#128 Boomtown (16-10)

avg: 977.74  •  sd: 64.65  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
116 Moontower Win 12-5 1636.05 Jun 30th Texas Two Finger 2018
221 Chili Poppers Win 13-4 996.65 Jun 30th Texas Two Finger 2018
49 Cosa Nostra Loss 5-12 771.79 Jul 1st Texas Two Finger 2018
94 Tex Mix Loss 10-12 914.91 Jul 1st Texas Two Finger 2018
97 tHUMP Win 10-9 1264.88 Jul 1st Texas Two Finger 2018
215 Free Ride Win 12-10 730.14 Jul 21st The Royal Experience 18
159 Hellbenders Win 13-9 1229.31 Jul 21st The Royal Experience 18
135 Blitzkrieg Loss 10-12 719.61 Jul 21st The Royal Experience 18
94 Tex Mix Loss 7-12 632.52 Jul 21st The Royal Experience 18
227 Mixfits** Win 15-4 933.44 Ignored Jul 22nd The Royal Experience 18
159 Hellbenders Win 15-8 1375.55 Jul 22nd The Royal Experience 18
159 Hellbenders Win 10-8 1073.41 Aug 11th Hootie on the Hill 2018
234 rubber duck ultimate.** Win 13-5 856.14 Ignored Aug 11th Hootie on the Hill 2018
240 Memphis Hustle & Flow** Win 11-2 744.49 Ignored Aug 11th Hootie on the Hill 2018
115 STAX Win 8-6 1337.92 Aug 11th Hootie on the Hill 2018
215 Free Ride Win 15-4 1092.01 Aug 12th Hootie on the Hill 2018
130 Impact Win 15-13 1183.01 Aug 12th Hootie on the Hill 2018
94 Tex Mix Win 13-12 1278.03 Aug 12th Hootie on the Hill 2018
248 Mixed on the Rock** Win 15-2 393.91 Ignored Sep 8th Ozarks Mixed Sectional Championship 2018
234 rubber duck ultimate. Win 15-8 820.95 Sep 8th Ozarks Mixed Sectional Championship 2018
49 Cosa Nostra Loss 9-13 953.22 Sep 22nd South Central Mixed Regional Championship 2018
21 Public Enemy** Loss 3-13 1075.65 Ignored Sep 22nd South Central Mixed Regional Championship 2018
89 Sweet Action Loss 11-13 940.19 Sep 22nd South Central Mixed Regional Championship 2018
97 tHUMP Loss 9-13 721.32 Sep 23rd South Central Mixed Regional Championship 2018
94 Tex Mix Loss 9-15 637.55 Sep 23rd South Central Mixed Regional Championship 2018
118 Risky Business Loss 11-13 802.56 Sep 23rd South Central Mixed Regional 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)