#199 HAOS (11-13)

avg: 696.95  •  sd: 56  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
264 Albany Airbenders Win 12-7 852.36 Jul 6th AntlerLock 2019
224 Side Hustle Loss 12-14 364.87 Jul 6th AntlerLock 2019
97 Sunken Circus Loss 7-11 710.97 Jul 6th AntlerLock 2019
124 Happy Valley Loss 7-15 467.36 Jul 7th AntlerLock 2019
137 Default Loss 10-13 671.92 Jul 7th AntlerLock 2019
168 WHUF* Win 8-5 1287.72 Jul 7th AntlerLock 2019
- Cool Whip** Win 15-2 600 Ignored Jul 20th Vacationland 2019
275 Dead Reckoning Win 15-4 849.24 Jul 20th Vacationland 2019
148 Scarecrow Win 9-8 1053.71 Jul 20th Vacationland 2019
264 Albany Airbenders Win 13-3 931.85 Jul 21st Vacationland 2019
133 Night Shift Loss 8-10 757.39 Jul 21st Vacationland 2019
212 Sorted Beans Win 10-6 1145.76 Jul 21st Vacationland 2019
216 Espionage Loss 11-12 493.95 Aug 24th The Incident 2019 Age of Ultimatron
143 Superstition Loss 8-12 509.13 Aug 24th The Incident 2019 Age of Ultimatron
180 Varsity Loss 10-12 534.65 Aug 24th The Incident 2019 Age of Ultimatron
85 HVAC Loss 5-13 631.84 Aug 24th The Incident 2019 Age of Ultimatron
270 Baltimore BENCH Win 11-4 892.64 Aug 25th The Incident 2019 Age of Ultimatron
264 Albany Airbenders Win 11-7 798.74 Aug 25th The Incident 2019 Age of Ultimatron
293 Turnstyle** Win 13-3 439.57 Ignored Aug 25th The Incident 2019 Age of Ultimatron
285 Drunk in Space Win 15-6 731.84 Sep 7th East New England Mixed Club Sectional Championship 2019
212 Sorted Beans Loss 10-11 524.6 Sep 7th East New England Mixed Club Sectional Championship 2019
5 Wild Card** Loss 1-15 1402.74 Ignored Sep 7th East New England Mixed Club Sectional Championship 2019
206 DTH Loss 10-11 549.83 Sep 8th East New England Mixed Club Sectional Championship 2019
210 Face Off Loss 10-12 419.75 Sep 8th East New England Mixed Club Sectional Championship 2019
**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)