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
1Massey Consensus0.728570.4874813.59831.2433283.608770561209370389
2Line (updated)0.718180.5000012.62470.4247245.711770553217165165
3Donchess Inference0.716880.4738313.28990.2138267.461770552218353392
4ARGH Power Ratings0.716880.5000013.4558-0.1104281.555770552218369369
5Dokter Entropy0.716510.4597113.14050.5041262.208769551218348409
6Laz Index0.714290.4868113.16090.6398263.527770550220369389
7Computer Adjusted Line0.712990.4767412.65910.4734246.306770549221205225
8Payne W/L0.712990.4762514.3145-0.7173318.431770549221361397
9Super List0.712990.4993415.29311.5619355.876770549221378379
10Line (Midweek)0.7116912.64290.4740246.300770548222
11Billingsley0.711690.4822113.88260.1543304.154770548222366393
12PI-Rate Bias0.710390.4953813.20861.1340264.793770547223375382
13PerformanZ Ratings0.709090.4795814.02440.5273308.273770546224364395
14Edward Kambour0.709090.4815813.28060.6883265.528770546224366394
15Pi-Ratings Mean0.709090.4939813.13661.0153261.875770546224369378
16Line (opening)0.707790.5000012.75260.2760251.696770545225337337
17Howell0.708330.4938913.5013-0.1457282.844768544224364373
18System Average0.706490.4861712.96460.5539255.949770544226369390
19Keeper0.710350.5153113.42451.2305283.635763542221387364
20TeamRankings.com0.703900.4827113.11300.7473263.278770542228363389
21David Harville0.703900.4591013.14670.2825262.413770542228348410
22Payne Power Ratings0.703900.4671113.6009-0.1149286.661770542228355405
23System Median0.701300.4741012.95980.5655255.160770540230357396
24Versus Sports Simulator0.701430.4676413.32600.6634271.270767538229354403
25ESPN FPI0.698700.4677213.02181.1573260.627770538232355404
26Pi-Rate Ratings0.698700.5053113.20491.0277264.988770538232381373
27Beck Elo0.696100.4947413.45830.7619284.370770536234376384
28Sagarin Points0.692210.4585013.35170.2749270.378770533237348411
29Sagarin Recent0.692210.4789513.56770.4317292.251770533237364396
30Moore Power Ratings0.692210.4881613.42320.6346279.246770533237371389
31Sagarin Ratings0.690910.4473713.25410.2903266.691770532238340420
32Massey Ratings0.690910.4828913.4370-0.0081276.138770532238367393
33Payne Predict0.690910.4631613.86720.3339301.146770532238352408
34Daniel Curry Index0.689610.4671113.87910.1010298.036770531239355405
35DP Dwiggins0.691910.4958913.92950.3133304.002766530236362368
36Stephen Kerns0.688310.5072513.90701.0216301.969770530240385374
37Stat Fox0.687010.4903813.41172.1963274.644770529241357371
38Born Power Index0.684420.4855313.54101.2933278.308770527243369391
39Pigskin Index0.683120.5021113.19470.9822262.218770526244357354
40Sagarin Golden Mean0.681820.4671113.51860.3441283.960770525245355405
41Dave Congrove0.682700.5052813.72530.9936288.525769525244383375
42Cleanup Hitter0.668830.4731214.32280.8333319.305770515255352392
43Laffaye RWP0.701410.5035913.86640.2000304.175710498212351346
44Loudsound.org0.653950.4796214.7039-2.9618340.061760497263353383
45Talisman Red0.689940.4908113.34320.1340271.022716494222347360
46Dunkel Index0.676300.4978013.50551.3240279.919692468224340343
47FEI Projections0.682770.5041213.03170.3315257.875621424197306301
48Roundtable0.692310.5019813.62660.7186293.881533369164253251
49Brent Craig0.708430.5194213.07990.5354263.541415294121214198
50Bihl System0.693240.4939213.07530.2528258.480414287127203208
51Linear Regression0.690770.4974713.19280.4825267.460401277124197199
52Logistic Regression0.678300.4722215.4058-2.1711369.469401272129187209
53Least Squares w/ HFA0.665840.5151515.65820.6268372.986401267134204192
54Catherwood Ratings0.770270.5000013.74320.6351276.443148114347070
* 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