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

2014 Season Totals

Through 2015-01-13
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Line (updated)0.736840.5233512.47701.3191249.765760560200269245
2Line (Midweek)0.7326212.49731.2580252.051748548200
3Computer Adjusted Line0.735530.5132312.50661.2500250.262760559201291276
4Line (opening)0.720320.5225812.55470.9453251.703758546212324296
5Thompson CAL0.739470.5081112.57491.1438251.332760562198376364
6Thompson ATS0.736840.5067612.62680.9076253.703760560200375365
7Thompson Average0.731580.5027212.70091.0303256.739760556204370366
8Dokter Entropy0.730260.4966212.77481.2805257.344760555205367372
9Ashby AccuRatings0.728950.5072012.77900.7397260.553760554206352342
10Pi-Ratings Mean0.717110.5382512.81050.6926260.100760545215394338
11System Median0.730260.5151512.82450.8342261.095760555205374352
12System Average0.722370.5081312.85530.8323262.563760549211375363
13Atomic Football0.722370.5099712.89971.1315265.172760549211358344
14PI-Rate Bias0.718420.5313412.93250.9499266.871760546214390344
15Pi-Rate Ratings0.722370.5359612.95601.0500269.513760549211395342
16Pigskin Index0.732890.5100312.96580.5319268.003760557203356342
17Sagarin Points0.728950.4857913.01631.3367271.817760554206359380
18DirectorOfInformation0.726320.4973013.02800.5673271.395760552208368372
19Sagarin Ratings0.734210.4966213.07981.2648270.887760558202367372
20ThePowerRank.com0.704850.5034713.10380.4475274.416742523219363358
21Billingsley+0.731580.5216213.17330.3666279.161760556204386354
22Massey Consensus0.726320.5189213.21871.0745277.300760552208384356
23CPA Rankings0.734210.5027013.22780.4700273.204760558202372368
24Laz Index0.709210.5108113.23910.2984276.767760539221378362
25Massey Ratings0.703880.5079913.2848-0.0307282.541618435183286277
26Brent Craig 20.730880.4781313.29414.5184281.04835325895164179
27Edward Kambour0.722300.5006913.32391.1352282.256749541208365364
28ComPughter Ratings0.708440.5027113.33540.4806280.579758537221371367
29Payne Power Ratings0.728590.5162613.35950.3545282.559759553206381357
30Stat Fox0.728950.4943513.37111.8056285.530760554206350358
31Sagarin Golden Mean0.726320.5027013.39051.2257281.650760552208372368
32NutShell Combo0.708620.5098413.44950.4232290.404580411169285274
33Donchess Inference0.697890.5047513.46600.2313286.376758529229372365
34Bihl System0.690830.4945113.49131.1259282.167469324145225230
35ARGH Power Ratings0.721050.5028213.49511.0266285.106760548212357353
36Brent Craig0.703170.4816813.51861.3501284.228758533225355382
37Sagarin Points Elo0.725000.5061113.51981.0935289.009760551209373364
38Loudsound.org0.690770.5639713.5236-3.1740303.556401277124216167
39Linear Regression0.688350.5112413.5403-0.4773287.299369254115182174
40Nutshell Eye0.687930.5054313.54810.5517294.092580399181279273
41Dunkel Index0.726550.5047513.58281.4209303.465757550207372365
42Billingsley0.718420.5189213.58350.0035299.722760546214384356
43Howell0.705800.5106713.64050.6208294.962758535223359344
44Lee Burdorf0.712400.4938813.65390.8791292.789758540218363372
45Tempo Free Gridiron0.713620.5258913.6579-1.2368309.315646461185325293
46DP Dwiggins0.749350.4517913.67621.4726293.43038328796164199
47Catherwood Ratings0.720320.5014013.67811.5831296.065758546212357355
48Moore Power Ratings0.717310.4904913.68381.1843297.639757543214361375
49Covers.com0.698680.5286913.7098-0.2118303.723760531229387345
50Beck Elo0.701280.4905113.73050.8736291.916703493210336349
51Stephen Kerns0.705160.4872513.7344-0.0158293.368736519217344362
52Randal Horobik0.734350.4780213.73601.1337291.875591434157261285
53Keeper0.711080.4850913.74012.0397291.578758539219358380
54Dave Congrove0.732890.4891913.75050.3377306.783760557203362378
55FEI Projections0.687750.5098313.77470.1225302.117759522237363349
56Nutshell Girl0.711910.4800613.78950.8216306.373722514208337365
57PerformanZ Ratings0.698680.5027013.86220.7613302.269760531229372368
58PointShare0.655170.5089613.8665-0.0945302.334580380200284274
59Laffaye RWP0.700000.5405413.8757-1.5578311.392760532228400340
60Regression Based Analys0.724460.4784113.89162.3003309.165646468178288314
61Born Power Index0.711840.4973013.89170.9360302.254760541219368372
62MDS Model0.708210.5045213.89810.0988309.047682483199335329
63Marsee0.698680.4777813.99212.6526307.843760531229344376
64NutShell Sports0.708440.5103414.00850.0378316.792758537221370355
65Cleanup Hitter0.706720.5059014.17612.3361336.343699494205343335
66CPA Retro0.686840.4891914.21340.2496312.580760522238362378
67Daniel Curry Index0.714100.4993214.31450.8363323.839759542217368369
68Sportrends0.685160.5134714.33730.0255332.841667457210324307
69Super List0.690790.5331514.55720.9633335.618760525235394345
70Least Squares w/ HFA0.666670.5322115.45410.0537375.347369246123190167
71Logistic Regression0.685640.5546215.7456-2.8696389.856369253116198159
72Laffaye XWP0.692110.4782616.52096.7767425.075760526234352384
* 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