#161 Prion (10-9)

avg: 783.61  •  sd: 68.51  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
240 PanIC** Win 13-5 741.66 Ignored Jul 22nd Corny Classic II
89 Three Rivers Ultimate Club Loss 8-13 624.15 Jul 22nd Corny Classic II
156 Stackcats Loss 9-12 468.45 Jul 22nd Corny Classic II
146 Indiana Pterodactyl Attack Loss 13-14 713.82 Jul 23rd Corny Classic II
210 Chalice Win 14-13 585.57 Jul 23rd Corny Classic II
209 Mastodon Win 9-4 1062.95 Jul 23rd Corny Classic II
227 Arms Race Win 11-6 872.67 Aug 19th Cooler Classic 34
205 Locomotion Win 11-8 882.79 Aug 19th Cooler Classic 34
181 Frostbite Win 11-7 1108.05 Aug 19th Cooler Classic 34
155 Madison United Mixed Ultimate Loss 5-12 217.14 Aug 19th Cooler Classic 34
209 Mastodon Win 14-5 1062.95 Aug 20th Cooler Classic 34
181 Frostbite Win 11-7 1108.05 Aug 20th Cooler Classic 34
196 Great Minnesota Get Together Win 10-6 1054.9 Aug 20th Cooler Classic 34
19 RAMP** Loss 5-15 1138.88 Ignored Sep 9th 2023 Mixed Central Plains Sectional Championship
156 Stackcats Win 11-8 1179.43 Sep 9th 2023 Mixed Central Plains Sectional Championship
30 Chicago Parlay** Loss 4-15 1063.97 Ignored Sep 9th 2023 Mixed Central Plains Sectional Championship
129 Bandwagon Loss 7-9 639.87 Sep 9th 2023 Mixed Central Plains Sectional Championship
146 Indiana Pterodactyl Attack Loss 9-14 364.95 Sep 10th 2023 Mixed Central Plains Sectional Championship
173 Practice Player Penguins [JV] Loss 11-12 608.97 Sep 10th 2023 Mixed Central 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)