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

2021 Second Half Totals

Through 2021-12-05
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Roundtable0.740070.5153812.57400.1986243.75827720572134126
2Massey Consensus0.737570.4636913.42311.0790275.44236226795166192
3PerformanZ Ratings0.734810.4846813.29381.1753274.88136226696174185
4Billingsley0.726520.4484713.77320.5301295.03336226399161198
5Keeper0.726520.5195513.18301.2832270.62736226399186172
6Payne Predict0.726520.4930412.90090.2285259.05936226399177182
7ARGH Power Ratings0.723760.4770113.12290.3052263.912362262100166182
8Payne W/L0.720990.4553113.9167-0.4852295.302362261101163195
9Super List0.720990.5000015.22461.0901352.415362261101179179
10Howell0.719440.4726213.14580.1904260.867360259101164183
11Line (updated)0.718230.4193512.52210.3840243.7123622601025272
12Laz Index0.718230.4986112.84140.5660253.302362260102179180
13DP Dwiggins0.715880.5000012.95541.0891261.103359257102173173
14Line (opening)0.715470.5268112.53040.2928245.960362259103167150
15Sagarin Points0.715470.4581012.86420.2136251.527362259103164194
16Brent Craig0.715470.5264612.92200.6982258.763362259103189170
17TeamRankings.com0.712710.5423712.65080.6194249.794362258104192162
18Dokter Entropy0.712710.4733912.86280.9058258.267362258104169188
19ESPN FPI0.712710.4804512.72511.2501253.788362258104172186
20Edward Kambour0.709940.4818912.81920.4270249.943362257105173186
21PI-Rate Bias0.709940.5097512.89320.7599255.343362257105183176
22Versus Sports Simulator0.709940.4846812.96960.4108258.153362257105174185
23Moore Power Ratings0.709940.5069613.13630.8668268.911362257105182177
24Laffaye RWP0.707790.4852513.59670.8251286.14830821890148157
25Payne Power Ratings0.707180.4651813.2370-0.2399269.025362256106167192
26Linear Regression0.707180.5069613.05210.2023260.289362256106182177
27Donchess Inference0.707180.4715913.04730.6147260.831362256106166186
28David Harville0.707180.4636912.79400.2059250.270362256106166192
29Line (Midweek)0.7071812.48340.4530242.906362256106
30System Average0.707180.4958212.65650.5963245.391362256106178181
31Pi-Ratings Mean0.707180.5000012.89500.7210253.865362256106176176
32Computer Adjusted Line0.704420.4418612.53590.4365243.3963622551077696
33FEI Projections0.704420.5070012.80140.0914248.857362255107181176
34Bihl System0.704420.4986112.92440.2093254.904362255107179180
35Stephen Kerns0.704420.5027913.08770.8369257.512362255107180178
36Daniel Curry Index0.704420.4735413.18770.3151263.870362255107170189
37Sagarin Ratings0.701660.4345412.81240.2092247.906362254108156203
38Beck Elo0.701660.5069613.08540.9386263.108362254108182177
39Massey Ratings0.698900.4735413.08760.1975258.765362253109170189
40Sagarin Golden Mean0.696130.4596112.91100.2220251.715362252110165194
41Pigskin Index0.693370.4969912.93360.6745254.762362251111165167
42Sagarin Recent0.693370.4791112.95750.1950256.779362251111172187
43Pi-Rate Ratings0.693370.5112412.90750.6953255.836362251111182174
44System Median0.693370.4930012.68330.5408246.394362251111176181
45Talisman Red0.692520.4888312.9714-0.0088259.714361250111175183
46Loudsound.org0.688390.4736813.6884-2.4759280.323353243110162180
47Dunkel Index0.687850.4902513.02960.9754256.963362249113176183
48Born Power Index0.687850.4986113.05981.1018262.691362249113179180
49Logistic Regression0.687850.4624015.5402-2.4646375.449362249113166193
50Least Squares w/ HFA0.687850.5208915.63910.2504371.884362249113187172
51Dave Congrove0.686980.5154113.26341.0123270.447361248113184173
52Stat Fox0.685080.5000013.04982.3151263.710362248114172172
53Cleanup Hitter0.665750.4668614.41710.8539318.649362241121162185
* 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