#177 Red Bat (5-19)

avg: 612.6  •  sd: 53.96  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
103 Imperial Loss 9-13 615.49 Jun 29th Spirit of the Plains 2019
191 Yacht Club Win 12-11 652.56 Jun 29th Spirit of the Plains 2019
18 Yogosbo** Loss 4-13 1116.13 Ignored Jun 29th Spirit of the Plains 2019
30 Mad Men Loss 6-11 949.39 Jun 30th Spirit of the Plains 2019
73 Swans Loss 3-10 583.51 Jun 30th Spirit of the Plains 2019
137 Kansas City Smokestack Loss 5-13 272.45 Jun 30th Spirit of the Plains 2019
116 Timber Loss 5-13 368.84 Jul 13th The Bropen 2019
33 Nain Rouge** Loss 2-13 878.8 Ignored Jul 13th The Bropen 2019
96 HouSE Loss 6-13 452.49 Jul 13th The Bropen 2019
98 Minnesota Superior U20B Loss 8-11 682.39 Jul 13th The Bropen 2019
18 Yogosbo** Loss 5-13 1116.13 Ignored Jul 13th The Bropen 2019
178 Milwaukee Revival Loss 9-10 484.07 Jul 14th The Bropen 2019
178 Milwaukee Revival Win 13-9 1027.63 Aug 17th Cooler Classic 31
103 Imperial Loss 2-13 434.06 Aug 17th Cooler Classic 31
137 Kansas City Smokestack Loss 6-13 272.45 Aug 17th Cooler Classic 31
97 THE BODY Loss 8-11 684.07 Aug 18th Cooler Classic 31
116 Timber Loss 5-11 368.84 Aug 18th Cooler Classic 31
184 Chimney Win 9-8 681.37 Aug 18th Cooler Classic 31
57 Cryptic Loss 5-11 703.47 Sep 7th West Plains Mens Club Sectional Championship 2019
- Miner Magic Win 11-6 987.41 Sep 7th West Plains Mens Club Sectional Championship 2019
59 Scythe** Loss 4-11 682.8 Ignored Sep 7th West Plains Mens Club Sectional Championship 2019
137 Kansas City Smokestack Loss 8-11 506.84 Sep 7th West Plains Mens Club Sectional Championship 2019
123 CaSTLe Loss 5-15 323.61 Sep 8th West Plains Mens Club Sectional Championship 2019
191 Yacht Club Win 13-8 1023.72 Sep 8th West Plains 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)