Computer Rating System Prediction Results for College Football (NCAA IA)

2021 Season Totals

Through 2022-01-11
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Line (updated)0.718180.5000012.62470.4247245.711770553217165165
2Line (Midweek)0.7116912.64290.4740246.300770548222
3Computer Adjusted Line0.712990.4767412.65910.4734246.306770549221205225
4Line (opening)0.707790.5000012.75260.2760251.696770545225337337
5System Median0.701300.4741012.95980.5655255.160770540230357396
6System Average0.706490.4861712.96460.5539255.949770544226369390
7ESPN FPI0.698700.4677213.02181.1573260.627770538232355404
8FEI Projections0.682770.5041213.03170.3315257.875621424197306301
9Bihl System0.693240.4939213.07530.2528258.480414287127203208
10Brent Craig0.708430.5194213.07990.5354263.541415294121214198
11TeamRankings.com0.703900.4827113.11300.7473263.278770542228363389
12Pi-Ratings Mean0.709090.4939813.13661.0153261.875770546224369378
13Dokter Entropy0.716510.4597113.14050.5041262.208769551218348409
14David Harville0.703900.4591013.14670.2825262.413770542228348410
15Laz Index0.714290.4868113.16090.6398263.527770550220369389
16Linear Regression0.690770.4974713.19280.4825267.460401277124197199
17Pigskin Index0.683120.5021113.19470.9822262.218770526244357354
18Pi-Rate Ratings0.698700.5053113.20491.0277264.988770538232381373
19PI-Rate Bias0.710390.4953813.20861.1340264.793770547223375382
20Sagarin Ratings0.690910.4473713.25410.2903266.691770532238340420
21Edward Kambour0.709090.4815813.28060.6883265.528770546224366394
22Donchess Inference0.716880.4738313.28990.2138267.461770552218353392
23Versus Sports Simulator0.701430.4676413.32600.6634271.270767538229354403
24Talisman Red0.689940.4908113.34320.1340271.022716494222347360
25Sagarin Points0.692210.4585013.35170.2749270.378770533237348411
26Stat Fox0.687010.4903813.41172.1963274.644770529241357371
27Moore Power Ratings0.692210.4881613.42320.6346279.246770533237371389
28Keeper0.710350.5153113.42451.2305283.635763542221387364
29Massey Ratings0.690910.4828913.4370-0.0081276.138770532238367393
30ARGH Power Ratings0.716880.5000013.4558-0.1104281.555770552218369369
31Beck Elo0.696100.4947413.45830.7619284.370770536234376384
32Howell0.708330.4938913.5013-0.1457282.844768544224364373
33Dunkel Index0.676300.4978013.50551.3240279.919692468224340343
34Sagarin Golden Mean0.681820.4671113.51860.3441283.960770525245355405
35Born Power Index0.684420.4855313.54101.2933278.308770527243369391
36Sagarin Recent0.692210.4789513.56770.4317292.251770533237364396
37Massey Consensus0.728570.4874813.59831.2433283.608770561209370389
38Payne Power Ratings0.703900.4671113.6009-0.1149286.661770542228355405
39Roundtable0.692310.5019813.62660.7186293.881533369164253251
40Dave Congrove0.682700.5052813.72530.9936288.525769525244383375
41Catherwood Ratings0.770270.5000013.74320.6351276.443148114347070
42Laffaye RWP0.701410.5035913.86640.2000304.175710498212351346
43Payne Predict0.690910.4631613.86720.3339301.146770532238352408
44Daniel Curry Index0.689610.4671113.87910.1010298.036770531239355405
45Billingsley0.711690.4822113.88260.1543304.154770548222366393
46Stephen Kerns0.688310.5072513.90701.0216301.969770530240385374
47DP Dwiggins0.691910.4958913.92950.3133304.002766530236362368
48PerformanZ Ratings0.709090.4795814.02440.5273308.273770546224364395
49Payne W/L0.712990.4762514.3145-0.7173318.431770549221361397
50Cleanup Hitter0.668830.4731214.32280.8333319.305770515255352392
51Loudsound.org0.653950.4796214.7039-2.9618340.061760497263353383
52Super List0.712990.4993415.29311.5619355.876770549221378379
53Logistic Regression0.678300.4722215.4058-2.1711369.469401272129187209
54Least Squares w/ HFA0.665840.5151515.65820.6268372.986401267134204192
* This system does not make predictions.  I make predictions for this
  system by translating it to a new scale that allows for making predictions.



Retrodictive records are found by taking the ratings from the current week
and applying them to the entire season to date.

The ideal system would be one that has the highest correct game decisions,
has the smallest mean error(deviation from the actual game result), and has
a bias of zero.

Mean Error = average[abs(prediction-actual)]

      Bias = agerage(prediction - actual)

      Std. = Standard Deviation of individual game biases