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