#53 Stellar (14-6)

avg: 972.24  •  sd: 89.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
87 Cold Cuts** Win 13-1 836.9 Ignored Jun 29th Spirit of the Plains 2019
72 Helix Win 13-8 1129.96 Jun 29th Spirit of the Plains 2019
102 The Matriarchy** Win 13-3 234.85 Ignored Jun 29th Spirit of the Plains 2019
60 Crackle Loss 6-8 532.58 Jun 30th Spirit of the Plains 2019
72 Helix Loss 6-8 333.31 Jun 30th Spirit of the Plains 2019
103 Superior** Win 8-0 109.85 Ignored Jun 30th Spirit of the Plains 2019
87 Cold Cuts** Win 13-2 836.9 Ignored Aug 3rd Heavyweights 2019
94 Inferno** Win 13-4 689.54 Ignored Aug 3rd Heavyweights 2019
85 Lady Forward** Win 13-4 857.2 Ignored Aug 3rd Heavyweights 2019
91 MystiKuE** Win 13-0 781.29 Ignored Aug 3rd Heavyweights 2019
75 Viva Win 13-10 889.2 Aug 4th Heavyweights 2019
31 Fusion Loss 8-12 941.89 Aug 4th Heavyweights 2019
60 Crackle Win 13-5 1433.07 Aug 17th Cooler Classic 31
46 Indy Rogue Loss 6-11 553.47 Aug 17th Cooler Classic 31
90 Sureshot** Win 13-4 781.56 Ignored Aug 17th Cooler Classic 31
102 The Matriarchy** Win 13-0 234.85 Ignored Aug 17th Cooler Classic 31
62 Trainwreck Win 9-7 1049.01 Aug 18th Cooler Classic 31
46 Indy Rogue Loss 6-7 975.16 Aug 18th Cooler Classic 31
28 Wicked Loss 9-10 1285.01 Sep 7th West Plains Womens Club Sectional Championship 2019
76 Iowa Wild Rose Win 13-6 1079.76 Sep 7th West Plains Womens Club Sectional 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)