#244 Natural Twenties (3-13)

avg: 407.71  •  sd: 69.12  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
276 SkyLab Loss 8-12 -252.7 Jun 29th Rose City Rumble 2019
146 Igneous Ultimate Loss 7-15 284.28 Jun 29th Rose City Rumble 2019
161 Breakers Mark Loss 8-14 291.5 Jun 29th Rose City Rumble 2019
95 Garbage** Loss 3-15 523.25 Ignored Jun 29th Rose City Rumble 2019
82 Happy Hour** Loss 4-15 591.14 Ignored Aug 3rd Kleinman Eruption 2019
157 Choco Ghost House Loss 10-11 718.38 Aug 3rd Kleinman Eruption 2019
64 Donuts** Loss 2-15 672.77 Ignored Aug 3rd Kleinman Eruption 2019
253 Friendzone Win 12-11 466.63 Aug 3rd Kleinman Eruption 2019
95 Garbage Loss 9-15 607.77 Aug 4th Kleinman Eruption 2019
161 Breakers Mark Loss 13-14 702.53 Aug 4th Kleinman Eruption 2019
276 SkyLab Win 10-8 451.12 Sep 7th Oregon Mixed Club Sectional Championship 2019
67 The Administrators Loss 8-13 759.02 Sep 7th Oregon Mixed Club Sectional Championship 2019
157 Choco Ghost House Loss 8-12 402.22 Sep 7th Oregon Mixed Club Sectional Championship 2019
125 Hive** Loss 3-13 420.76 Ignored Sep 7th Oregon Mixed Club Sectional Championship 2019
223 Eugene Skyfall Loss 8-15 -28.59 Sep 8th Oregon Mixed Club Sectional Championship 2019
276 SkyLab Win 15-14 313.46 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)