#131 Absolute Zero (12-11)

avg: 966.06  •  sd: 61.39  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
67 Firefly Loss 6-14 682.6 Jun 9th Bay Area Ultimate Classic 2018
37 BW Ultimate Loss 4-11 900.56 Jun 9th Bay Area Ultimate Classic 2018
170 Spoiler Alert Loss 8-11 392.91 Jun 9th Bay Area Ultimate Classic 2018
190 DR Win 9-6 1053.72 Jun 10th Bay Area Ultimate Classic 2018
119 Buckwild Loss 6-8 730.6 Jun 10th Bay Area Ultimate Classic 2018
161 AC Bandits Win 10-5 1374.18 Jun 10th Bay Area Ultimate Classic 2018
210 VU Win 12-6 1105.96 Jul 21st Revolution 2018
- POWERLINE Loss 7-11 867.06 Jul 21st Revolution 2018
120 Mimosas Loss 9-11 773.75 Jul 21st Revolution 2018
- Happy Cows Win 11-6 878.48 Jul 22nd Revolution 2018
190 DR Win 12-11 760.15 Jul 22nd Revolution 2018
193 Feral Cows Win 9-7 895.1 Jul 22nd Revolution 2018
245 Hot Stix** Win 11-2 564.35 Ignored Aug 12th Mixed Club Summer Series 2018
190 DR Win 11-6 1181.84 Aug 12th Mixed Club Summer Series 2018
187 Megalodon Win 11-4 1243.4 Aug 12th Mixed Club Summer Series 2018
193 Feral Cows Win 11-5 1215.76 Aug 12th Mixed Club Summer Series 2018
136 Lawn Patrol Loss 5-11 348.72 Aug 12th Mixed Club Summer Series 2018
55 American Barbecue Loss 9-13 905.72 Sep 8th Nor Cal Mixed Sectional Championship 2018
17 Polar Bears** Loss 1-13 1139.68 Ignored Sep 8th Nor Cal Mixed Sectional Championship 2018
161 AC Bandits Win 13-7 1357.82 Sep 8th Nor Cal Mixed Sectional Championship 2018
67 Firefly Loss 11-13 1053.76 Sep 8th Nor Cal Mixed Sectional Championship 2018
120 Mimosas Loss 11-12 897.95 Sep 9th Nor Cal Mixed Sectional Championship 2018
136 Lawn Patrol Win 10-8 1211.39 Sep 9th Nor Cal 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)