#12 Mischief (29-11)

avg: 1784.35  •  sd: 70.37  •  top 16/20: 72%

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# Opponent Result Game Rating Status Date Event
31 Metro North Win 12-11 1681.32 Jul 7th TCT Pro Elite Challenge 2018
10 shame. Loss 8-13 1348.57 Jul 7th TCT Pro Elite Challenge 2018
13 Birdfruit Win 12-11 1904.29 Jul 7th TCT Pro Elite Challenge 2018
22 XIST Win 9-8 1743.05 Jul 8th TCT Pro Elite Challenge 2018
16 NOISE Loss 10-12 1505.06 Jul 8th TCT Pro Elite Challenge 2018
36 Steamboat Win 12-6 2084.7 Jul 8th TCT Pro Elite Challenge 2018
29 7 Figures Loss 8-11 1194.77 Jul 21st Revolution 2018
74 Alchemy Win 14-4 1865.2 Jul 21st Revolution 2018
35 Classy Win 11-7 1980.61 Jul 21st Revolution 2018
29 7 Figures Win 8-7 1685.38 Jul 22nd Revolution 2018
65 Family Style Win 14-3 1887.22 Jul 22nd Revolution 2018
23 Lights Out Win 12-5 2214.46 Jul 22nd Revolution 2018
15 Toro Win 14-12 1981.59 Aug 18th TCT Elite Select Challenge 2018
38 Columbus Cocktails Win 13-6 2100.3 Aug 18th TCT Elite Select Challenge 2018
17 Polar Bears Loss 5-13 1139.68 Aug 18th TCT Elite Select Challenge 2018
33 League of Shadows Win 11-7 2002.85 Aug 19th TCT Elite Select Challenge 2018
25 The Chad Larson Experience Win 12-8 2041.91 Aug 19th TCT Elite Select Challenge 2018
210 VU** Win 11-3 1126.65 Ignored Sep 8th Nor Cal Mixed Sectional Championship 2018
74 Alchemy Win 11-3 1865.2 Sep 8th Nor Cal Mixed Sectional Championship 2018
190 DR** Win 11-4 1235.15 Ignored Sep 8th Nor Cal Mixed Sectional Championship 2018
85 Platypi Win 11-4 1790.67 Sep 8th Nor Cal Mixed Sectional Championship 2018
136 Lawn Patrol Win 11-5 1548.72 Sep 8th Nor Cal Mixed Sectional Championship 2018
51 Cutthroat Win 13-12 1482.69 Sep 9th Nor Cal Mixed Sectional Championship 2018
37 BW Ultimate Win 13-10 1828.7 Sep 9th Nor Cal Mixed Sectional Championship 2018
17 Polar Bears Win 13-7 2297.22 Sep 9th Nor Cal Mixed Sectional Championship 2018
7 Blackbird Loss 5-13 1291.68 Sep 9th Nor Cal Mixed Sectional Championship 2018
51 Cutthroat Win 13-3 1957.69 Sep 22nd Southwest Mixed Regional Championship 2018
37 BW Ultimate Loss 11-13 1271.72 Sep 22nd Southwest Mixed Regional Championship 2018
71 Robot Win 13-8 1771.06 Sep 22nd Southwest Mixed Regional Championship 2018
48 Rubix Loss 13-14 1253.83 Sep 22nd Southwest Mixed Regional Championship 2018
37 BW Ultimate Win 13-5 2100.56 Sep 23rd Southwest Mixed Regional Championship 2018
17 Polar Bears Win 13-10 2067.83 Sep 23rd Southwest Mixed Regional Championship 2018
7 Blackbird Win 12-11 2016.68 Sep 23rd Southwest Mixed Regional Championship 2018
2 Seattle Mixtape Loss 10-13 1693.49 Oct 18th USA Ultimate National Championships 2018
5 Space Heater Win 14-13 2087.94 Oct 18th USA Ultimate National Championships 2018
30 Jughandle Win 15-11 1938.52 Oct 18th USA Ultimate National Championships 2018
3 Drag'n Thrust Loss 12-15 1717.74 Oct 19th USA Ultimate National Championships 2018
10 shame. Win 15-8 2409.53 Oct 19th USA Ultimate National Championships 2018
6 Snake Country Loss 9-15 1427.5 Oct 19th USA Ultimate National Championships 2018
10 shame. Loss 11-15 1463.56 Oct 20th USA Ultimate National Championships 2018
**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)