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