#71 William & Mary (16-4)

avg: 1326.62  •  sd: 94.61  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
59 Duke Loss 5-7 1117.82 Jan 26th Winta Binta Vinta Fest 2019
182 George Mason** Win 12-5 1228.31 Ignored Jan 26th Winta Binta Vinta Fest 2019
105 Liberty Loss 5-7 759.04 Jan 26th Winta Binta Vinta Fest 2019
45 Virginia Loss 2-9 945.7 Jan 26th Winta Binta Vinta Fest 2019
271 Virginia-B** Win 13-1 416.54 Ignored Jan 27th Winta Binta Vinta Fest 2019
82 Georgetown Win 9-7 1545.8 Jan 27th Winta Binta Vinta Fest 2019
105 Liberty Win 10-6 1583.35 Jan 27th Winta Binta Vinta Fest 2019
223 Elon Win 13-6 983.22 Feb 9th Ultimate Galentines Celebration 2019
203 Wake Forest** Win 13-2 1108.51 Ignored Feb 9th Ultimate Galentines Celebration 2019
259 East Carolina** Win 13-0 673.16 Ignored Feb 10th Ultimate Galentines Celebration 2019
274 Wooster** Win 13-0 385.82 Ignored Feb 10th Ultimate Galentines Celebration 2019
153 Virginia Tech Win 13-3 1460.33 Feb 10th Ultimate Galentines Celebration 2019
213 Mary Washington** Win 15-2 1076.29 Ignored Feb 23rd Virginia Showcase Series 22319
166 Richmond Win 15-4 1370.47 Mar 23rd Virginia Showcase Series 32319
259 East Carolina** Win 13-5 673.16 Ignored Mar 30th Atlantic Coast Open 2019
182 George Mason** Win 12-1 1228.31 Ignored Mar 30th Atlantic Coast Open 2019
197 Christopher Newport** Win 13-3 1165.13 Ignored Mar 30th Atlantic Coast Open 2019
147 George Washington Win 13-4 1481.09 Mar 30th Atlantic Coast Open 2019
61 James Madison Loss 12-13 1310.16 Mar 31st Atlantic Coast Open 2019
130 Connecticut Win 12-5 1592.45 Mar 31st Atlantic Coast Open 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)