ThePredictionTracker NCAA RESULTS

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

2008 Second Half Totals

System	Pct. Correct	Against Spread	Absolute Error	Bias	Mean Square Error	games	suw	sul	atsw	atsl
Born Power Index	0.71345	0.51929	12.7167	-1.2377	260.174	342	244	98	175	162
Line (updated)	0.71053		12.7295	-0.7792	260.590	342	243	99
Computer Adjusted Line	0.71053	0.52713	12.7222	-0.8012	260.940	342	243	99	68	61
Atomic Football	0.73099	0.51335	12.7469	-1.0207	261.664	342	250	92	173	164
Stat Fox	0.71345	0.57547	12.6229	0.1143	262.928	342	244	98	183	135
NutShell Sports	0.74854	0.52226	12.8088	-1.1215	263.255	342	256	86	176	161
Moore Power Ratings	0.72807	0.52819	12.9262	-1.4903	269.551	342	249	93	178	159
CPA Rankings	0.74561	0.56677	12.8293	-0.5895	270.412	342	255	87	191	146
Line (opening)	0.69591	0.47292	12.9123	-1.0088	270.659	342	238	104	131	146
Dokter Entropy	0.73099	0.51632	12.8318	-0.2416	271.208	342	250	92	174	163
System Median	0.73977	0.50450	12.8014	-1.0301	271.609	342	253	89	168	165
System Average	0.74561	0.50298	12.8384	-1.0316	272.144	342	255	87	169	167
Pigskin Index	0.72271	0.47284	12.9645	-1.2886	273.201	339	245	94	148	165
Sagarin Predictive	0.71930	0.49852	13.0343	-1.5220	273.436	342	246	96	168	169
Lee Burdorf	0.70760	0.52096	13.0058	-1.1304	275.189	342	242	100	174	160
Covers.com	0.71345	0.51045	12.9807	-1.3268	277.506	342	244	98	171	164
Laz Index	0.73099	0.52381	12.9975	-1.4367	279.048	342	250	92	176	160
Catherwood Ratings	0.70455	0.51701	13.0714	-0.5325	279.343	308	217	91	152	142
Edward Kambour	0.71930	0.50742	13.1752	-0.6575	279.715	342	246	96	171	166
Hank Trexler	0.72222	0.48039	12.9444	-1.1433	279.888	342	247	95	147	159
Harmon Forcast	0.70674	0.46440	13.0587	-1.0528	280.205	341	241	100	150	173
Bihl System	0.74561	0.51190	13.0658	-0.8429	280.721	342	255	87	172	164
Dave Congrove	0.69298	0.51786	13.0498	-1.3734	280.731	342	237	105	174	162
Ashby AccuRatings	0.70760	0.48438	13.0994	-0.4091	282.343	342	242	100	155	165
Dunkel Index	0.70882	0.49552	13.0055	-0.0394	283.190	340	241	99	166	169
Beck Elo	0.70175	0.50298	13.1152	-1.1366	283.193	342	240	102	169	167
NutShell Retro	0.70468	0.49107	13.2403	-1.1406	283.195	342	241	101	165	171
Marsee	0.71053	0.49068	13.1696	0.3860	285.713	342	243	99	158	164
Stephen Kerns	0.72141	0.55357	13.2930	-3.7919	285.825	341	246	95	186	150
Bassett Model	0.70381	0.50595	13.0540	-1.2490	286.534	341	240	101	170	166
DP Dwiggins	0.68063	0.46809	13.3402	-3.4083	288.246	191	130	61	88	100
ARGH Power Ratings	0.72222	0.51735	13.0746	-0.7529	288.384	342	247	95	164	153
Linear Regression	0.74561	0.50148	13.3796	-0.8116	288.757	342	255	87	169	168
Sagarin	0.72807	0.49702	13.2590	-1.5895	289.517	342	249	93	167	169
Keeper	0.71930	0.46884	13.5427	-0.4290	293.736	342	246	96	158	179
PerformanZ Ratings	0.71930	0.49258	13.3172	-1.1177	294.286	342	246	96	166	171
Howell	0.71930	0.49682	13.4503	-0.6753	299.602	342	246	96	156	158
Warren Claassen	0.72807	0.50000	13.5085	-1.5746	300.145	342	249	93	168	168
Imes Comprank	0.70447	0.48252	13.5215	-0.9651	300.146	291	205	86	138	148
Nutshell Girl	0.70760	0.50742	13.5932	-1.5051	302.535	342	242	100	171	166
Massey Consensus	0.73099	0.51335	13.6469	-0.7243	307.219	342	250	92	173	164
Massey BCS *	0.71637	0.49258	13.5732	-0.8457	313.232	342	245	97	166	171
Sagarin Elo	0.69883	0.50148	13.8124	-1.6423	319.360	342	239	103	169	168
Anderson/Hester *	0.70710	0.47748	13.8421	-1.3609	320.219	338	239	99	159	174
Colley Rankings *	0.70175	0.47917	13.9185	-0.9162	320.895	342	240	102	161	175
CPA Retro	0.69298	0.53412	13.7712	-0.5298	321.405	342	237	105	180	157
Martien Maas	0.70175	0.51488	14.0081	-0.8904	324.670	342	240	102	173	163
Billingsly	0.66374	0.44807	14.2939	-1.2398	328.980	342	227	115	151	186
Wolfe *	0.70175	0.51039	14.0233	-0.3427	329.651	342	240	102	172	165
Sportrends	0.68935	0.50606	14.5725	-1.1127	350.439	338	233	105	167	163
Tom Benson	0.69103	0.49158	14.5393	-0.7469	350.801	301	208	93	146	151
Super List	0.71053	0.48214	15.2454	-0.9772	371.767	342	243	99	162	174
Least Squares w/ HFA	0.65789	0.49258	16.1102	-1.1122	412.168	342	225	117	166	171
Logistic Regression	0.67251	0.49852	19.9079	-4.7427	967.244	342	230	112	168	169


* 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