#164 BATL Cows (11-15)

avg: 856.2  •  sd: 58.9  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
268 Orbit Win 12-3 898.04 Jun 15th ATL Classic 2019
47 Huntsville Outlaws** Loss 3-13 873.42 Ignored Jun 15th ATL Classic 2019
271 Bold City Win 13-6 887.31 Jun 15th ATL Classic 2019
235 Mississippi Blues Win 13-5 1085.91 Jun 15th ATL Classic 2019
278 Baywatch** Win 13-4 815.25 Ignored Jun 16th ATL Classic 2019
74 Trash Pandas Loss 6-12 694.57 Jun 16th ATL Classic 2019
130 m'kay Ultimate Loss 3-7 432.15 Jun 16th ATL Classic 2019
99 Mutiny Win 13-8 1666.64 Jul 20th 2019 Club Terminus
109 Shakedown Loss 5-13 541.92 Jul 20th 2019 Club Terminus
174 Magic City Mayhem Win 11-9 1035.37 Jul 20th 2019 Club Terminus
70 Memphis STAX Loss 10-12 1063.4 Jul 20th 2019 Club Terminus
130 m'kay Ultimate Loss 9-13 613.58 Jul 21st 2019 Club Terminus
99 Mutiny Loss 6-13 570.48 Jul 21st 2019 Club Terminus
174 Magic City Mayhem Win 9-8 911.17 Jul 21st 2019 Club Terminus
113 sKNO cone Loss 10-12 873.54 Aug 10th HoDown ShowDown 23 GOAT
38 Superlame** Loss 4-13 958.52 Ignored Aug 10th HoDown ShowDown 23 GOAT
74 Trash Pandas Loss 7-13 716.35 Aug 10th HoDown ShowDown 23 GOAT
99 Mutiny Loss 10-12 932.35 Aug 10th HoDown ShowDown 23 GOAT
159 Rowdy Win 14-10 1299.34 Aug 11th HoDown ShowDown 23 GOAT
89 FlyTrap Win 11-9 1449.92 Aug 11th HoDown ShowDown 23 GOAT
165 APEX Loss 13-15 630.93 Aug 11th HoDown ShowDown 23 GOAT
268 Orbit Win 10-8 560.71 Sep 7th East Coast Mixed Club Sectional Championship 2019
162 OutKast Loss 8-10 610.24 Sep 7th East Coast Mixed Club Sectional Championship 2019
34 'Shine** Loss 2-13 988.45 Ignored Sep 7th East Coast Mixed Club Sectional Championship 2019
225 Monster Win 13-8 1079.06 Sep 8th East Coast Mixed Club Sectional Championship 2019
165 APEX Loss 8-13 348.95 Sep 8th East Coast 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)