#19 Pop (13-18)

avg: 1679.32  •  sd: 78.41  •  top 16/20: 74.1%

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# Opponent Result Game Rating Status Date Event
12 Traffic Loss 10-13 1440.93 Jul 7th TCT Pro Elite Challenge 2018
18 Phoenix Loss 8-13 1201.51 Jul 7th TCT Pro Elite Challenge 2018
9 Schwa Loss 6-13 1237.97 Jul 7th TCT Pro Elite Challenge 2018
15 Wildfire Win 10-9 1848.35 Jul 8th TCT Pro Elite Challenge 2018
23 LOL Win 9-7 1789.55 Jul 8th TCT Pro Elite Challenge 2018
10 Nemesis Loss 9-10 1699.48 Jul 8th TCT Pro Elite Challenge 2018
11 Rival Win 15-7 2404.18 Aug 3rd 2018 US Open Club Championships
5 Scandal Loss 9-14 1629.23 Aug 3rd 2018 US Open Club Championships
10 Nemesis Loss 6-13 1224.48 Aug 3rd 2018 US Open Club Championships
7 Ozone Loss 13-14 1811.53 Aug 4th 2018 US Open Club Championships
1 Brute Squad** Loss 6-15 1862.67 Ignored Aug 4th 2018 US Open Club Championships
11 Rival Loss 8-14 1268.15 Aug 5th 2018 US Open Club Championships
15 Wildfire Win 13-10 2051.49 Aug 18th TCT Elite Select Challenge 2018
18 Phoenix Loss 12-13 1572.67 Aug 18th TCT Elite Select Challenge 2018
25 Colorado Small Batch Win 13-6 2047.1 Aug 18th TCT Elite Select Challenge 2018
6 6ixers Loss 12-13 1891.35 Aug 19th TCT Elite Select Challenge 2018
14 Showdown Win 11-7 2198.03 Aug 19th TCT Elite Select Challenge 2018
24 Wicked Win 10-7 1881.83 Sep 22nd North Central Womens Regional Championship 2018
74 MystiKuE** Win 11-1 831.1 Ignored Sep 22nd North Central Womens Regional Championship 2018
58 Stellar** Win 11-3 1263.29 Ignored Sep 22nd North Central Womens Regional Championship 2018
70 Lady Forward** Win 11-2 977.96 Ignored Sep 22nd North Central Womens Regional Championship 2018
24 Wicked Win 12-8 1933.32 Sep 23rd North Central Womens Regional Championship 2018
16 Heist Loss 12-13 1597.08 Sep 23rd North Central Womens Regional Championship 2018
44 Crackle** Win 15-6 1566.74 Ignored Sep 23rd North Central Womens Regional Championship 2018
7 Ozone Loss 11-14 1623.2 Oct 18th USA Ultimate National Championships 2018
4 Seattle Riot Loss 6-15 1663.78 Oct 18th USA Ultimate National Championships 2018
11 Rival Loss 9-15 1288.7 Oct 18th USA Ultimate National Championships 2018
8 Nightlock Loss 4-15 1320.39 Oct 19th USA Ultimate National Championships 2018
11 Rival Win 15-14 1929.18 Oct 19th USA Ultimate National Championships 2018
8 Nightlock Loss 12-15 1619.9 Oct 19th USA Ultimate National Championships 2018
10 Nemesis Loss 12-14 1603.52 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)