#17 Ozone (16-5)

avg: 1686.4  •  sd: 72.31  •  top 16/20: 42.3%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
75 Calypso** Win 13-1 1054.85 Ignored Jul 8th Club Terminus 2023
44 Juice Box** Win 13-5 1588.44 Ignored Jul 8th Club Terminus 2023
67 Magma** Win 13-1 1198.14 Ignored Jul 8th Club Terminus 2023
35 Huntsville Laika Win 13-5 1772.59 Jul 9th Club Terminus 2023
67 Magma** Win 13-0 1198.14 Ignored Jul 9th Club Terminus 2023
78 cATLanta** Win 13-1 959.22 Ignored Jul 9th Club Terminus 2023
40 Hayride Win 15-8 1642.55 Jul 15th TCT Pro Elite Challenge East 2023
31 Rival Win 11-7 1833.33 Jul 15th TCT Pro Elite Challenge East 2023
14 Parcha Loss 10-11 1700.67 Jul 15th TCT Pro Elite Challenge East 2023
7 BENT Loss 7-13 1573.9 Jul 16th TCT Pro Elite Challenge East 2023
23 Flight Loss 9-12 1194.04 Aug 19th TCT Elite Select Challenge 2023
54 Stellar** Win 15-6 1476.94 Ignored Aug 19th TCT Elite Select Challenge 2023
9 Schwa Loss 5-15 1501.71 Aug 19th TCT Elite Select Challenge 2023
38 FAB Win 14-4 1719.26 Aug 20th TCT Elite Select Challenge 2023
29 Pop Win 13-7 1959.66 Aug 20th TCT Elite Select Challenge 2023
30 Tabby Rosa Win 9-8 1509.24 Aug 20th TCT Elite Select Challenge 2023
58 Fiasco** Win 15-1 1389.62 Ignored Sep 23rd 2023 Southeast Womens Regional Championship
35 Huntsville Laika Win 15-3 1772.59 Sep 23rd 2023 Southeast Womens Regional Championship
44 Juice Box** Win 13-0 1588.44 Ignored Sep 23rd 2023 Southeast Womens Regional Championship
67 Magma** Win 15-4 1198.14 Ignored Sep 24th 2023 Southeast Womens Regional Championship
2 Phoenix Loss 9-15 1964.26 Sep 24th 2023 Southeast 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)