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

2009 Last Week

Through
Rank System Pct. Correct Against Spread Absolute Error Bias Mean Square Error games suw sul atsw atsl
1Massey *0.794120.818189.54263.5397156.53734277276
2Hank Trexler0.676470.5312512.94124.2353274.9433423111715
3CPA Retro0.647060.6060612.23214.9915235.3693422122013
4Edward Kambour0.647060.6060612.42764.6224245.8123422122013
5PerformanZ Ratings0.647060.5757613.33565.4809271.9023422121914
6ARGH Power Ratings0.617650.5806512.66915.1985258.0053421131813
7Nutshell Girl0.617650.6060611.86763.6406240.0443421132013
8Tom Benson0.606060.6562513.39825.6012273.0363320132111
9NutShell Combo0.588240.6363612.71564.5479274.9753420142112
10Least Squares w/ HFA0.588240.4545515.31007.9982387.7603420141518
11Marsee0.575760.5151513.63644.4848306.4813319141716
12Sagarin Predictive0.558820.6060613.03765.3565272.7203419152013
13System Average0.558820.5151512.83505.0597269.4243419151716
14Dave Congrove0.558820.6060612.81625.0744282.4533419152013
15Billingsley0.558820.6969712.52654.0265257.2523419152310
16Howell0.558820.6250012.30944.5153248.4483419152012
17Moore Power Ratings0.529410.5757613.54825.3788304.7993418161914
18Pigskin Index0.529410.5312513.58824.5882301.0283418161715
19NationalSportsRankings0.529410.5151513.61715.2653304.3803418161716
20NutShell Sports0.529410.5151514.00565.4250321.4993418161716
21Lee Burdorf0.529410.5151514.29414.7824335.4173418161716
22Keeper0.529410.3636414.38596.0547362.6253418161221
23Born Power Index0.529410.3871014.39155.5562342.8013418161219
24Beck Elo0.529410.5454513.49004.6135279.1853418161815
25Atomic Football0.529410.4848513.12295.4918279.8123418161617
26Line (opening)0.529410.5312513.11765.6471292.1503418161715
27Billingsley+0.529410.6666712.71006.1471280.8663418162211
28Covers.com0.529410.6060612.71503.4879266.4373418162013
29System Median0.529410.5000012.80795.0891266.1003418161616
30Anderson/Hester *0.529410.6060612.84854.2038270.9313418162013
31Schmidt Comp. Ratings0.529410.5757612.96504.4297260.5453418161914
32Warren Claassen0.529410.4848512.97714.8035270.4123418161617
33Frank Alder0.529410.5454513.11534.6588275.6013418161815
34Stephen Kerns0.500000.5757614.62127.2194338.9483417171914
35Sportrends0.500000.5483914.07354.3676319.8433417171714
36Stat Fox0.500000.4827614.05976.0597321.1183417171415
37Linear Regression0.500000.5151514.01945.7500299.1803417171716
38CPA Rankings0.500000.5000013.66415.5806293.3643417171616
39CF By the Numbers0.500000.5000013.50005.1471279.7213417171515
40Bihl System0.500000.5151513.39945.3406277.5493417171716
41Line (updated)0.5000013.11766.2941290.717341717
42Payne Power Ratings0.500000.5454513.10914.8526271.6863417171815
43Computer Adjusted Line0.500000.6428613.04416.1029287.05934171795
44Sagarin Elo0.500000.5757612.92125.0300263.8563417171914
45Super List0.470590.5151513.86656.6818306.2903416181716
46Laz Index0.470590.4545513.48244.7929289.4803416181518
47Dokter Entropy0.470590.5454513.29684.9015276.8283416181815
48Massey Consensus0.470590.5757613.15445.1021280.7043416181914
49Wolfe *0.470590.5757613.06655.1682274.8543416181914
50Martien Maas0.470590.5757612.93064.4629271.7953416181914
51Dunkel Index0.441180.3333314.60716.1347348.7053415191122
52Bassett Model0.441180.5151514.16886.0806307.9533415191716
53Harmon Forcast0.441180.4516113.94125.3529300.1573415191417
54Ashby AccuRatings0.441180.5161313.41185.6471300.5913415191615
55Sagarin0.441180.5454513.02945.1782262.8163415191815
56Logistic Regression0.441180.6666712.55262.7774248.8453415192211
57Catherwood Ratings0.411760.4838714.58825.5882336.6703414201516
58Colley Rankings *0.382350.5757613.05504.6485273.2413413211914

* 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