#2 Seattle Mixtape (17-7)

avg: 2021.63  •  sd: 71.06  •  top 16/20: 100%

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# Opponent Result Game Rating Status Date Event
3 Drag'n Thrust Loss 10-15 1564.63 Aug 3rd 2018 US Open Club Championships
21 Public Enemy Loss 10-11 1550.65 Aug 3rd 2018 US Open Club Championships
4 BFG Loss 10-11 1854.89 Aug 3rd 2018 US Open Club Championships
8 Love Tractor Win 11-8 2244.77 Aug 4th 2018 US Open Club Championships
41 Storm Win 15-13 1693.34 Aug 4th 2018 US Open Club Championships
9 Wild Card Win 14-13 1998.65 Sep 1st TCT Pro Championships 2018
1 AMP Loss 13-15 1939.71 Sep 1st TCT Pro Championships 2018
24 Rally Win 15-8 2175.92 Sep 1st TCT Pro Championships 2018
1 AMP Win 15-11 2535.05 Sep 2nd TCT Pro Championships 2018
4 BFG Win 15-11 2361.06 Sep 2nd TCT Pro Championships 2018
11 Slow White Win 15-8 2392.11 Sep 2nd TCT Pro Championships 2018
3 Drag'n Thrust Loss 14-15 1893.23 Sep 3rd TCT Pro Championships 2018
80 Garbage** Win 13-3 1840.08 Ignored Sep 22nd Northwest Mixed Regional Championship 2018
96 Pheathers and Phurr** Win 13-3 1739.96 Ignored Sep 22nd Northwest Mixed Regional Championship 2018
14 Lochsa Win 13-9 2182.28 Sep 22nd Northwest Mixed Regional Championship 2018
46 The Administrators** Win 13-5 1995.8 Ignored Sep 22nd Northwest Mixed Regional Championship 2018
4 BFG Win 13-11 2208.74 Sep 23rd Northwest Mixed Regional Championship 2018
12 Mischief Win 13-10 2112.5 Oct 18th USA Ultimate National Championships 2018
30 Jughandle Win 15-7 2157.35 Oct 18th USA Ultimate National Championships 2018
5 Space Heater Loss 9-15 1447.46 Oct 18th USA Ultimate National Championships 2018
17 Polar Bears Win 15-9 2255.17 Oct 19th USA Ultimate National Championships 2018
7 Blackbird Win 13-11 2120.52 Oct 19th USA Ultimate National Championships 2018
6 Snake Country Win 13-12 2067.98 Oct 20th USA Ultimate National Championships 2018
1 AMP Loss 8-15 1589.08 Oct 21st 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)