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

2022 Season Totals

Through 2022-11-27
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Least Squares w/ HFA0.677420.5569114.45141.0497332.83324816880137109
2Logistic Regression0.671190.5445214.5062-0.7884374.87129519897159133
3Massey Ratings0.703600.5336112.49290.0154251.081722508214381333
4Donchess Inference0.709140.5185212.49770.5439251.702722512210364338
5Loudsound.org0.662940.5176013.9622-3.3273309.639715474241353329
6Laz Index0.694440.5168512.91210.4877264.879720500220368344
7Talisman Red0.696680.5160813.02000.2567274.034722503219369346
8Keeper0.698060.5154113.30971.7055284.757722504218368346
9Roundtable0.685770.5091613.05530.4545281.221506347159250241
10David Harville0.698060.5077112.54670.0799253.363722504218362351
11Sagarin Golden Mean0.688370.5076912.5364-0.0153253.214722497225363352
12Line (opening)0.713300.5058612.07830.7569235.339722515207302295
13Billingsley0.674060.5035113.50370.2184293.842721486235359354
14Waywardtrends0.684210.5028012.86480.8934266.965722494228359355
15ESPN FPI0.707690.5021212.33401.0923244.704715506209355352
16Sagarin Ratings0.713300.5007012.5120-0.1253250.226722515207358357
17Dave Congrove0.684210.5000013.04791.1467269.526722494228357357
18Daniel Curry Index0.684210.4993013.22730.7831282.547722494228357358
19Sagarin Points0.696680.4993012.5999-0.1295253.933722503219356357
20System Median0.698060.4985812.41270.5512247.265722504218351353
21Payne W/L0.666200.4950913.5750-0.2449295.967722481241353360
22Payne Power Ratings0.698060.4937112.90750.2387267.268722504218353362
23Dunkel Index0.697450.4935913.15971.2799282.044628438190308316
24FEI Projections0.681820.4893612.7222-1.9092263.996572390182276288
25System Average0.692520.4888012.48850.5760249.398722500222349365
26Laffaye RWP0.693110.4871413.5713-0.1791293.015668463205322339
27Pi-Rate Ratings0.713300.4858812.48181.1135251.789722515207344364
28Dokter Entropy0.711910.4852712.31291.1022242.662722514208346367
29Pi-Ratings Mean0.714680.4844212.40400.9838247.383722516206342364
30Bihl System0.673370.4835412.89600.6229273.924398268130191204
31Stat Fox0.690480.4831612.84742.2314263.709714493221330353
32Edward Kambour0.687500.4824712.70190.5940260.183720495225344369
33Sagarin Recent0.699450.4817912.7254-0.0133258.763722505217344370
34PI-Rate Bias0.706370.4803412.50551.1191252.336722510212342370
35ARGH Power Ratings0.682830.4802313.1551-0.0949278.659722493229328355
36Pigskin Index0.704990.4801812.62881.1083256.325722509213327354
37PerformanZ Ratings0.667590.4797214.17821.0210316.497722482240343372
38Stephen Kerns0.693910.4796114.07320.8059318.064722501221341370
39Linear Regression0.691530.4794513.07081.4479284.14729520491140152
40Line (updated)0.721610.4793712.08240.6669234.624722521201151164
41Beck Elo0.684210.4782613.21440.9240278.860722494228341372
42DP Dwiggins0.700830.4748213.3892-1.0789286.011722506216330365
43Moore Power Ratings0.683770.4740513.1911-0.0503277.159721493228338375
44Howell0.682830.4729113.46190.1601296.618722493229323360
45Born Power Index0.695290.4727313.11431.3616277.002722502220338377
46TeamRankings.com0.706370.4717512.46700.2687250.292722510212334374
47Massey Consensus0.691140.4671313.06551.5723278.857722499223334381
48Cleanup Hitter0.655120.4655214.10250.7549312.152722473249324372
49Versus Sports Simulator0.700970.4648912.81430.7919264.154719504215331381
50Payne Predict0.688370.4634813.27670.8472280.860722497225330382
51Computer Adjusted Line0.720220.4591312.11220.6496235.525722520202191225
52Catherwood Ratings0.674520.4544113.38092.0873283.677722487235314377
53Brent Craig0.703080.4512012.66891.2246254.986714502212319388
54Line (Midweek)0.7257612.06990.6406234.881722524198
* 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