#156 ELevate (12-9)

avg: 912.98  •  sd: 68.29  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
289 Taco Cat** Win 13-2 567.09 Ignored Aug 3rd Heavyweights 2019
279 Identity Theft** Win 13-4 809.93 Ignored Aug 3rd Heavyweights 2019
169 Wildstyle Win 13-7 1368.83 Aug 3rd Heavyweights 2019
154 Melt Loss 11-13 684.96 Aug 3rd Heavyweights 2019
172 Prion Win 13-8 1295.3 Aug 4th Heavyweights 2019
169 Wildstyle Win 12-11 936.29 Aug 4th Heavyweights 2019
218 Great Minnesota Get Together Win 12-8 1053.48 Aug 17th Cooler Classic 31
171 Mousetrap Loss 9-10 674.55 Aug 17th Cooler Classic 31
228 Midwestern Mediocrity Win 13-8 1022.1 Aug 17th Cooler Classic 31
92 Mojo Jojo Loss 10-12 955.03 Aug 17th Cooler Classic 31
192 Jabba Loss 6-7 583.36 Aug 18th Cooler Classic 31
209 Pushovers-B Win 9-2 1259.42 Aug 18th Cooler Classic 31
214 Stackcats Win 10-4 1237.26 Aug 18th Cooler Classic 31
125 Nothing's Great Again Loss 6-13 452.35 Sep 7th Central Plains Mixed Club Sectional Championship 2019
277 Indiana Pterodactyl Attack** Win 13-3 823.31 Ignored Sep 7th Central Plains Mixed Club Sectional Championship 2019
172 Prion Win 13-6 1399.14 Sep 7th Central Plains Mixed Club Sectional Championship 2019
139 Tequila Mockingbird Loss 11-12 860.39 Sep 7th Central Plains Mixed Club Sectional Championship 2019
135 Los Heros Loss 8-15 446.27 Sep 8th Central Plains Mixed Club Sectional Championship 2019
160 EMU Win 14-10 1293.62 Sep 8th Central Plains Mixed Club Sectional Championship 2019
139 Tequila Mockingbird Loss 6-15 385.39 Sep 8th Central Plains Mixed Club Sectional Championship 2019
160 EMU Loss 13-14 769.92 Sep 8th Central Plains Mixed Club Sectional Championship 2019
**Blowout Eligible

FAQ

The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)