Computer Rating System Prediction Results for College Football (NCAA IA)
2014 Retrodiction Results
Through
Rank |
System |
Pct. Correct |
Against Spread |
Absolute Error |
Bias |
Mean Square Error |
games |
suw |
sul |
atsw |
atsl |
1 | Least Squares w/ HFA | 0.82632 | 0.00000 | 9.2885 | 0.0512 | 135.151 | 760 | 628 | 132 | 0 | 0 |
2 | Covers.com | 0.77895 | 0.00000 | 11.8271 | 0.0870 | 224.369 | 760 | 592 | 168 | 0 | 0 |
3 | NutShell Sports | 0.78947 | 0.00000 | 11.9673 | 0.1682 | 231.625 | 760 | 600 | 160 | 0 | 0 |
4 | Stortrends | 0.76612 | 0.00000 | 11.5045 | 0.2327 | 208.121 | 667 | 511 | 156 | 0 | 0 |
5 | Payne Power Ratings | 0.81579 | 0.00000 | 11.0928 | -0.2774 | 195.876 | 760 | 620 | 140 | 0 | 0 |
6 | Beck Elo | 0.80263 | 0.00000 | 11.1433 | 0.3585 | 199.185 | 760 | 610 | 150 | 0 | 0 |
7 | NutShell Combo | 0.79079 | 0.00000 | 11.5542 | 0.4336 | 223.363 | 760 | 601 | 159 | 0 | 0 |
8 | Sagarin Predictive | 0.78947 | 0.00000 | 10.6223 | 0.5138 | 179.152 | 760 | 600 | 160 | 0 | 0 |
9 | Sagarin | 0.80921 | 0.00000 | 10.5521 | 0.5754 | 179.995 | 760 | 615 | 145 | 0 | 0 |
10 | Laz Index | 0.77895 | 0.00000 | 10.8580 | 0.6309 | 189.538 | 760 | 592 | 168 | 0 | 0 |
11 | Nutshell Girl | 0.77105 | 0.00000 | 11.8099 | 0.6992 | 237.484 | 760 | 586 | 174 | 0 | 0 |
12 | Sagarin Elo | 0.83289 | 0.00000 | 11.3897 | 0.7004 | 208.562 | 760 | 633 | 127 | 0 | 0 |
13 | System Average | 0.80658 | 0.00000 | 10.7080 | 0.7210 | 184.020 | 760 | 613 | 147 | 0 | 0 |
14 | CPA Retro | 0.79342 | 0.00000 | 11.7421 | 0.7469 | 229.051 | 760 | 603 | 157 | 0 | 0 |
15 | SuperList | 0.75658 | 0.00000 | 12.5472 | 0.7683 | 256.469 | 760 | 575 | 185 | 0 | 0 |
16 | system Median | 0.80263 | 0.00000 | 10.6445 | 0.7746 | 182.142 | 760 | 610 | 150 | 0 | 0 |
17 | CPA Rankings | 0.79211 | 0.00000 | 10.5370 | 0.7913 | 176.040 | 760 | 602 | 158 | 0 | 0 |
18 | Least Squares | 0.80000 | 0.00000 | 10.4506 | 0.8218 | 173.854 | 760 | 608 | 152 | 0 | 0 |
19 | Pigskin Index | 0.76579 | 0.00000 | 11.1697 | 0.8485 | 199.925 | 760 | 582 | 178 | 0 | 0 |
20 | PerformanZ Ratings | 0.78947 | 0.00000 | 11.2891 | 0.8602 | 198.884 | 760 | 600 | 160 | 0 | 0 |
21 | Sonny Moore | 0.78684 | 0.00000 | 11.1638 | 0.9848 | 196.186 | 760 | 598 | 162 | 0 | 0 |
22 | Massey Concensus Rank | 0.81447 | 0.00000 | 11.0212 | 0.9871 | 197.717 | 760 | 619 | 141 | 0 | 0 |
23 | Edward Kambour | 0.78026 | 0.00000 | 10.6716 | 1.1649 | 182.119 | 760 | 593 | 167 | 0 | 0 |
24 | Born Power Index | 0.79079 | 0.00000 | 10.9884 | 1.4090 | 192.659 | 760 | 601 | 159 | 0 | 0 |
25 | Ashby AccuRatings | 0.77368 | 0.00000 | 10.9395 | 1.7062 | 193.157 | 760 | 588 | 172 | 0 | 0 |
26 | Logistic Regression | 0.83421 | 0.00000 | 15.3849 | -1.7076 | 639.423 | 760 | 634 | 126 | 0 | 0 |
27 | Stat Fox | 0.76053 | 0.00000 | 11.1237 | 1.9051 | 192.928 | 760 | 578 | 182 | 0 | 0 |
* 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