#152 Melt (14-10)

avg: 861.32  •  sd: 45.84  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
241 Madison United Mixed Ultimate Win 12-8 860.09 Jul 20th Minnesota Ultimate Disc Invitational
219 Great Minnesota Get Together Win 13-5 1156.41 Jul 21st Minnesota Ultimate Disc Invitational
225 Boomtown Pandas Win 12-6 1098.82 Jul 21st Minnesota Ultimate Disc Invitational
240 Duloofda Win 10-7 809.23 Jul 21st Minnesota Ultimate Disc Invitational
112 Pandamonium Loss 7-8 942.1 Jul 21st Minnesota Ultimate Disc Invitational
168 ELevate Win 13-11 1008.99 Aug 3rd Heavyweights 2019
211 Mastodon Win 13-8 1084.82 Aug 3rd Heavyweights 2019
250 Mishigami Win 13-10 691.57 Aug 3rd Heavyweights 2019
217 Stackcats Win 12-8 1009.67 Aug 3rd Heavyweights 2019
63 Toast Loss 9-13 858.79 Aug 4th Heavyweights 2019
122 Nothing's Great Again Loss 8-13 539.7 Aug 4th Heavyweights 2019
227 Midwestern Mediocrity Win 13-7 1029.56 Aug 17th Cooler Classic 31
217 Stackcats Win 12-9 913.89 Aug 17th Cooler Classic 31
176 Mousetrap Win 13-11 961.27 Aug 17th Cooler Classic 31
126 Risky Business Loss 1-13 410.25 Aug 17th Cooler Classic 31
76 Mojo Jojo Loss 6-7 1098.93 Aug 18th Cooler Classic 31
141 Point of No Return Loss 5-7 570.49 Aug 18th Cooler Classic 31
31 NOISE Loss 7-13 1030.85 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
219 Great Minnesota Get Together Win 13-10 884.55 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
245 Dinosaur Fancy Win 13-5 987.22 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
137 Mad Udderburn Win 13-12 1052.56 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
117 Bird Loss 8-13 560.22 Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
176 Mousetrap Loss 9-10 607.43 Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
141 Point of No Return Loss 10-12 660.51 Sep 8th Northwest 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)