#138 Choco Ghost House (10-7)

avg: 994.75  •  sd: 55.41  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
82 Pegasus Win 12-11 1370.6 Jun 29th Rose City Rumble 2019
87 Garbage Loss 10-15 751.76 Jun 29th Rose City Rumble 2019
272 SkyLab Win 15-7 875.16 Jun 29th Rose City Rumble 2019
150 Igneous Ultimate Win 15-10 1378.66 Jun 29th Rose City Rumble 2019
250 Friendzone Win 15-5 1016.85 Aug 3rd Kleinman Eruption 2019
232 Natural Twenties Win 11-10 616.54 Aug 3rd Kleinman Eruption 2019
77 Happy Hour Loss 9-10 1144.36 Aug 3rd Kleinman Eruption 2019
59 Donuts Loss 7-15 783.86 Aug 3rd Kleinman Eruption 2019
245 Mola Mola Win 15-4 1053.96 Aug 4th Kleinman Eruption 2019
95 Platypi Win 15-14 1303.4 Aug 4th Kleinman Eruption 2019
87 Garbage Loss 9-14 731.5 Aug 4th Kleinman Eruption 2019
272 SkyLab Win 13-7 832.69 Sep 7th Oregon Mixed Club Sectional Championship 2019
232 Natural Twenties Win 12-8 932.69 Sep 7th Oregon Mixed Club Sectional Championship 2019
64 The Administrators Loss 9-13 926.39 Sep 7th Oregon Mixed Club Sectional Championship 2019
127 Hive Win 9-8 1172.23 Sep 7th Oregon Mixed Club Sectional Championship 2019
36 Garage Sale Loss 11-14 1250.04 Sep 8th Oregon Mixed Club Sectional Championship 2019
77 Happy Hour Loss 10-14 870.66 Sep 8th Oregon 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)