#1 shame. (21-1)

avg: 2167.21  •  sd: 81.55  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
74 Sego** Win 15-2 1791.34 Ignored Jun 24th Colorado Summer Solstice 2023
102 Space Ghosts** Win 15-4 1638.16 Ignored Jun 24th Colorado Summer Solstice 2023
80 Flagstaff Ultimate** Win 15-4 1742.99 Ignored Jun 24th Colorado Summer Solstice 2023
32 Mile High Trash Win 12-8 2004.01 Jun 25th Colorado Summer Solstice 2023
35 Impact** Win 15-6 2117.09 Ignored Jun 25th Colorado Summer Solstice 2023
31 Kansas City United Win 13-7 2152.69 Jun 25th Colorado Summer Solstice 2023
2 Drag'n Thrust Win 15-14 2197.18 Aug 4th 2023 US Open Club Championships ICC
8 NOISE Win 15-8 2458.69 Aug 4th 2023 US Open Club Championships ICC
11 Seattle Mixtape Win 15-12 2174.52 Aug 5th 2023 US Open Club Championships ICC
3 AMP Loss 12-15 1767.36 Aug 5th 2023 US Open Club Championships ICC
18 Polar Bears Win 15-6 2361.21 Aug 6th 2023 US Open Club Championships ICC
43 Dirty Bird Win 15-8 2043.13 Aug 19th TCT Elite Select Challenge 2023
6 Sprocket Win 15-10 2378.57 Aug 19th TCT Elite Select Challenge 2023
17 Lawless Win 15-11 2144.35 Aug 19th TCT Elite Select Challenge 2023
14 Rally Win 15-8 2398.55 Aug 20th TCT Elite Select Challenge 2023
9 Space Force Win 15-12 2191.19 Aug 20th TCT Elite Select Challenge 2023
6 Sprocket Win 15-10 2378.57 Aug 20th TCT Elite Select Challenge 2023
239 Central Arkansas Surge** Win 15-0 770 Ignored Sep 23rd 2023 South Central Mixed Regional Championship
102 Space Ghosts** Win 15-2 1638.16 Ignored Sep 23rd 2023 South Central Mixed Regional Championship
85 Risky Business Win 14-7 1709.36 Sep 24th 2023 South Central Mixed Regional Championship
21 Love Tractor Win 15-9 2222.51 Sep 24th 2023 South Central Mixed Regional Championship
32 Mile High Trash** Win 14-6 2162.85 Ignored Sep 24th 2023 South Central Mixed 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)