#193 Feral Cows (7-11)

avg: 615.76  •  sd: 73.24  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
245 Hot Stix** Win 15-5 564.35 Ignored Jul 21st Revolution 2018
182 Sebastopol Orchard Loss 4-11 72.27 Jul 21st Revolution 2018
71 Robot** Loss 5-14 674.9 Ignored Jul 21st Revolution 2018
210 VU Win 10-7 916.32 Jul 22nd Revolution 2018
131 Absolute Zero Loss 7-9 686.72 Jul 22nd Revolution 2018
236 Delta Breeze Win 15-3 809.22 Jul 22nd Revolution 2018
131 Absolute Zero Loss 5-11 366.06 Aug 12th Mixed Club Summer Series 2018
190 DR Win 10-9 760.15 Aug 12th Mixed Club Summer Series 2018
187 Megalodon Win 10-8 906.07 Aug 12th Mixed Club Summer Series 2018
136 Lawn Patrol Loss 4-10 348.72 Aug 12th Mixed Club Summer Series 2018
37 BW Ultimate Loss 5-11 900.56 Sep 8th Nor Cal Mixed Sectional Championship 2018
35 Classy** Loss 4-11 913.71 Ignored Sep 8th Nor Cal Mixed Sectional Championship 2018
187 Megalodon Loss 9-11 394.19 Sep 8th Nor Cal Mixed Sectional Championship 2018
120 Mimosas Loss 7-11 556.06 Sep 8th Nor Cal Mixed Sectional Championship 2018
91 Argo Loss 6-11 618.26 Sep 8th Nor Cal Mixed Sectional Championship 2018
161 AC Bandits Loss 5-13 200.29 Sep 9th Nor Cal Mixed Sectional Championship 2018
190 DR Win 12-11 760.15 Sep 9th Nor Cal Mixed Sectional Championship 2018
182 Sebastopol Orchard Win 13-11 901.11 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)