#145 Madison United Mixed Ultimate (11-9)

avg: 824.22  •  sd: 64.3  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
210 ELevate Win 13-6 1052.38 Jul 8th Heavyweights 2023
88 Spectre Loss 9-13 690.05 Jul 8th Heavyweights 2023
135 Point of No Return Loss 6-13 261.51 Jul 8th Heavyweights 2023
186 2Fly2Furious Win 11-10 706.62 Jul 9th Heavyweights 2023
179 Frostbite Win 10-7 1035.82 Jul 9th Heavyweights 2023
150 Toast! Win 10-9 928.62 Jul 9th Heavyweights 2023
109 Pushovers Win 13-9 1444.08 Aug 19th Cooler Classic 34
159 Pandamonium Loss 7-11 318.96 Aug 19th Cooler Classic 34
165 Prion Win 12-5 1361.72 Aug 19th Cooler Classic 34
73 Northern Comfort Loss 4-10 594.2 Aug 19th Cooler Classic 34
109 Pushovers Win 12-11 1150.51 Aug 20th Cooler Classic 34
135 Point of No Return Win 10-8 1124.18 Aug 20th Cooler Classic 34
116 Jabba Loss 6-14 392.19 Aug 20th Cooler Classic 34
103 Bird Loss 9-10 912.54 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
189 Great Minnesota Get Together Win 13-10 895.03 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
236 Mad City Vibes Win 13-9 651.59 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
86 Mad Udderburn Loss 7-13 563.61 Sep 9th 2023 Mixed Northwest Plains Sectional Championship
179 Frostbite Loss 8-9 521.15 Sep 10th 2023 Mixed Northwest Plains Sectional Championship
76 Bantr Loss 10-14 785.35 Sep 10th 2023 Mixed Northwest Plains Sectional Championship
182 Melt Win 12-8 1061.22 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)