#86 Crown Peach (12-6)

avg: 1146.98  •  sd: 68.8  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
238 Victrix** Win 13-0 793.58 Ignored Jul 8th Club Terminus 2023
204 New Orleans Boil Win 11-5 1123.57 Jul 8th Club Terminus 2023
73 m'kay Ultimate Win 10-8 1496.41 Jul 8th Club Terminus 2023
53 Roma Ultima Loss 7-11 881.98 Jul 9th Club Terminus 2023
81 B-Unit Loss 8-10 913.72 Jul 9th Club Terminus 2023
169 Happy Hour Win 11-7 1207.5 Jul 9th Club Terminus 2023
217 Flood Zone** Win 14-4 1009.59 Ignored Aug 12th HoDown Showdown 2023
107 FlyTrap Win 12-11 1163.84 Aug 12th HoDown Showdown 2023
152 Verdant Win 15-4 1424.5 Aug 12th HoDown Showdown 2023
53 Roma Ultima Loss 11-14 1035.54 Aug 13th HoDown Showdown 2023
96 Bear Jordan Win 10-9 1201 Aug 13th HoDown Showdown 2023
85 Too Much Fun Loss 9-13 731.95 Aug 13th HoDown Showdown 2023
34 Dirty Bird Win 11-8 1948.72 Sep 9th 2023 Mixed East Coast Sectional Championship
217 Flood Zone Win 13-7 967.12 Sep 9th 2023 Mixed East Coast Sectional Championship
195 MoonPi Win 13-9 986.49 Sep 9th 2023 Mixed East Coast Sectional Championship
73 m'kay Ultimate Win 10-9 1358.75 Sep 9th 2023 Mixed East Coast Sectional Championship
34 Dirty Bird Loss 8-15 1018.31 Sep 10th 2023 Mixed East Coast Sectional Championship
53 Roma Ultima Loss 8-14 812.84 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)