#237 Turnstyle (4-17)

avg: 205.28  •  sd: 83.92  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
18 Loco** Loss 1-15 1134.4 Ignored Jul 7th Philly Invite 2018
152 Peep Show** Loss 5-15 255.36 Ignored Jul 7th Philly Invite 2018
66 The Feminists** Loss 4-15 683.56 Ignored Jul 7th Philly Invite 2018
87 Sparkle Ponies Loss 9-15 661.95 Jul 7th Philly Invite 2018
- Philadelphia Forge Win 11-9 316.39 Jul 8th Philly Invite 2018
165 Unlimited Swipes Loss 8-13 292.1 Jul 8th Philly Invite 2018
163 Stoke Loss 2-15 196.61 Jul 8th Philly Invite 2018
133 Townies** Loss 4-15 361.15 Ignored Aug 4th White Mountain Mixed 2018
73 Chaotic Good** Loss 3-15 665.65 Ignored Aug 4th White Mountain Mixed 2018
214 Face Off Loss 6-10 -3.1 Aug 4th White Mountain Mixed 2018
181 RIMIX Loss 4-15 72.36 Aug 5th White Mountain Mixed 2018
209 DTH Loss 8-11 165.56 Aug 5th White Mountain Mixed 2018
220 Bees Win 12-11 528.91 Aug 25th The Incident 2018
239 Pandatime Loss 12-13 42.17 Aug 25th The Incident 2018
141 Powermove** Loss 6-15 293.51 Ignored Aug 25th The Incident 2018
158 Philly Twist Loss 7-15 215.1 Aug 25th The Incident 2018
239 Pandatime Win 9-8 292.17 Aug 26th The Incident 2018
232 Baltimore BENCH Win 8-7 414.24 Aug 26th The Incident 2018
231 BLT Stacks Loss 6-11 -248.02 Aug 26th The Incident 2018
83 Birds** Loss 3-13 625.54 Ignored Sep 8th Metro New York Mixed Sectional Championship 2018
220 Bees Loss 10-13 75.77 Sep 8th Metro New York 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)