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

2017 Last Week

Through 2018-01-09
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Sagarin Points0.675000.6923112.97431.4812299.5214027132712
2ThePowerRank.com0.600000.6923112.71751.2825288.0794024162712
3TeamRankings.com0.650000.6923112.97751.7325298.2914026142712
4Linear Regression0.600000.6666713.53002.2980319.3354024162613
5ComPughter Ratings0.631580.6486513.98002.4611348.7283824142413
6Talisman Red0.656250.6451612.97410.5578300.0583221112011
7The Sports Cruncher0.636360.6250012.9300-1.3730284.1073321122012
8Ashby AccuRatings0.675000.6216213.17501.1755302.8874027132314
9Sagarin Ratings0.725000.6153812.99751.2450304.0974029112415
10Edward Kambour0.675000.6153813.21630.9543296.4234027132415
11System Average0.625000.6153813.39431.4342309.4324025152415
12Stat Fox0.575000.6111113.87481.2258300.8374023172214
13System Median0.625000.6052613.28651.3195308.2604025152315
14Bihl System0.605260.5945913.81581.2221334.5783823152215
15Computer Adjusted Line0.600000.5925913.51250.8625295.4254024161611
16Born Power Index0.500000.5897414.14481.4303334.1874020202316
17PerformanZ Ratings0.600000.5897414.03630.7233339.1354024162316
18Atomic Football0.650000.5675713.00001.4500294.1474026142116
19Howell0.600000.5675713.81231.7627356.0274024162116
20Line (updated)0.600000.5652213.50000.8000293.4594024161310
21Donchess Inference0.650000.5641013.22331.3682308.5084026142217
22Laz Index0.575000.5641013.66381.2807318.6244023172217
23Sagarin Golden Mean0.675000.5641013.16201.4570304.6014027132217
24Moore Power Ratings0.525000.5641014.14000.6920323.2524021192217
25Loudsound.org0.641030.5555614.07690.5385340.9933925142016
26Stephen Kerns0.575000.5526314.32752.8775350.2434023172117
27FEI Projections0.650000.5526313.15002.2500299.6734026142117
28DP Dwiggins0.550000.5526314.24982.3498368.3604022182117
29Liam Bressler0.473680.5405413.58661.4608307.9633818202017
30Dokter Entropy0.575000.5384613.58151.3425316.0824023172118
31Least Squares w/ HFA0.600000.5384615.79334.5727416.5734024162118
32ARGH Power Ratings0.700000.5384613.70001.4125338.0064028122118
33Payne Power Ratings0.675000.5384613.61381.0353337.6264027132118
34Dave Congrove0.600000.5384613.29331.9327284.0874024162118
35Super List0.675000.5384613.95452.5890366.4864027132118
36Laffaye RWP0.625000.5384613.77650.9945323.4294025152118
37ESPN FPI0.625000.5384613.39401.1685299.3114025152118
38Massey Ratings0.650000.5384613.53201.5345315.0074026142118
39NutShell Sports0.650000.5384614.62101.6585376.6134026142118
40Sagarin Recent0.600000.5384613.57850.7330324.8174024162118
41Roundtable0.615380.5263214.10261.0256343.2043924152018
42Brent Craig0.564100.5263213.95822.5382335.5123922172018
43Lee Burdorf0.487180.5135114.89490.8077346.8993919201918
44Logistic Regression0.600000.5128214.3945-0.9840359.7974024162019
45Billingsley0.525000.5128214.78080.3247365.2364021192019
46Pi-Ratings Mean0.550000.5128213.35751.8775310.8164022182019
47Keeper0.625000.5128213.99151.5740324.7424025152019
48Marsee0.550000.4736814.45001.5500339.9904022181820
49Pi-Rate Ratings0.525000.4615413.74252.0375324.8054021191821
50Beck Elo0.575000.4615413.67700.8750322.3584023171821
51Cleanup Hitter0.525000.4615415.45000.5750335.9424021191821
52Billingsley+0.475000.4615414.97250.5230383.9694019211821
53Daniel Curry Index0.500000.4615415.48151.7450370.9104020201821
54Catherwood Ratings0.525000.4473714.32501.2750321.4344021191721
55Massey Consensus0.525000.4102616.38171.5152397.6494021191623
56Dunkel Index0.600000.4102614.73201.6530358.5354024161623
57Line (opening)0.450000.4074114.07501.0750323.8714018221116
58Pigskin Index0.475000.3947414.70050.5505356.4054019211523
59PI-Rate Bias0.500000.3846213.76752.0475325.6364020201524
60Line (Midweek)0.5250013.75000.8000309.047402119
* 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