#22 LOL (14-7)

avg: 1529.16  •  sd: 106.28  •  top 16/20: 1.4%

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# Opponent Result Game Rating Status Date Event
59 Portland Ivy** Win 11-2 1423.66 Ignored Aug 4th Seattle Round Robin 2019
87 Sizzle** Win 13-2 866.82 Ignored Aug 4th Seattle Round Robin 2019
36 Seattle Soul Loss 6-8 928.39 Aug 4th Seattle Round Robin 2019
36 Seattle Soul Win 10-7 1618.55 Aug 4th Seattle Round Robin 2019
20 Grit Win 12-11 1733.05 Aug 17th TCT Elite Select Challenge 2019
31 Heist Win 13-9 1726.13 Aug 17th TCT Elite Select Challenge 2019
7 Phoenix Loss 3-15 1451.86 Aug 17th TCT Elite Select Challenge 2019
20 Grit Win 11-9 1857.26 Aug 18th TCT Elite Select Challenge 2019
17 Showdown Loss 5-11 1080.21 Aug 18th TCT Elite Select Challenge 2019
14 Nemesis Loss 3-8 1174.52 Aug 18th TCT Elite Select Challenge 2019
93 Ultraviolet** Win 13-0 758.84 Ignored Sep 8th Nor Cal Womens Club Sectional Championship 2019
32 FAB Win 11-8 1657.51 Sep 8th Nor Cal Womens Club Sectional Championship 2019
- 2nd Wave** Win 11-4 1355.72 Ignored Sep 8th Nor Cal Womens Club Sectional Championship 2019
89 Tempo** Win 13-1 834.07 Ignored Sep 8th Nor Cal Womens Club Sectional Championship 2019
32 FAB Win 13-7 1849.43 Sep 21st Southwest Club Womens Regional Championship 2019
42 Rampage Win 13-3 1725.62 Sep 21st Southwest Club Womens Regional Championship 2019
10 Nightlock Loss 5-13 1357.64 Sep 21st Southwest Club Womens Regional Championship 2019
89 Tempo** Win 13-3 834.07 Ignored Sep 21st Southwest Club Womens Regional Championship 2019
11 Wildfire Loss 10-13 1538.86 Sep 22nd Southwest Club Womens Regional Championship 2019
1 Fury** Loss 4-13 1841.46 Ignored Sep 22nd Southwest Club Womens Regional Championship 2019
42 Rampage Win 11-9 1374.83 Sep 22nd Southwest Club Womens Regional 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)