#222 Monster (10-16)

avg: 541.18  •  sd: 68.59  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
283 Craw Daddies Win 9-5 630.43 Jul 6th Huntsville Huckfest 2019
35 'Shine Loss 10-13 1197.76 Jul 6th Huntsville Huckfest 2019
158 OutKast Loss 6-13 239.42 Jul 6th Huntsville Huckfest 2019
228 The Umbrella Loss 10-13 141.9 Jul 6th Huntsville Huckfest 2019
165 Possum Loss 8-15 240.71 Jul 7th Huntsville Huckfest 2019
231 Mississippi Blues Win 13-7 1012.87 Jul 7th Huntsville Huckfest 2019
284 Mixed on the Rock Win 15-5 680.36 Jul 7th Huntsville Huckfest 2019
251 Big Bend Win 12-7 883.87 Jul 12th Swan Boat 2019
206 FIRE ULTIMATE CLUB MIAMI Loss 10-11 490.77 Jul 12th Swan Boat 2019
155 Jackpot Loss 8-10 594.24 Jul 12th Swan Boat 2019
252 Mixchief Win 9-3 956.35 Jul 13th Swan Boat 2019
94 Mutiny Loss 7-15 528.81 Jul 14th Swan Boat 2019
278 Baywatch Win 15-10 618.5 Jul 14th Swan Boat 2019
206 FIRE ULTIMATE CLUB MIAMI Win 13-7 1173.3 Jul 14th Swan Boat 2019
254 Derby City Thunder Loss 9-11 80.13 Aug 17th Mudbowl 2019
231 Mississippi Blues Loss 8-12 14.18 Aug 17th Mudbowl 2019
158 OutKast Win 11-10 964.42 Aug 17th Mudbowl 2019
170 Magic City Mayhem Loss 11-13 534.31 Aug 18th Mudbowl 2019
231 Mississippi Blues Loss 8-10 192.67 Aug 18th Mudbowl 2019
298 The Leftovers Win 7-2 600 Ignored Aug 18th Mudbowl 2019
189 Hairy Otter Win 12-8 1107.12 Sep 7th East Coast Mixed Club Sectional Championship 2019
160 APEX Loss 7-13 271.08 Sep 7th East Coast Mixed Club Sectional Championship 2019
130 m'kay Ultimate Loss 8-13 489.25 Sep 7th East Coast Mixed Club Sectional Championship 2019
68 JLP** Loss 3-13 645.59 Ignored Sep 7th East Coast Mixed Club Sectional Championship 2019
162 BATL Cows Loss 8-13 323.09 Sep 8th East Coast Mixed Club Sectional Championship 2019
165 Possum Loss 5-13 205.52 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)