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