#155 Madison United Mixed Ultimate (11-9)

avg: 817.14  •  sd: 66.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
212 ELevate Win 13-6 1042.78 Jul 8th Heavyweights 2023
117 Spectre Loss 9-13 591.89 Jul 8th Heavyweights 2023
144 Point of No Return Loss 6-13 246.9 Jul 8th Heavyweights 2023
191 2Fly2Furious Win 11-10 718.77 Jul 9th Heavyweights 2023
181 Frostbite Win 10-7 1030.82 Jul 9th Heavyweights 2023
136 Toast! Win 10-9 1004.34 Jul 9th Heavyweights 2023
112 Pushovers Win 13-9 1440.56 Aug 19th Cooler Classic 34
164 Pandamonium Loss 7-11 307.41 Aug 19th Cooler Classic 34
161 Prion Win 12-5 1383.61 Aug 19th Cooler Classic 34
78 Northern Comfort Loss 4-10 588.75 Aug 19th Cooler Classic 34
112 Pushovers Win 12-11 1146.99 Aug 20th Cooler Classic 34
144 Point of No Return Win 10-8 1109.57 Aug 20th Cooler Classic 34
121 Jabba Loss 6-14 384.87 Aug 20th Cooler Classic 34
111 Bird Loss 9-10 897.53 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
196 Great Minnesota Get Together Win 13-10 886.89 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
235 Mad City Vibes Win 13-9 648.36 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
92 Mad Udderburn Loss 7-13 542.62 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
181 Frostbite Loss 8-9 516.15 Sep 10th 2023 Mixed Northwest Plains Sectional Championship
82 Bantr Loss 10-14 776.07 Sep 10th 2023 Mixed Northwest Plains Sectional Championship
188 Melt Win 12-8 1051.38 Sep 10th 2023 Mixed Northwest Plains 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)