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

2022 Season Totals

Through 2023-01-10
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1ARGH Power Ratings0.675260.4789113.0938-0.0512276.669776524252352383
2Beck Elo0.677840.4803713.13710.8316277.478776526250367397
3Bihl System0.673170.4815712.86940.7020271.105410276134196211
4Billingsley0.664520.5026113.43790.1611292.406775515260385381
5Born Power Index0.694590.4791713.03841.2843276.156776539237368400
6Brent Craig0.703300.4549212.67821.2032256.102728512216328393
7Catherwood Ratings0.677840.4614313.26681.9858281.530776526250341398
8Cleanup Hitter0.648200.4699614.00450.5626310.485776503273352397
9Computer Adjusted Line0.713920.4690312.09210.5844234.884776554222212240
10Daniel Curry Index0.685640.5006513.16720.7610280.958773530243383382
11Dave Congrove0.684280.5071712.93430.9805267.934776531245389378
12David Harville0.694590.5091412.49660.0855253.125776539237390376
13Dokter Entropy0.703610.4908612.27911.0174243.062776546230376390
14Donchess Inference0.701030.5218512.45160.4972250.995776544232394361
15DP Dwiggins0.692900.4865613.2723-0.9342283.183775537238362382
16Dunkel Index0.696480.4963113.07131.2361279.665682475207336341
17Edward Kambour0.688630.4856412.66170.5814259.395774533241372394
18ESPN FPI0.703510.5052612.27330.9943244.335769541228384376
19FEI Projections0.675720.4943312.6622-1.6793261.959626423203305312
20Howell0.676550.4768413.41240.2463294.056776525251350384
21Keeper0.695480.5248013.15671.6739279.270775539236402364
22Laffaye RWP0.682830.4803913.5330-0.0155291.424722493229343371
23Laz Index0.688630.5189512.84010.4397263.631774533241397368
24Least Squares w/ HFA0.662250.5351214.37191.5603327.602302200102160139
25Line (Midweek)0.7203612.05990.5664234.538776559217
26Line (opening)0.706190.5077912.08050.6617236.294776548228326316
27Line (updated)0.715210.4928012.06510.6012233.847776555221171176
28Linear Regression0.684810.4956512.85461.3205278.097349239110171174
29Logistic Regression0.647560.5362314.2849-0.8567362.924349226123185160
30Loudsound.org0.664350.5167913.9540-3.3022309.256718477241354331
31Massey Consensus0.681700.4700513.04111.4341279.200776529247361407
32Massey Ratings0.697160.5319412.4786-0.0418251.724776541235408359
33Moore Power Ratings0.680000.4817213.1106-0.0252276.591775527248369397
34Payne Power Ratings0.688140.4947912.86810.2151267.004776534242380388
35Payne Predict0.684280.4732013.15130.7929278.935776531245362403
36Payne W/L0.658510.4895613.5289-0.2410295.208776511265375391
37PerformanZ Ratings0.666240.4856814.00260.9886310.134776517259373395
38PI-Rate Bias0.702320.4902012.46051.0799251.311776545231375390
39Pi-Rate Ratings0.711340.4921112.43841.0485251.072776552224374386
40Pi-Ratings Mean0.711340.4920812.36400.9370246.959776552224373385
41Pigskin Index0.702320.4897112.56571.0377255.484776545231357372
42Roundtable0.683400.5029813.04440.5502279.380518354164253250
43Sagarin Golden Mean0.680410.5065112.5151-0.0336253.531776528248389379
44Sagarin Points0.689430.5039212.5489-0.1454253.307776535241386380
45Sagarin Ratings0.707470.5065112.4622-0.1380249.689776549227389379
46Sagarin Recent0.699740.4915312.6528-0.0329257.407776543233377390
47Stat Fox0.690100.4925212.74492.0602262.238768530238362373
48Stephen Kerns0.690720.4842913.89670.7545312.164776536240370394
49System Average0.688140.4993512.43380.5424248.770776534242383384
50System Median0.693300.5085912.36080.5109246.750776538238385372
51Talisman Red0.692010.5234412.92520.2529271.807776537239402366
52TeamRankings.com0.703610.4789512.39570.2530249.400776546230364396
53Versus Sports Simulator0.697280.4758212.73390.7699262.842773539234364401
54Waywardtrends0.684280.5110812.77760.8167264.981776531245392375
* 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