#154 Melt (14-10)

avg: 913.8  •  sd: 45.84  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
244 Madison United Mixed Ultimate Win 12-8 902.93 Jul 20th Minnesota Ultimate Disc Invitational
122 Pandamonium Loss 7-8 956.72 Jul 21st Minnesota Ultimate Disc Invitational
226 Boomtown Pandas Win 12-6 1150.92 Jul 21st Minnesota Ultimate Disc Invitational
240 Duloofda Win 10-7 861.09 Jul 21st Minnesota Ultimate Disc Invitational
218 Great Minnesota Get Together Win 13-5 1212.32 Jul 21st Minnesota Ultimate Disc Invitational
213 Mastodon Win 13-8 1141.68 Aug 3rd Heavyweights 2019
156 ELevate Win 13-11 1141.83 Aug 3rd Heavyweights 2019
214 Stackcats Win 12-8 1078.41 Aug 3rd Heavyweights 2019
251 Mishigami Win 13-10 744.33 Aug 3rd Heavyweights 2019
125 Nothing's Great Again Loss 8-13 556.19 Aug 4th Heavyweights 2019
58 Toast Loss 9-13 966.52 Aug 4th Heavyweights 2019
214 Stackcats Win 12-9 982.62 Aug 17th Cooler Classic 31
100 Risky Business Loss 1-13 569 Aug 17th Cooler Classic 31
228 Midwestern Mediocrity Win 13-7 1083.47 Aug 17th Cooler Classic 31
171 Mousetrap Win 13-11 1028.39 Aug 17th Cooler Classic 31
147 Point of No Return Loss 5-7 604.58 Aug 18th Cooler Classic 31
92 Mojo Jojo Loss 6-7 1068.15 Aug 18th Cooler Classic 31
248 Dinosaur Fancy Win 13-5 1032.61 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
141 Mad Udderburn Win 13-12 1093.38 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
218 Great Minnesota Get Together Win 13-10 940.46 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
32 NOISE Loss 7-13 1054.27 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
129 Bird Loss 8-13 539.4 Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
147 Point of No Return Loss 10-12 694.6 Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
171 Mousetrap Loss 9-10 674.55 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)