#60 Crackle (11-11)

avg: 833.07  •  sd: 55.7  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
76 Iowa Wild Rose Win 13-4 1079.76 Jun 29th Spirit of the Plains 2019
91 MystiKuE** Win 13-1 781.29 Ignored Jun 29th Spirit of the Plains 2019
31 Fusion Loss 6-12 803.73 Jun 29th Spirit of the Plains 2019
53 Stellar Win 8-6 1272.73 Jun 30th Spirit of the Plains 2019
31 Fusion Loss 4-9 783.04 Jun 30th Spirit of the Plains 2019
72 Helix Win 8-3 1233.8 Jun 30th Spirit of the Plains 2019
10 Traffic** Loss 4-15 1337.23 Ignored Jul 13th TCT Select Flight Invite West 2019
57 Outbreak Loss 7-11 397.47 Jul 13th TCT Select Flight Invite West 2019
67 Jackwagon Win 10-8 973.25 Jul 13th TCT Select Flight Invite West 2019
40 Pine Baroness Loss 7-13 651.51 Jul 14th TCT Select Flight Invite West 2019
51 Fiasco Win 7-6 1148.87 Jul 14th TCT Select Flight Invite West 2019
38 FAB Loss 3-13 615.76 Jul 14th TCT Select Flight Invite West 2019
62 Trainwreck Win 13-9 1188.24 Aug 17th Cooler Classic 31
46 Indy Rogue Loss 9-12 754.8 Aug 17th Cooler Classic 31
76 Iowa Wild Rose Win 13-7 1037.3 Aug 17th Cooler Classic 31
53 Stellar Loss 5-13 372.24 Aug 17th Cooler Classic 31
62 Trainwreck Loss 5-6 644.67 Aug 18th Cooler Classic 31
46 Indy Rogue Loss 4-6 734.55 Aug 18th Cooler Classic 31
87 Cold Cuts Win 12-5 836.9 Sep 7th Northwest Plains Womens Club Sectional Championship 2019
91 MystiKuE** Win 13-3 781.29 Ignored Sep 7th Northwest Plains Womens Club Sectional Championship 2019
85 Lady Forward Win 13-7 814.73 Sep 7th Northwest Plains Womens Club Sectional Championship 2019
31 Fusion Loss 5-13 783.04 Sep 7th Northwest 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)