šŸˆ Espns computer poll

2020 Season Totals
Through 2020-11-29
Rank​
Bias
suw
sul
atsw
atsl
1​
Stephen Kerns​
0.78636​
0.48826​
13.3144​
1.0820​
280.856​
220​
173​
47​
104​
109​
2​
Donchess Inference​
0.75194​
0.51989​
13.0238​
1.4258​
263.313​
387​
291​
96​
196​
181​
3​
Dunkel Index​
0.75000​
0.48677​
13.6608​
2.1004​
287.141​
384​
288​
96​
184​
194​
4​
ESPN FPI​
0.74815​
0.51005​
12.9985​
1.0128​
257.757​
405​
303​
102​
203​
195​
5​
System Median​
0.74201​
0.50505​
13.0946​
1.1963​
266.382​
407​
302​
105​
200​
196​
6​
Massey Consensus​
0.74074​
0.51378​
13.2601​
1.7347​
278.993​
405​
300​
105​
205​
194​
7​
Talisman Red​
0.74020​
0.49000​
13.9459​
0.6804​
299.628​
204​
151​
53​
98​
102​
8​
David Harville​
0.73956​
0.51870​
13.2293​
1.3537​
273.149​
407​
301​
106​
208​
193​
9​
Born Power Index​
0.73956​
0.47880​
13.9170​
2.2338​
306.716​
407​
301​
106​
192​
209​
10​
TeamRankings.com​
0.73892​
0.50765​
13.1037​
1.1446​
263.528​
406​
300​
106​
199​
193​
11​
Line (Midweek)​
0.73710​
12.8354​
0.5430​
253.806​
407​
300​
107​
12​
FEI Projections​
0.73645​
0.52525​
13.2866​
1.3363​
281.610​
406​
299​
107​
208​
188​
13​
Keeper​
0.73600​
0.47411​
13.7118​
0.7583​
285.943​
375​
276​
99​
174​
193​
14​
Line (updated)​
0.73464​
0.47150​
12.8489​
0.4459​
252.721​
407​
299​
108​
91​
102​
15​
Dokter Entropy​
0.73333​
0.50882​
13.0878​
1.5344​
269.014​
405​
297​
108​
202​
195​
16​
System Average​
0.73219​
0.48379​
13.1128​
1.2102​
266.497​
407​
298​
109​
194​
207​
17​
Computer Adjusted Line​
0.73219​
0.51163​
12.8440​
0.5541​
252.043​
407​
298​
109​
132​
126​
18​
Beck Elo​
0.73219​
0.49377​
13.6258​
2.0462​
287.267​
407​
298​
109​
198​
203​
19​
PerformanZ Ratings​
0.73219​
0.52120​
13.6584​
1.4475​
296.664​
407​
298​
109​
209​
192​
20​
ARGH Power Ratings​
0.73020​
0.55440​
13.2630​
1.2395​
276.418​
404​
295​
109​
214​
172​
21​
Versus Sports Simulator​
0.72569​
0.49239​
13.3629​
1.5377​
278.443​
401​
291​
110​
194​
200​
22​
Roundtable​
0.72308​
0.48207​
14.6885​
1.0346​
357.884​
260​
188​
72​
121​
130​
23​
Catherwood Ratings​
0.71990​
0.50000​
13.8943​
3.0934​
306.456​
407​
293​
114​
196​
196​
24​
Sagarin Ratings​
0.71990​
0.48500​
14.0088​
0.5096​
300.779​
407​
293​
114​
194​
206​
25​
Moore Power Ratings​
0.71852​
0.48872​
13.8480​
0.7457​
290.096​
405​
291​
114​
195​
204​
26​
PI-Rate Bias​
0.71744​
0.51899​
13.2280​
0.5111​
268.719​
407​
292​
115​
205​
190​
27​
Sagarin Points​
0.71499​
0.49127​
14.1130​
0.4874​
306.917​
407​
291​
116​
197​
204​
28​
Sagarin Recent​
0.71499​
0.48628​
14.3603​
0.6116​
312.610​
407​
291​
116​
195​
206​
29​
Pi-Rate Ratings​
0.71499​
0.53535​
13.2000​
0.4610​
269.101​
407​
291​
116​
212​
184​
30​
Super List​
0.71358​
0.47619​
14.6349​
2.0333​
325.660​
405​
289​
116​
190​
209​
31​
Howell​
0.71250​
0.54427​
13.2774​
0.7876​
275.233​
400​
285​
115​
209​
175​
32​
Daniel Curry Index​
0.71111​
0.47870​
15.0413​
1.1443​
369.354​
405​
288​
117​
191​
208​
33​
Stat Fox​
0.71007​
0.51414​
13.8281​
3.0273​
300.853​
407​
289​
118​
200​
189​
34​
ThePowerRank.com​
0.70886​
0.49612​
13.5529​
-0.2840​
283.082​
395​
280​
115​
192​
195​
35​
Massey Ratings​
0.70574​
0.48861​
13.7706​
0.6250​
296.198​
401​
283​
118​
193​
202​
36​
Laz Index​
0.70516​
0.50623​
13.6021​
1.6159​
283.465​
407​
287​
120​
203​
198​
37​
Edward Kambour​
0.70516​
0.47132​
13.9333​
1.2897​
299.011​
407​
287​
120​
189​
212​
38​
Sagarin Golden Mean​
0.70516​
0.48379​
13.9751​
0.4389​
300.774​
407​
287​
120​
194​
207​
39​
Pi-Ratings Mean​
0.70270​
0.53652​
13.1314​
0.3565​
264.986​
407​
286​
121​
213​
184​
40​
Line (opening)​
0.69533​
0.50289​
13.3784​
0.8722​
279.485​
407​
283​
124​
174​
172​
41​
Cleanup Hitter​
0.68828​
0.47792​
14.8193​
1.0837​
339.377​
401​
276​
125​
184​
201​
42​
Dave Congrove​
0.68473​
0.50250​
14.4861​
1.4326​
328.460​
406​
278​
128​
201​
199​
43​
Loudsound.org​
0.65995​
0.52231​
15.6675​
-2.9673​
394.310​
397​
262​
135​
199​
182​
* 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
 
Back
Top Bottom