#248 Mixed on the Rock (0-14)

avg: -206.09  •  sd: 129.77  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
234 rubber duck ultimate. Loss 7-13 -301.39 Jul 21st The Royal Experience 18
227 Mixfits Loss 6-13 -266.56 Jul 21st The Royal Experience 18
135 Blitzkrieg** Loss 1-13 357.73 Ignored Jul 21st The Royal Experience 18
191 Coalition Ultimate** Loss 5-13 19.68 Ignored Jul 21st The Royal Experience 18
234 rubber duck ultimate. Loss 11-15 -125.02 Jul 22nd The Royal Experience 18
215 Free Ride** Loss 5-15 -107.99 Ignored Jul 22nd The Royal Experience 18
94 Tex Mix** Loss 0-13 553.03 Ignored Aug 11th Hootie on the Hill 2018
215 Free Ride** Loss 5-13 -107.99 Ignored Aug 11th Hootie on the Hill 2018
135 Blitzkrieg** Loss 1-13 357.73 Ignored Aug 11th Hootie on the Hill 2018
130 Impact** Loss 3-13 368.83 Ignored Aug 11th Hootie on the Hill 2018
234 rubber duck ultimate. Loss 10-15 -197.46 Aug 12th Hootie on the Hill 2018
240 Memphis Hustle & Flow Loss 14-15 19.49 Aug 12th Hootie on the Hill 2018
128 Boomtown** Loss 2-15 377.74 Ignored Sep 8th Ozarks Mixed Sectional Championship 2018
234 rubber duck ultimate. Loss 7-15 -343.86 Sep 8th Ozarks 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)