#240 Duloofda (5-13)

avg: 419.57  •  sd: 48.49  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
287 Ope! Win 13-9 442.13 Jul 20th Minnesota Ultimate Disc Invitational
176 Mousetrap Win 11-9 981.63 Jul 21st Minnesota Ultimate Disc Invitational
76 Mojo Jojo Loss 7-12 703.42 Jul 21st Minnesota Ultimate Disc Invitational
152 Melt Loss 7-10 471.66 Jul 21st Minnesota Ultimate Disc Invitational
208 Pushovers-B Loss 8-11 236.56 Jul 21st Minnesota Ultimate Disc Invitational
295 Fox Valley Forge Win 13-8 151.7 Aug 17th Cooler Classic 31
211 Mastodon Loss 8-13 92.5 Aug 17th Cooler Classic 31
107 Shakedown Loss 8-13 596.7 Aug 17th Cooler Classic 31
227 Midwestern Mediocrity Win 14-13 597.03 Aug 17th Cooler Classic 31
176 Mousetrap Loss 6-8 431.93 Aug 18th Cooler Classic 31
217 Stackcats Loss 7-8 443.52 Aug 18th Cooler Classic 31
208 Pushovers-B Loss 8-9 477.17 Aug 18th Cooler Classic 31
65 Northern Comfort** Loss 3-13 663.1 Ignored Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
295 Fox Valley Forge Win 13-6 255.54 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
112 Pandamonium** Loss 3-13 467.1 Ignored Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
208 Pushovers-B Loss 12-13 477.17 Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
225 Boomtown Pandas Loss 11-13 290.67 Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
241 Madison United Mixed Ultimate Loss 10-11 293.94 Sep 8th Northwest Plains 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)