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