#231 Black Market III (1-16)

avg: 135.41  •  sd: 75.81  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
154 Foxtrot** Loss 5-13 161.61 Ignored Aug 3rd Heavyweights 2019
82 Black Lung** Loss 3-13 526.33 Ignored Aug 3rd Heavyweights 2019
100 Timber** Loss 2-13 441.48 Ignored Aug 3rd Heavyweights 2019
237 Kettering Win 13-10 286.53 Aug 4th Heavyweights 2019
193 Carolina Sky Loss 8-13 11.93 Aug 4th Heavyweights 2019
129 Kentucky Flying Circus** Loss 2-13 298.44 Ignored Aug 24th Indy Invite Club 2019
149 Ditto A** Loss 4-13 174.9 Ignored Aug 24th Indy Invite Club 2019
128 Enigma Loss 7-13 341.59 Aug 24th Indy Invite Club 2019
169 MomINtuM Loss 3-15 72.06 Aug 25th Indy Invite Club 2019
224 Bird Patrol Loss 9-10 137.11 Aug 25th Indy Invite Club 2019
149 Ditto A Loss 9-15 259.42 Aug 25th Indy Invite Club 2019
169 MomINtuM Loss 9-13 253.49 Sep 7th Central Plains Mens Club Sectional Championship 2019
117 Satellite Loss 7-13 399.66 Sep 7th Central Plains Mens Club Sectional Championship 2019
149 Ditto A Loss 7-13 217.37 Sep 7th Central Plains Mens Club Sectional Championship 2019
21 Brickyard** Loss 0-13 1087.79 Ignored Sep 7th Central Plains Mens Club Sectional Championship 2019
222 Nasty Girls Loss 7-15 -336.98 Sep 8th Central Plains Mens Club Sectional Championship 2019
224 Bird Patrol Loss 11-15 -119.05 Sep 8th Central Plains Mens 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)