#195 MoonPi (6-14)

avg: 567.93  •  sd: 62.02  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
- Forcey Loss 6-11 735.15 Jun 24th Huntsville Huckfest
150 Memphis STAX Loss 8-11 461.82 Jun 24th Huntsville Huckfest
218 Hairy Otter Loss 8-13 -106.44 Jun 24th Huntsville Huckfest
115 Dizzy Kitty Loss 7-12 497.91 Jul 8th Summer Glazed Daze 2023
100 Columbus Chaos Loss 4-14 459.97 Jul 8th Summer Glazed Daze 2023
66 Malice in Wonderland** Loss 4-14 668.7 Ignored Jul 8th Summer Glazed Daze 2023
248 Pickles Win 13-6 650.83 Jul 9th Summer Glazed Daze 2023
34 Dirty Bird** Loss 0-15 983.11 Ignored Aug 12th HoDown Showdown 2023
206 Piedmont United Loss 10-14 90.06 Aug 12th HoDown Showdown 2023
126 Barefoot Loss 9-12 621.76 Aug 12th HoDown Showdown 2023
96 Bear Jordan Loss 9-12 730.64 Aug 12th HoDown Showdown 2023
236 Rampage Win 14-5 825.56 Aug 13th HoDown Showdown 2023
248 Pickles Win 11-4 650.83 Aug 13th HoDown Showdown 2023
217 Flood Zone Win 11-9 658.8 Aug 13th HoDown Showdown 2023
34 Dirty Bird** Loss 3-13 983.11 Ignored Sep 9th 2023 Mixed East Coast Sectional Championship
217 Flood Zone Win 9-8 534.59 Sep 9th 2023 Mixed East Coast Sectional Championship
86 Crown Peach Loss 9-13 728.41 Sep 9th 2023 Mixed East Coast Sectional Championship
73 m'kay Ultimate Loss 6-13 633.75 Sep 9th 2023 Mixed East Coast Sectional Championship
152 Verdant Loss 0-13 224.5 Sep 10th 2023 Mixed East Coast Sectional Championship
218 Hairy Otter Win 13-5 989.72 Sep 10th 2023 Mixed East Coast 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)