#30 Colorado Small Batch (9-14)

avg: 1397.71  •  sd: 71.35  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
10 Traffic Loss 6-12 1357.92 Jun 22nd Eugene Summer Solstice 2019
1 Fury** Loss 2-13 1902.24 Ignored Jun 22nd Eugene Summer Solstice 2019
27 Elevate Win 10-7 1823.21 Jun 22nd Eugene Summer Solstice 2019
9 Nightlock Loss 7-8 1823.3 Jun 22nd Eugene Summer Solstice 2019
10 Traffic Loss 4-12 1337.23 Jun 23rd Eugene Summer Solstice 2019
38 FAB Win 10-7 1605.42 Jun 23rd Eugene Summer Solstice 2019
2 Seattle Riot** Loss 4-13 1813.39 Ignored Jun 23rd Eugene Summer Solstice 2019
25 Sneaky House Hippos Loss 8-9 1337.74 Jun 23rd Eugene Summer Solstice 2019
8 Schwa Loss 8-13 1489.33 Jul 13th TCT Pro Elite Challenge 2019
9 Nightlock Loss 2-13 1348.3 Jul 13th TCT Pro Elite Challenge 2019
20 Pop Win 13-9 2051.94 Jul 13th TCT Pro Elite Challenge 2019
28 Wicked Loss 6-9 991.45 Jul 14th TCT Pro Elite Challenge 2019
15 Nemesis Loss 6-10 1267.82 Jul 14th TCT Pro Elite Challenge 2019
21 Grit Loss 8-11 1247.67 Jul 14th TCT Pro Elite Challenge 2019
26 Virginia Rebellion Loss 8-13 951.54 Jul 27th TCT Select Flight Invite East 2019
20 Pop Loss 7-13 1075.84 Jul 27th TCT Select Flight Invite East 2019
39 Stella Win 12-11 1336.9 Jul 27th TCT Select Flight Invite East 2019
66 Hot Metal** Win 12-5 1319.64 Ignored Jul 27th TCT Select Flight Invite East 2019
27 Elevate Win 10-7 1823.21 Jul 28th TCT Select Flight Invite East 2019
33 Heist Loss 10-12 1133.6 Jul 28th TCT Select Flight Invite East 2019
62 Trainwreck** Win 15-4 1369.67 Ignored Sep 7th Rocky Mountain Womens Club Sectional Championship 2019
- COSMOS** Win 15-0 600 Ignored Sep 7th Rocky Mountain Womens Club Sectional Championship 2019
67 Jackwagon** Win 13-4 1310.59 Ignored Sep 7th Rocky Mountain 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)