#193 Hairy Otter (8-10)

avg: 705.18  •  sd: 73.94  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
140 Crucible Loss 8-12 542.3 Jul 20th Bourbon Bash 2019
257 Derby City Thunder Win 14-4 977.02 Jul 20th Bourbon Bash 2019
170 Thunderpants the Magic Dragon Loss 9-14 333.31 Jul 20th Bourbon Bash 2019
249 Second Wind Win 13-8 918.98 Jul 20th Bourbon Bash 2019
196 Petey's Scallywags Loss 9-10 575.71 Jul 21st Bourbon Bash 2019
175 Moonshine Win 11-10 906.83 Jul 21st Bourbon Bash 2019
217 Pi+ Loss 5-7 286.9 Jul 21st Bourbon Bash 2019
174 Magic City Mayhem Loss 6-13 186.17 Aug 17th Mudbowl 2019
298 The Leftovers** Win 13-2 600 Ignored Aug 17th Mudbowl 2019
119 Seoulmates Loss 7-11 622.64 Aug 17th Mudbowl 2019
162 OutKast Win 13-10 1201.05 Aug 18th Mudbowl 2019
235 Mississippi Blues Win 13-8 982.07 Aug 18th Mudbowl 2019
119 Seoulmates Loss 8-13 593.38 Aug 18th Mudbowl 2019
40 Murmur** Loss 3-13 940.03 Ignored Sep 7th East Coast Mixed Club Sectional Championship 2019
74 Trash Pandas Loss 7-13 716.35 Sep 7th East Coast Mixed Club Sectional Championship 2019
230 The Umbrella Win 13-8 1009.63 Sep 7th East Coast Mixed Club Sectional Championship 2019
225 Monster Loss 8-12 141.75 Sep 7th East Coast Mixed Club Sectional Championship 2019
230 The Umbrella Win 13-6 1113.47 Sep 8th East Coast 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)