#284 Mixed on the Rock (2-11)

avg: 136.35  •  sd: 121.64  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
243 rubber duck ultimate. Loss 7-11 -4.25 Jun 15th Texas Two Finger 2019
70 Memphis STAX** Loss 1-11 701.52 Ignored Jun 15th Texas Two Finger 2019
45 Waterloo** Loss 0-11 893.19 Ignored Jun 15th Texas Two Finger 2019
169 Wildstyle** Loss 3-11 211.29 Ignored Jun 15th Texas Two Finger 2019
105 Auburn HeyDay** Loss 2-13 558.12 Ignored Jul 6th Huntsville Huckfest 2019
283 Craw Daddies Win 13-10 485.15 Jul 6th Huntsville Huckfest 2019
47 Huntsville Outlaws** Loss 3-13 873.42 Ignored Jul 6th Huntsville Huckfest 2019
167 Possum Loss 6-13 236.1 Jul 6th Huntsville Huckfest 2019
268 Orbit Loss 8-13 -198.12 Jul 7th Huntsville Huckfest 2019
283 Craw Daddies Win 13-11 385.85 Jul 7th Huntsville Huckfest 2019
225 Monster Loss 5-15 -17.1 Jul 7th Huntsville Huckfest 2019
49 Boomtown** Loss 2-15 863.97 Ignored Sep 14th Ozarks Mixed Club Sectional Championship 2019
243 rubber duck ultimate. Loss 11-15 81.48 Sep 14th Ozarks 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)