#46 Indy Rogue (16-5)

avg: 1100.16  •  sd: 71.02  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
65 Eliza Furnace Win 12-8 1166.93 Jun 22nd SCINNY 2019
97 Belle** Win 15-4 426.63 Ignored Jun 22nd SCINNY 2019
90 Sureshot** Win 15-3 781.56 Ignored Jun 22nd SCINNY 2019
85 Lady Forward Win 14-7 840.08 Jun 22nd SCINNY 2019
84 Autonomous Win 15-7 895.43 Jun 23rd SCINNY 2019
64 Notorious C.L.E. Win 15-7 1335.54 Jun 23rd SCINNY 2019
26 Virginia Rebellion Loss 5-13 847.7 Jul 27th TCT Select Flight Invite East 2019
38 FAB Loss 4-13 615.76 Jul 27th TCT Select Flight Invite East 2019
12 Rival** Loss 5-13 1313.04 Ignored Jul 27th TCT Select Flight Invite East 2019
24 Salty Loss 11-12 1338.7 Jul 27th TCT Select Flight Invite East 2019
55 Dish Loss 9-13 457.12 Jul 28th TCT Select Flight Invite East 2019
66 Hot Metal Win 13-7 1277.17 Jul 28th TCT Select Flight Invite East 2019
87 Cold Cuts** Win 13-4 836.9 Ignored Aug 17th Cooler Classic 31
60 Crackle Win 12-9 1178.44 Aug 17th Cooler Classic 31
53 Stellar Win 11-6 1518.93 Aug 17th Cooler Classic 31
76 Iowa Wild Rose** Win 13-4 1079.76 Ignored Aug 17th Cooler Classic 31
60 Crackle Win 6-4 1198.68 Aug 18th Cooler Classic 31
53 Stellar Win 7-6 1097.24 Aug 18th Cooler Classic 31
55 Dish Win 13-4 1475.68 Sep 7th Central Plains Womens Club Sectional Championship 2019
106 Frenzy** Win 13-1 600 Ignored Sep 7th Central Plains Womens Club Sectional Championship 2019
72 Helix Win 13-9 1052.36 Sep 7th Central 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)