#164 Enough Monkeys (7-9)

avg: 795.85  •  sd: 97.1  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
57 Heartless Loss 8-12 872.51 Jul 7th AntlerLock 2018
124 Albany Airbenders Loss 8-12 570.95 Jul 7th AntlerLock 2018
150 Scarecrow Win 12-11 992.4 Jul 7th AntlerLock 2018
214 Face Off Loss 9-12 147.69 Jul 7th AntlerLock 2018
220 Bees Win 15-9 919.39 Jul 8th AntlerLock 2018
189 DTX Win 15-9 1156.52 Jul 8th AntlerLock 2018
195 Rainbow Win 15-5 1195.18 Aug 4th White Mountain Mixed 2018
33 League of Shadows Loss 7-15 935.95 Aug 4th White Mountain Mixed 2018
209 DTH Win 15-13 745.35 Aug 4th White Mountain Mixed 2018
189 DTX Loss 13-15 426.86 Aug 4th White Mountain Mixed 2018
73 Chaotic Good Loss 11-15 884.48 Aug 5th White Mountain Mixed 2018
195 Rainbow Win 9-6 1013.75 Aug 5th White Mountain Mixed 2018
189 DTX Loss 7-13 83.5 Aug 5th White Mountain Mixed 2018
58 Happy Valley Loss 7-15 711.42 Sep 8th West New England Mixed Sectional Championship 2018
57 Heartless Loss 12-15 1013.17 Sep 8th West New England Mixed Sectional Championship 2018
154 Default Win 14-13 972.13 Sep 8th West New England 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)