#130 m'kay Ultimate (11-9)

avg: 985.41  •  sd: 53.37  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
251 Big Bend Win 13-6 963.36 Jun 15th ATL Classic 2019
75 Auburn HeyDay Win 11-10 1352.49 Jun 15th ATL Classic 2019
80 Trash Pandas Loss 11-12 1073.09 Jun 15th ATL Classic 2019
158 OutKast Win 10-4 1439.42 Jun 15th ATL Classic 2019
162 BATL Cows Win 7-3 1419.25 Jun 16th ATL Classic 2019
47 Huntsville Outlaws Loss 10-11 1316.37 Jun 16th ATL Classic 2019
252 Mixchief Win 13-8 852.51 Jun 16th ATL Classic 2019
20 Weird** Loss 5-13 1081.45 Ignored Jul 20th 2019 Club Terminus
228 The Umbrella Win 13-6 1070.04 Jul 20th 2019 Club Terminus
78 Memphis STAX Loss 9-13 788.77 Jul 20th 2019 Club Terminus
170 Magic City Mayhem Win 9-6 1181.71 Jul 20th 2019 Club Terminus
162 BATL Cows Win 13-9 1237.82 Jul 21st 2019 Club Terminus
20 Weird** Loss 5-13 1081.45 Ignored Jul 21st 2019 Club Terminus
78 Memphis STAX Loss 2-9 607.34 Jul 21st 2019 Club Terminus
160 APEX Loss 10-11 703.62 Sep 7th East Coast Mixed Club Sectional Championship 2019
222 Monster Win 13-8 1037.34 Sep 7th East Coast Mixed Club Sectional Championship 2019
68 JLP Loss 8-12 804.43 Sep 7th East Coast Mixed Club Sectional Championship 2019
228 The Umbrella Win 13-4 1070.04 Sep 7th East Coast Mixed Club Sectional Championship 2019
165 Possum Win 13-11 1034.36 Sep 8th East Coast Mixed Club Sectional Championship 2019
158 OutKast Loss 9-11 590.21 Sep 8th East Coast Mixed Club Sectional Championship 2019
**Blowout Eligible

FAQ

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
  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
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)