#31 Rival (16-7)

avg: 1366.44  •  sd: 113.28  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
40 Hayride Win 15-4 1677.74 Jul 15th TCT Pro Elite Challenge East 2023
17 Ozone Loss 7-11 1219.5 Jul 15th TCT Pro Elite Challenge East 2023
14 Parcha Loss 9-10 1700.67 Jul 15th TCT Pro Elite Challenge East 2023
30 Tabby Rosa Loss 7-12 863.72 Jul 16th TCT Pro Elite Challenge East 2023
43 Zephyr Win 13-6 1625.29 Jul 29th TCT Select Flight East 2023
39 Brooklyn Book Club Loss 7-8 958.2 Jul 29th TCT Select Flight East 2023
55 Shiver Win 10-5 1444.55 Jul 29th TCT Select Flight East 2023
32 Crush City Win 13-9 1731.96 Jul 30th TCT Select Flight East 2023
34 Indy Rogue Loss 10-14 787.64 Jul 30th TCT Select Flight East 2023
18 Starling Ultimate Loss 10-13 1346.36 Jul 30th TCT Select Flight East 2023
83 Autonomous** Win 13-3 876.44 Ignored Sep 9th 2023 Womens East Plains Sectional Championship
80 Notorious C.L.E.** Win 13-2 902.98 Ignored Sep 9th 2023 Womens East Plains Sectional Championship
92 Sureshot** Win 13-0 647.83 Ignored Sep 9th 2023 Womens East Plains Sectional Championship
102 Solstice** Win 13-3 281.02 Ignored Sep 9th 2023 Womens East Plains Sectional Championship
96 Y'all** Win 13-0 595.64 Ignored Sep 10th 2023 Womens East Plains Sectional Championship
83 Autonomous** Win 15-3 876.44 Ignored Sep 10th 2023 Womens East Plains Sectional Championship
92 Sureshot** Win 15-2 647.83 Ignored Sep 10th 2023 Womens East Plains Sectional Championship
96 Y'all** Win 15-3 595.64 Ignored Sep 23rd 2023 Great Lakes Womens Regional Championship
83 Autonomous** Win 15-3 876.44 Ignored Sep 23rd 2023 Great Lakes Womens Regional Championship
62 Dish Win 15-8 1267.59 Sep 23rd 2023 Great Lakes Womens Regional Championship
34 Indy Rogue Win 15-10 1639.94 Sep 24th 2023 Great Lakes Womens Regional Championship
12 Nemesis Loss 8-15 1366.66 Sep 24th 2023 Great Lakes Womens Regional Championship
102 Solstice** Win 15-1 281.02 Ignored Sep 24th 2023 Great Lakes Womens Regional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)