#230 EDM (1-15)

avg: 304.08  •  sd: 109.69  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
76 All Jeeps, All Night Loss 7-11 786.47 Jun 17th Colorado Mixed Round Robin 2018
138 The Strangers** Loss 1-11 339.56 Ignored Jun 17th Colorado Mixed Round Robin 2018
- Old Rush Loss 6-11 259.84 Jun 17th Colorado Mixed Round Robin 2018
145 Pandamonium Loss 1-13 285.38 Aug 4th Heavyweights 2018
111 panIC** Loss 4-13 466.49 Ignored Aug 4th Heavyweights 2018
172 Los Heros Loss 1-13 144.78 Aug 4th Heavyweights 2018
211 Stackcats Loss 4-13 -81.02 Aug 5th Heavyweights 2018
246 Taco Cat Win 11-7 370.72 Aug 5th Heavyweights 2018
76 All Jeeps, All Night** Loss 2-13 653.36 Ignored Aug 25th Castle Rock Mixed 2018
138 The Strangers Loss 6-12 360.25 Aug 25th Castle Rock Mixed 2018
169 Springs Mixed Ulty Team Loss 6-13 165.88 Aug 25th Castle Rock Mixed 2018
43 Flight Club** Loss 2-15 873.13 Ignored Sep 8th Rocky Mountain Mixed Sectional Championship 2018
89 Sweet Action** Loss 1-15 569.03 Ignored Sep 8th Rocky Mountain Mixed Sectional Championship 2018
169 Springs Mixed Ulty Team Loss 12-15 465.38 Sep 8th Rocky Mountain Mixed Sectional Championship 2018
- Eggshells** Loss 6-15 365.72 Sep 9th Rocky Mountain Mixed Sectional Championship 2018
169 Springs Mixed Ulty Team Loss 10-15 312.27 Sep 9th Rocky Mountain Mixed Sectional Championship 2018
**Blowout Eligible

FAQ

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
  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
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)