#46 Shiver (7-5)

avg: 727.66  •  sd: 78.2  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
62 Fiasco Win 10-4 883.05 Jun 28th Club Terminus 2025
38 Juice Box Loss 4-11 299.75 Jun 28th Club Terminus 2025
17 Ozone** Loss 4-11 927.54 Ignored Jun 28th Club Terminus 2025
68 cATLanta** Win 11-3 592.55 Ignored Jun 28th Club Terminus 2025
56 Calypso Win 13-10 880.33 Jun 29th Club Terminus 2025
48 Magma Loss 6-11 160.11 Jun 29th Club Terminus 2025
17 Ozone Loss 6-13 927.54 Jun 29th Club Terminus 2025
48 Magma Win 11-9 956.01 Jul 12th Filling the Void Mens Womens 2025
- Roseate Spoonbill** Win 12-1 600 Ignored Jul 12th Filling the Void Mens Womens 2025
44 Wave Loss 10-11 624.67 Jul 12th Filling the Void Mens Womens 2025
- Roseate Spoonbill** Win 15-2 600 Ignored Jul 13th Filling the Void Mens Womens 2025
44 Wave Win 11-9 998.87 Jul 13th Filling the Void Mens Womens 2025
**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)