ThePredictionTracker NCAA RESULTS

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

2008 Last Week

System	Pct. Correct	Against Spread	Absolute Error	Bias	Mean Square Error	games	suw	sul	atsw	atsl
NutShell Sports	0.76471	0.57576	10.0309	-0.0138	173.370	34	26	8	19	14
Born Power Index	0.67647	0.60606	10.2794	-0.5147	180.981	34	23	11	20	13
CPA Rankings	0.70588	0.60606	10.6450	-0.6391	181.953	34	24	10	20	13
Bassett Model	0.67647	0.63636	10.3415	-0.8268	184.169	34	23	11	21	12
NutShell Retro	0.73529	0.60606	10.8026	0.8679	185.430	34	25	9	20	13
Stat Fox	0.61765	0.55172	10.7941	-0.6759	186.018	34	21	13	16	13
Atomic Football	0.67647	0.57576	10.6971	-0.5894	186.764	34	23	11	19	14
Edward Kambour	0.67647	0.57576	10.4726	-1.5615	188.077	34	23	11	19	14
Stephen Kerns	0.64706	0.63636	10.0709	-0.1856	189.341	34	22	12	21	12
Moore Power Ratings	0.73529	0.57576	10.2962	-1.2462	189.845	34	25	9	19	14
Ashby AccuRatings	0.64706	0.48276	11.0879	-0.9703	198.220	34	22	12	14	15
Laz Index	0.67647	0.60606	10.8041	-1.0918	198.285	34	23	11	20	13
Dave Congrove	0.61765	0.45455	11.4341	-1.4341	203.324	34	21	13	15	18
Sportrends	0.70588	0.66667	10.2059	-1.3765	204.785	34	24	10	22	11
Line (updated)	0.61765		10.9853	-0.3676	204.812	34	21	13
Computer Adjusted Line	0.58824	0.38462	11.0588	-0.5000	205.963	34	20	14	5	8
Sagarin Predictive	0.55882	0.54545	11.2815	-2.0562	206.851	34	19	15	18	15
Linear Regression	0.67647	0.42424	11.3444	-0.8509	210.478	34	23	11	14	19
Dokter Entropy	0.64706	0.51515	11.3721	-0.4938	215.465	34	22	12	17	16
Lee Burdorf	0.58824	0.46875	11.4147	-1.9971	218.939	34	20	14	15	17
Keeper	0.64706	0.51515	11.1291	-0.9532	219.099	34	22	12	17	16
System Average	0.61765	0.48485	11.3900	-1.4259	220.183	34	21	13	16	17
Line (opening)	0.52941	0.43333	11.5147	-0.1029	223.492	34	18	16	13	17
Nutshell Girl	0.67647	0.54545	11.2347	-1.4965	224.145	34	23	11	18	15
System Median	0.61765	0.46875	11.4129	-1.3282	224.168	34	21	13	15	17
Covers.com	0.73529	0.48485	11.5468	-1.4350	225.423	34	25	9	16	17
Bihl System	0.64706	0.42424	11.7526	-1.4391	226.050	34	22	12	14	19
PerformanZ Ratings	0.58824	0.33333	12.2959	-2.1112	227.284	34	20	14	11	22
Least Squares w/ HFA	0.61765	0.63636	12.1876	2.8982	227.568	34	21	13	21	12
Pigskin Index	0.61765	0.50000	11.2347	-1.7629	229.645	34	21	13	14	14
Dunkel Index	0.58824	0.45455	11.2276	0.5665	234.700	34	20	14	15	18
Hank Trexler	0.52941	0.25926	12.0294	-1.9706	235.268	34	18	16	7	20
Sagarin	0.50000	0.39394	12.4206	-1.8906	238.863	34	17	17	13	20
Massey BCS *	0.58824	0.42424	12.0538	-1.2015	244.763	34	20	14	14	19
Harmon Forcast	0.55882	0.29032	12.7941	-0.6765	247.722	34	19	15	9	22
Marsee	0.44118	0.33333	12.4118	-1.9412	249.889	34	15	19	11	22
Massey Consensus	0.47059	0.48485	12.4450	-2.2138	250.307	34	16	18	16	17
Beck Elo	0.44118	0.48485	12.8035	-1.6400	256.401	34	15	19	16	17
Warren Claassen	0.55882	0.42424	12.9662	-2.0344	257.229	34	19	15	14	19
DP Dwiggins	0.50000	0.36364	13.1159	-1.8865	261.483	34	17	17	12	21
ARGH Power Ratings	0.44118	0.46875	12.5074	-1.9632	271.962	34	15	19	15	17
Imes Comprank	0.39394	0.43750	12.7585	-1.4615	273.735	33	13	20	14	18
Anderson/Hester *	0.47059	0.36364	13.3253	-2.2671	275.071	34	16	18	12	21
Sagarin Elo	0.44118	0.39394	13.5385	-1.6591	282.815	34	15	19	13	20
Colley Rankings *	0.47059	0.36364	13.6924	-2.3741	284.983	34	16	18	12	21
CPA Retro	0.47059	0.45455	13.5318	-0.4588	290.703	34	16	18	15	18
Martien Maas	0.50000	0.36364	13.9174	-2.0291	298.294	34	17	17	12	21
Billingsly	0.44118	0.36364	13.4662	-0.9709	298.648	34	15	19	12	21
Howell	0.47059	0.31250	13.7788	-1.5141	313.938	34	16	18	10	22
Super List	0.47059	0.45455	13.5421	-1.4362	318.979	34	16	18	15	18
Wolfe *	0.41176	0.33333	14.4550	-1.8979	322.046	34	14	20	11	22
Logistic Regression	0.47059	0.42424	14.8032	-1.8697	334.728	34	16	18	14	19
Tom Benson	0.61765	0.45455	14.8959	-5.3247	382.882	34	21	13	15	18


* 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