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

2014 Second Half Totals

Through 2015-01-13
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Ashby AccuRatings0.731590.5329812.89310.4325267.211421308113202177
2Line (Midweek)0.7146312.92070.8183268.249410293117
3Line (opening)0.699280.5294112.92120.4988266.518419293126180160
4Line (updated)0.717340.5288112.94540.9477266.800421302119156139
5Computer Adjusted Line0.717340.5205012.95960.8575266.877421302119165152
6Thompson CAL0.722090.5245112.96480.6618266.308421304117214194
7Thompson Average0.714960.5320213.05430.4857269.285421301120216190
8DirectorOfInformation0.719710.5024513.06240.2684273.286421303118205203
9Thompson ATS0.717340.5024513.08600.6209270.603421302119205203
10System Median0.719710.5350013.08950.3080271.540421303118214186
11Dokter Entropy0.714960.5049013.10260.8485269.011421301120206202
12System Average0.712590.5208813.10910.3393272.426421300121212195
13Stephen Kerns0.714960.5187013.13660.1153273.012421301120208193
14Sagarin Ratings0.726840.5405413.14330.6402273.734421306115220187
15Atomic Football0.712590.5398913.19950.5819279.655421300121203173
16Donchess Inference0.703090.5184313.20760.2152275.788421296125211196
17Sagarin Points0.714960.4938613.21230.7641277.773421301120201206
18Sagarin Golden Mean0.724470.5269613.21970.7225277.833421305116215193
19Billingsley+0.724470.5441213.23010.1147279.158421305116222186
20Pigskin Index0.717340.5483013.2424-0.0922279.052421302119210173
21CPA Rankings0.731590.5049013.2431-0.4419278.176421308113206202
22Sagarin Points Elo0.731590.5185213.30180.3586279.550421308113210195
23Massey Consensus0.717340.5490213.31330.4597280.955421302119224184
24Payne Power Ratings0.735710.5369513.3613-0.7122282.787420309111218188
25Massey Ratings0.714960.5234413.3658-0.3064285.138421301120201183
26Pi-Ratings Mean0.693590.5062013.36620.0609279.121421292129204199
27PerformanZ Ratings0.705460.5294113.36640.6261279.334421297124216192
28Edward Kambour0.714960.5122513.36930.7713283.572421301120209199
29Pi-Rate Ratings0.698340.5333313.38130.2473286.081421294127216189
30Laz Index0.714960.5024513.3845-0.0067282.007421301120205203
31ARGH Power Ratings0.726840.5282113.39010.6502283.474421306115206184
32PI-Rate Bias0.695960.5123213.39710.2115284.679421293128208198
33Stat Fox0.733970.5180413.43951.5538284.597421309112201187
34Covers.com0.714960.5420813.4449-0.2154291.280421301120219185
35Howell0.714290.5155413.45350.2227287.045420300120199187
36Bihl System0.706440.4975413.46850.7592284.322419296123202204
37Regression Based Analys0.729640.5304713.48531.9674298.95230722483148131
38Keeper0.701670.4926113.49681.4262280.207419294125200206
39Born Power Index0.722090.5343113.50260.3003288.662421304117218190
40Linear Regression0.688350.5112413.5403-0.4773287.299369254115182174
41Billingsley0.700710.5318613.5492-0.1508297.315421295126217191
42ThePowerRank.com0.694710.4975113.54980.1344286.417416289127200202
43Dave Congrove0.748220.5147113.55370.2537300.298421315106210198
44Laffaye RWP0.710210.5441213.5657-1.6667299.276421299122222186
45Catherwood Ratings0.713600.5253813.61341.3604286.783419299120207187
46Moore Power Ratings0.712590.5380813.63960.6870296.684421300121219188
47Tempo Free Gridiron0.723130.5411013.6482-1.7134314.80530722285158134
48Marsee0.703090.4924613.66032.1971292.680421296125196202
49ComPughter Ratings0.694510.5049313.7075-0.3436293.888419291128205201
50Cleanup Hitter0.698250.5051513.71201.5798312.911401280121196192
51MDS Model0.700580.5045013.7147-0.2503300.594344241103168165
52Beck Elo0.691210.5258013.75410.4671295.399421291130214193
53NutShell Combo0.710210.5246313.78130.0451303.199421299122213193
54Lee Burdorf0.700710.4889413.79380.6742300.412421295126199208
55Loudsound.org0.689460.5625013.8176-3.4239316.756351242109189147
56Daniel Curry Index0.721430.5295613.82260.4498300.269420303117215191
57PointShare0.672210.5024613.8475-0.9520302.783421283138204202
58Nutshell Eye0.684090.5174113.8560-0.0618310.448421288133208194
59Randal Horobik0.730160.4891813.85720.2977301.68125218468113118
60Brent Craig0.683330.4963113.87490.6808297.249420287133202205
61DP Dwiggins0.693070.4408613.88121.0297293.91010170314152
62NutShell Sports0.695960.5111713.9946-0.0798311.339421293128206197
63Dunkel Index0.710530.4839514.06161.1671309.021418297121196209
64Sportrends0.678280.5226014.06301.0791309.786373253120185169
65Nutshell Girl0.691210.4730414.16230.2815323.692421291130193215
66FEI Projections0.674580.5076514.2518-0.7838323.376421284137199193
67CPA Retro0.660330.4852914.5276-0.9322324.421421278143198210
68Super List0.676960.5392214.67570.3789339.487421285136220188
69Least Squares w/ HFA0.666670.5322115.45410.0537375.347369246123190167
70Logistic Regression0.685640.5546215.7456-2.8696389.856369253116198159
71Brent Craig 20.692310.3137316.09383.1962373.6445236161635
72Laffaye XWP0.688840.4851516.27966.6292413.606421290131196208
* 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