#228 The Umbrella (5-15)

avg: 470.04  •  sd: 71.91  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
35 'Shine** Loss 3-13 925.9 Ignored Jul 6th Huntsville Huckfest 2019
222 Monster Win 13-10 869.32 Jul 6th Huntsville Huckfest 2019
158 OutKast Loss 7-13 281.89 Jul 6th Huntsville Huckfest 2019
80 Trash Pandas Loss 8-13 701.93 Jul 6th Huntsville Huckfest 2019
283 Craw Daddies Win 13-7 658.9 Jul 7th Huntsville Huckfest 2019
170 Magic City Mayhem Loss 6-13 163.15 Jul 7th Huntsville Huckfest 2019
266 Orbit Win 11-10 385.34 Jul 7th Huntsville Huckfest 2019
94 Mutiny Loss 7-13 571.27 Jul 20th 2019 Club Terminus
20 Weird** Loss 5-13 1081.45 Ignored Jul 20th 2019 Club Terminus
130 m'kay Ultimate Loss 6-13 385.41 Jul 20th 2019 Club Terminus
78 Memphis STAX** Loss 5-13 607.34 Ignored Jul 20th 2019 Club Terminus
94 Mutiny** Loss 5-13 528.81 Ignored Jul 21st 2019 Club Terminus
170 Magic City Mayhem Win 12-9 1108.51 Jul 21st 2019 Club Terminus
107 Shakedown** Loss 4-11 492.86 Ignored Jul 21st 2019 Club Terminus
43 Murmur** Loss 1-13 861.98 Ignored Sep 7th East Coast Mixed Club Sectional Championship 2019
189 Hairy Otter Loss 8-13 169.81 Sep 7th East Coast Mixed Club Sectional Championship 2019
130 m'kay Ultimate Loss 4-13 385.41 Sep 7th East Coast Mixed Club Sectional Championship 2019
80 Trash Pandas** Loss 5-13 598.09 Ignored Sep 7th East Coast Mixed Club Sectional Championship 2019
189 Hairy Otter Loss 6-13 65.97 Sep 8th East Coast Mixed Club Sectional Championship 2019
266 Orbit Win 13-9 678.91 Sep 8th East Coast 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)