#17 Showdown (13-11)

avg: 1680.21  •  sd: 151.31  •  top 16/20: 44.5%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
31 Heist Win 11-8 1673.17 Jul 13th TCT Pro Elite Challenge 2019
4 Molly Brown Loss 9-13 1861.98 Jul 13th TCT Pro Elite Challenge 2019
14 Nemesis Loss 8-10 1511.85 Jul 13th TCT Pro Elite Challenge 2019
5 6ixers Loss 7-13 1697.42 Jul 14th TCT Pro Elite Challenge 2019
13 Rival Loss 7-8 1710.07 Jul 14th TCT Pro Elite Challenge 2019
14 Nemesis Loss 9-10 1649.52 Jul 14th TCT Pro Elite Challenge 2019
10 Nightlock Win 12-8 2398.79 Jul 14th TCT Pro Elite Challenge 2019
11 Wildfire Loss 11-14 1553.66 Aug 17th TCT Elite Select Challenge 2019
54 Dish** Win 15-4 1501.33 Ignored Aug 17th TCT Elite Select Challenge 2019
15 Ozone Loss 10-15 1273.05 Aug 17th TCT Elite Select Challenge 2019
19 Underground Loss 9-10 1536.27 Aug 18th TCT Elite Select Challenge 2019
21 BENT Loss 7-8 1460.97 Aug 18th TCT Elite Select Challenge 2019
13 Rival Loss 7-8 1710.07 Aug 18th TCT Elite Select Challenge 2019
22 LOL Win 11-5 2129.16 Aug 18th TCT Elite Select Challenge 2019
92 Austin Hex** Win 11-0 774.56 Ignored Sep 7th Texas Womens Club Sectional Championship 2019
102 Cazadora** Win 11-0 284.7 Ignored Sep 7th Texas Womens Club Sectional Championship 2019
50 Crush City Win 11-6 1546 Sep 7th Texas Womens Club Sectional Championship 2019
83 Inferno** Win 11-0 908.17 Ignored Sep 7th Texas Womens Club Sectional Championship 2019
97 Maeve** Win 11-0 505.4 Ignored Sep 7th Texas Womens Club Sectional Championship 2019
61 Trainwreck** Win 13-0 1409.84 Ignored Sep 21st South Central Club Womens Regional Championship 2019
50 Crush City** Win 13-4 1599.31 Ignored Sep 21st South Central Club Womens Regional Championship 2019
83 Inferno** Win 13-2 908.17 Ignored Sep 21st South Central Club Womens Regional Championship 2019
28 Colorado Small Batch Win 10-8 1658.24 Sep 22nd South Central Club Womens Regional Championship 2019
4 Molly Brown Loss 7-13 1723.02 Sep 22nd South Central 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)