#185 Boomtown Pandas (13-13)

avg: 650.51  •  sd: 68.2  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
112 Mojo Jojo Loss 4-11 462.39 Jul 14th MN Ultimate Disc Invitational 2018
202 Great Minnesota Get Together Win 9-8 678.8 Jul 14th MN Ultimate Disc Invitational 2018
- MN Superior Loss 2-11 57.29 Jul 14th MN Ultimate Disc Invitational 2018
247 Macalester College[C] Win 11-6 415.62 Jul 14th MN Ultimate Disc Invitational 2018
184 Mousetrap Loss 8-10 395.41 Jul 15th MN Ultimate Disc Invitational 2018
228 Mixed Duluth Win 9-8 453.27 Jul 15th MN Ultimate Disc Invitational 2018
48 Rubix Loss 5-11 778.83 Jul 15th MN Ultimate Disc Invitational 2018
191 Coalition Ultimate Loss 4-11 19.68 Jul 15th MN Ultimate Disc Invitational 2018
186 Jabba Loss 10-13 322.05 Aug 4th Heavyweights 2018
97 tHUMP Loss 5-13 539.88 Aug 4th Heavyweights 2018
211 Stackcats Win 10-6 1015.14 Aug 4th Heavyweights 2018
145 Pandamonium Loss 7-11 418.49 Aug 4th Heavyweights 2018
235 Skyhawks Win 12-3 844.51 Aug 5th Heavyweights 2018
217 Mastodon Win 13-6 1083.04 Aug 5th Heavyweights 2018
111 panIC Loss 6-13 466.49 Aug 18th Cooler Classic 30
186 Jabba Win 13-12 775.2 Aug 18th Cooler Classic 30
249 LudICRous** Win 13-4 379.2 Ignored Aug 18th Cooler Classic 30
191 Coalition Ultimate Win 13-7 1177.21 Aug 18th Cooler Classic 30
166 Spirit Fowl Loss 13-14 662.68 Aug 19th Cooler Classic 30
146 Prion Win 13-12 1010.02 Aug 19th Cooler Classic 30
186 Jabba Win 15-11 1031.36 Aug 19th Cooler Classic 30
184 Mousetrap Win 11-9 907.28 Sep 8th Northwest Plains Mixed Sectional Championship 2018
- TMI Loss 6-11 298.32 Sep 8th Northwest Plains Mixed Sectional Championship 2018
45 Northern Comfort** Loss 1-13 835.86 Ignored Sep 8th Northwest Plains Mixed Sectional Championship 2018
228 Mixed Duluth Win 13-2 928.27 Sep 9th Northwest Plains Mixed Sectional Championship 2018
166 Spirit Fowl Loss 9-13 369.11 Sep 9th Northwest Plains 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)