#66 Malice in Wonderland (16-4)

avg: 1268.7  •  sd: 52.78  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
115 Dizzy Kitty Win 12-11 1143.42 Jul 8th Summer Glazed Daze 2023
100 Columbus Chaos Loss 11-12 934.97 Jul 8th Summer Glazed Daze 2023
195 MoonPi** Win 14-4 1167.93 Ignored Jul 8th Summer Glazed Daze 2023
180 District Cocktails Win 15-7 1265.86 Jul 9th Summer Glazed Daze 2023
206 Piedmont United** Win 13-5 1088.76 Ignored Jul 22nd Filling the Void 2023
197 Swampbenders** Win 13-3 1158.19 Ignored Jul 22nd Filling the Void 2023
85 Too Much Fun Win 13-9 1569.08 Jul 22nd Filling the Void 2023
105 Legion Win 13-8 1540.14 Jul 22nd Filling the Void 2023
106 Ant Madness Loss 8-8 1041.14 Jul 23rd Filling the Void 2023
141 Catalyst Win 15-6 1466.38 Jul 23rd Filling the Void 2023
217 Flood Zone** Win 15-3 1009.59 Ignored Aug 12th HoDown Showdown 2023
107 FlyTrap Win 13-12 1163.84 Aug 12th HoDown Showdown 2023
152 Verdant Win 15-6 1424.5 Aug 12th HoDown Showdown 2023
34 Dirty Bird Loss 8-14 1047.08 Aug 13th HoDown Showdown 2023
85 Too Much Fun Win 14-13 1275.52 Aug 13th HoDown Showdown 2023
73 m'kay Ultimate Win 11-6 1780.44 Aug 13th HoDown Showdown 2023
236 Rampage** Win 13-1 825.56 Ignored Sep 9th 2023 Mixed North Carolina Sectional Championship
107 FlyTrap Win 12-10 1276.96 Sep 9th 2023 Mixed North Carolina Sectional Championship
141 Catalyst Win 13-11 1095.22 Sep 9th 2023 Mixed North Carolina Sectional Championship
29 Storm Loss 7-15 1075.01 Sep 10th 2023 Mixed North Carolina Sectional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)