#50 Taco Truck (11-8)

avg: 1053.99  •  sd: 63.5  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
57 Outbreak Win 11-7 1331.26 Jun 15th ATL Classic 2019
22 Tabby Rosa Loss 7-12 1037.18 Jun 15th ATL Classic 2019
78 cATLanta** Win 10-4 1009.48 Ignored Jun 15th ATL Classic 2019
61 Red Hot Ultimate Win 13-5 1370.23 Jun 15th ATL Classic 2019
26 Virginia Rebellion Loss 4-7 951.54 Jun 16th ATL Classic 2019
45 Queen Cake Win 12-9 1462.36 Jun 16th ATL Classic 2019
48 Brooklyn Book Club Loss 5-9 553.12 Jul 13th Scuffletown Throwdown 2019
65 Eliza Furnace Win 10-7 1115.44 Jul 13th Scuffletown Throwdown 2019
93 Suffrage** Win 11-4 749.01 Ignored Jul 13th Scuffletown Throwdown 2019
29 Warhawks Loss 3-11 800.16 Jul 13th Scuffletown Throwdown 2019
77 DC Rogue Win 8-5 888.41 Jul 13th Scuffletown Throwdown 2019
58 Agency Win 12-6 1441.04 Jul 14th Scuffletown Throwdown 2019
48 Brooklyn Book Club Loss 10-11 957.18 Jul 14th Scuffletown Throwdown 2019
29 Warhawks Loss 9-10 1275.16 Jul 14th Scuffletown Throwdown 2019
86 Honey Pot Win 12-6 831.31 Aug 10th HoDown ShowDown 23 GOAT
86 Honey Pot** Win 13-5 852 Ignored Aug 10th HoDown ShowDown 23 GOAT
57 Outbreak Win 13-10 1192.5 Aug 10th HoDown ShowDown 23 GOAT
57 Outbreak Loss 11-12 739.36 Aug 10th HoDown ShowDown 23 GOAT
7 Phoenix** Loss 4-15 1547.19 Ignored Sep 8th North Carolina Womens 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)