#148 Syndicate (7-12)

avg: 792.64  •  sd: 59.02  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
65 Dohrk Stor Loss 6-13 643.15 Jun 22nd Eugene Summer Solstice 2019
68 Sawtooth Loss 6-13 636.41 Jun 22nd Eugene Summer Solstice 2019
110 Oregon Eruption! Loss 5-8 555.57 Jun 22nd Eugene Summer Solstice 2019
19 Voodoo Loss 6-13 1091.19 Jun 22nd Eugene Summer Solstice 2019
162 Rip City Win 12-8 1155.37 Jun 23rd Eugene Summer Solstice 2019
194 Komori Win 15-10 949.11 Jun 23rd Eugene Summer Solstice 2019
123 CaSTLe Loss 6-11 376.92 Jul 20th The Royal Experience 2019
236 Identity Crisis** Win 13-1 610.25 Ignored Jul 20th The Royal Experience 2019
59 Scythe Loss 9-13 864.23 Jul 20th The Royal Experience 2019
76 DeMo Loss 8-13 674.7 Jul 20th The Royal Experience 2019
191 Yacht Club Loss 12-14 306.6 Jul 21st The Royal Experience 2019
219 Tsunami B Win 11-4 907.11 Jul 21st The Royal Experience 2019
236 Identity Crisis** Win 15-0 610.25 Ignored Jul 21st The Royal Experience 2019
161 Boulder United Flatiron Hammers Win 13-10 1043.44 Sep 7th Rocky Mountain Mens Club Sectional Championship 2019
113 Choice City Hops Loss 12-13 866.9 Sep 7th Rocky Mountain Mens Club Sectional Championship 2019
41 Inception** Loss 4-13 820.45 Ignored Sep 7th Rocky Mountain Mens Club Sectional Championship 2019
174 Daybreak Win 13-11 864.32 Sep 7th Rocky Mountain Mens Club Sectional Championship 2019
80 ISO Atmo Loss 4-13 546.91 Sep 8th Rocky Mountain Mens Club Sectional Championship 2019
80 ISO Atmo Loss 12-13 1021.91 Sep 8th Rocky Mountain 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)