#49 Fiasco (9-12)

avg: 1025.1  •  sd: 83.28  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
58 Venom Win 9-4 1424.13 Jul 13th TCT Select Flight Invite West 2019
36 Seattle Soul Loss 9-15 713.4 Jul 13th TCT Select Flight Invite West 2019
97 Maeve** Win 15-2 505.4 Ignored Jul 13th TCT Select Flight Invite West 2019
9 Traffic** Loss 2-13 1363.67 Ignored Jul 14th TCT Select Flight Invite West 2019
55 Crackle Loss 6-7 743.04 Jul 14th TCT Select Flight Invite West 2019
56 Outbreak Win 8-5 1303.44 Jul 14th TCT Select Flight Invite West 2019
93 Ultraviolet** Win 10-3 758.84 Ignored Aug 24th Ski Town Classic 2019
58 Venom Win 9-3 1424.13 Aug 24th Ski Town Classic 2019
42 Rampage Loss 4-12 525.62 Aug 24th Ski Town Classic 2019
66 Jackwagon Win 11-9 928.39 Aug 24th Ski Town Classic 2019
58 Venom Win 8-6 1124.62 Aug 25th Ski Town Classic 2019
36 Seattle Soul Loss 8-10 966.21 Aug 25th Ski Town Classic 2019
23 Tabby Rosa Loss 6-10 999.46 Sep 7th Florida Womens Club Sectional Championship 2019
23 Tabby Rosa Loss 4-10 895.62 Sep 7th Florida Womens Club Sectional Championship 2019
23 Tabby Rosa Loss 6-12 916.31 Sep 7th Florida Womens Club Sectional Championship 2019
46 Queen Cake Win 10-9 1195.96 Sep 21st Southeast Club Womens Regional Championship 2019
15 Ozone** Loss 1-15 1126.66 Ignored Sep 21st Southeast Club Womens Regional Championship 2019
30 Steel Loss 12-15 1047.8 Sep 21st Southeast Club Womens Regional Championship 2019
57 Taco Truck Win 13-9 1261.8 Sep 22nd Southeast Club Womens Regional Championship 2019
23 Tabby Rosa Loss 8-12 1054.47 Sep 22nd Southeast Club Womens Regional Championship 2019
46 Queen Cake Loss 9-10 945.96 Sep 22nd Southeast 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)