#62 Shade (14-9)

avg: 1449.64  •  sd: 57.58  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
158 Alibi Win 13-2 1487.94 Jul 15th Boston Invite 2023
137 Expendables Win 13-7 1555.94 Jul 15th Boston Invite 2023
72 Colt Win 12-8 1830.44 Jul 15th Boston Invite 2023
163 Crossfire Win 13-4 1459.38 Jul 15th Boston Invite 2023
51 TireBizFriz Loss 10-15 1098.9 Aug 5th Vacationland
154 Odyssey Win 9-4 1494.28 Aug 5th Vacationland
231 Madhouse** Win 15-3 1023.21 Ignored Aug 5th Vacationland
32 Scoop Loss 12-15 1375.08 Aug 6th Vacationland
71 Big Wrench Loss 11-13 1166.17 Aug 6th Vacationland
79 Red Tide Win 15-13 1586.1 Aug 6th Vacationland
246 Army-West Point** Win 13-3 771.41 Ignored Sep 9th 2023 Mens Metro New York Sectional Championship
230 Bartle Boys** Win 13-1 1030.92 Ignored Sep 9th 2023 Mens Metro New York Sectional Championship
72 Colt Win 13-10 1717.42 Sep 9th 2023 Mens Metro New York Sectional Championship
209 Long Island Riff Raff** Win 13-3 1189.54 Ignored Sep 9th 2023 Mens Metro New York Sectional Championship
24 Blueprint Loss 8-15 1199.71 Sep 10th 2023 Mens Metro New York Sectional Championship
72 Colt Loss 11-14 1075.94 Sep 10th 2023 Mens Metro New York Sectional Championship
7 DiG** Loss 5-13 1567.51 Ignored Sep 23rd 2023 Northeast Mens Regional Championship
43 Mystery Box Loss 8-13 1101.38 Sep 23rd 2023 Northeast Mens Regional Championship
44 Red Circus Loss 11-12 1460.84 Sep 23rd 2023 Northeast Mens Regional Championship
72 Colt Win 13-9 1807.85 Sep 23rd 2023 Northeast Mens Regional Championship
71 Big Wrench Win 11-9 1644.21 Sep 24th 2023 Northeast Mens Regional Championship
51 TireBizFriz Win 13-7 2110.03 Sep 24th 2023 Northeast Mens Regional Championship
72 Colt Loss 8-12 948.13 Sep 24th 2023 Northeast Mens 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)