Northwestern       4  1     853

--- Division I FCS ---
                        W  L  T
                        -  -  -
  1  Montana St.        5  1     754
  2  Tarleton St.       6  0     746
  3  S. Dakota St.      5  1     745
  4  Stephen F.Austin   6  0     741
  5  N. Arizona         5  2     734
  6  Harvard            4  0     721
  7  Youngstown St.     5  2     720
  8  Lehigh             6  0     717
  9  Montana            5  2     715
 10  Yale               3  1     704
 11  South Dakota       5  2     702
 12  Illinois St.       4  2     697
     Colgate            4  2     697
 14  Idaho St.          4  2     696
 15  N. Iowa            3  2     693
 16  UC Davis           4  2     687
 17  North Dakota       5  2     686
 18  Lamar              5  1     683
 19  Tennessee Tech     5  1     674
 20  Austin Peay        5  2     672
     Mercer             5  2     672
     E. Tennessee St.   5  2     672
 23  Campbell           5  1     666
 24  Monmouth (NJ)      4  2     662
 25  Abilene Christian  3  4     660

Input files

• names.txt (List of team names, going back to 1800s)
• games.txt (Games played - in 2025, collected by Dr. Peter Wolfe)
• conf.txt (Conference affiliations)

Output files

• byrating.txt (Teams listed in order by rating)
• byname.txt (Teams listed alphabetically)
• byrate1.txt (Division I FBS by rating)
• byrate2.txt (Division I FCS by rating)
• byrate3.txt (Division II by rating)
• byrate4.txt (Division III by rating)
• byrate5.txt (NAIA by rating)
• standing1.txt (Division I FBS Conference standings)
• standing2.txt (Division I FCS Conference standings)
• standing3.txt (Division II Conference standings)
• standing4.txt (Division III Conference standings)
• standing5.txt (NAIA Conference standings)
• gam_neat.txt (games.txt made neat)

An adjustment I make

David's philosophy was that every team started the season with the same rating, regardless of who they were. I disagree a little bit, and so early in the season, I use games from last year to provide a more meaningful starting point for the ratings. By the time everyone has played about 8 games, that influence is gone and the ratings are "true" to the current season.

Source code

I have saved David's original source code from 1994 in a Github repository. Feel free to download it, run it for college football or another sport or even your own league, and tell me how it goes.

More detailed methodology

[I'll add this soon...]