The Inheriting Model

This model determines the best and worst FBS teams of all time based on strength of record

Displaying the top 100 teams for the end of the season in all seasons

Rank Season Team Score
11945Army0.847
21932USC0.811
31912Harvard0.802
41916Army0.802
51940Minnesota0.798
62018Clemson0.794
71930Alabama0.792
82020Alabama0.790
92015Alabama0.789
102019LSU0.789
112010Auburn0.787
122022Georgia0.786
132009Alabama0.786
141920California0.784
151937Pittsburgh0.784
161917Pittsburgh0.781
171905Yale0.781
181930Notre Dame0.781
191999Florida State0.780
201906Vanderbilt0.780
211983Auburn0.779
221909Michigan0.778
231978USC0.778
241944Norman Naval Air Station0.776
251931USC0.775
262016Clemson0.774
271946Army0.773
282001Miami0.772
291911Minnesota0.771
301915Georgia Tech0.771
311918Colorado School Of Mines0.771
322005Texas0.770
332004Auburn0.769
342006Florida0.769
352011LSU0.769
361971Nebraska0.769
372023Michigan0.768
381945Alabama0.767
391939Cornell0.767
401916Ohio State0.767
412016Alabama0.766
421952Georgia Tech0.766
431937Fordham0.765
441989Notre Dame0.764
451991Miami0.764
461943March Field0.763
472000Oklahoma0.763
481971Alabama0.763
491947Texas0.763
501995Nebraska0.763
511996Florida0.762
522002Ohio State0.762
531977Tennessee State0.762
541943Notre Dame0.761
551987Florida State0.761
561987Miami0.760
571972USC0.760
581902Yale0.760
591905Chicago0.759
601913Auburn0.759
611912Wisconsin0.759
621982Penn State0.759
631948Michigan0.759
642004USC0.759
651992Alabama0.758
661986Penn State0.758
671969Penn State0.757
681952Michigan State0.757
691959Syracuse0.757
701964Princeton0.756
711916Pittsburgh0.756
721908Harvard0.756
731938Tennessee0.756
742017UCF0.756
751997Michigan0.755
761930Utah0.755
771939Texas A&M0.755
781925Alabama0.755
791974Oklahoma0.755
802008Florida0.755
811922California0.754
821978Alabama0.754
831988Notre Dame0.754
842019Ohio State0.754
851994Penn State0.754
861928Georgia Tech0.753
871909Sewanee0.753
882014Ohio State0.752
891991Washington0.752
901940Stanford0.752
911933Michigan0.752
921920Princeton0.752
931898Harvard0.751
941923Michigan0.751
951916Georgia Tech0.751
961929Utah0.751
972021Georgia0.751
981994Nebraska0.751
992000Miami0.750
1001981Clemson0.750

How the Model Works

Winning against an opponent means you inherit your opponent's win percentage, and losing against an opponent means you inherit their loss percentage. Inheriting means you add your opponent's win percentage to your score on a win and you subtract your opponent's loss percentage from your score on a loss. Since ties were possible before the 1996 season, scoring for tying an opponent means inheriting the opponent's win percentage minus .500. This means that if the opponent's win percentage is above .500 your score gains a little, and if it's below .500 your score loses a little.

The scores are normalized for how many FBS games are played, and only FBS games are counted for scoring. The FBS/FCS split only happened in the 1978 season, so the FBS designation before 1978 is based off what the CFBD python library (where I pulled my data from) designates as FBS. Scores are also adjusted to a range of 0 to 1 from an original range of -1 to 1 by simply adding 1 and dividing by 2. This means all teams begin seasons with a score of .500. The first 3 weeks are not displayed since they are not informative from how few FBS games have been played by that point in the season.

FAQ

Q: How accurate is the model for predicting game results?

A: It is as accurate as using pure win percentage to predict, so it can correctly predict the results of a game about 70% of the time.