#50 CHAOS (3-9)

avg: 650.06  •  sd: 98.51  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
56 Calypso Loss 10-11 427.19 Jun 28th Club Terminus 2025
48 Magma Win 11-7 1173.7 Jun 28th Club Terminus 2025
47 Tabby Rosa Loss 8-10 453.02 Jun 28th Club Terminus 2025
56 Calypso Win 12-10 790.31 Jun 29th Club Terminus 2025
17 Ozone** Loss 3-13 927.54 Ignored Jun 29th Club Terminus 2025
47 Tabby Rosa Win 6-5 840.68 Jun 29th Club Terminus 2025
18 Outrage** Loss 5-15 915.9 Ignored Jul 12th 2025 Select Flight Invite East
6 Iris** Loss 2-14 1336.14 Ignored Jul 12th 2025 Select Flight Invite East
34 Brooklyn Book Club Loss 8-11 680.41 Jul 13th 2025 Select Flight Invite East
29 Wicked Loss 8-10 882.48 Jul 13th 2025 Select Flight Invite East
47 Tabby Rosa Loss 5-9 186.63 Jul 13th 2025 Select Flight Invite East
39 Zephyr Loss 4-7 386.4 Jul 13th 2025 Select Flight Invite East
**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)