#97 THE BODY (10-10)

avg: 1049.68  •  sd: 70.71  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
30 Mad Men Win 14-12 1717.04 Jun 29th Spirit of the Plains 2019
57 Cryptic Loss 12-13 1178.47 Jun 29th Spirit of the Plains 2019
76 DeMo Win 11-2 1770.86 Jun 29th Spirit of the Plains 2019
137 Kansas City Smokestack Win 5-1 1472.45 Jun 29th Spirit of the Plains 2019
45 Mallard Loss 5-12 797.23 Jun 30th Spirit of the Plains 2019
59 Scythe Loss 6-10 786.64 Jun 30th Spirit of the Plains 2019
103 Imperial Win 13-10 1362.2 Jun 30th Spirit of the Plains 2019
133 Kentucky Flying Circus Loss 8-13 388.77 Aug 3rd Heavyweights 2019
240 Ditto B** Win 13-3 456.15 Ignored Aug 3rd Heavyweights 2019
96 HouSE Loss 11-13 823.65 Aug 3rd Heavyweights 2019
193 Midnight Meat Train Win 13-6 1105.08 Aug 4th Heavyweights 2019
178 Milwaukee Revival Win 13-7 1166.6 Aug 4th Heavyweights 2019
156 Ditto A Win 13-9 1164.31 Aug 4th Heavyweights 2019
46 Haymaker Loss 6-13 796.63 Aug 17th Cooler Classic 31
73 Swans Win 13-8 1679.67 Aug 17th Cooler Classic 31
59 Scythe Loss 13-14 1157.8 Aug 17th Cooler Classic 31
103 Imperial Loss 6-13 434.06 Aug 17th Cooler Classic 31
111 Black Market II Loss 6-7 870.25 Aug 18th Cooler Classic 31
177 Red Bat Win 11-8 978.21 Aug 18th Cooler Classic 31
76 DeMo Loss 7-9 891.53 Aug 18th Cooler Classic 31
**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)