#135 William & Mary (8-9)

avg: 1273.75  •  sd: 67.58  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
49 Duke** Loss 1-15 1351.48 Ignored Jan 27th Winta Binta Vinta Fest 2018
145 Liberty Loss 8-9 1089.02 Jan 27th Winta Binta Vinta Fest 2018
66 Virginia Loss 5-11 1171.7 Jan 27th Winta Binta Vinta Fest 2018
150 Virginia Commonwealth Win 8-6 1486.73 Jan 27th Winta Binta Vinta Fest 2018
245 George Mason University** Win 15-3 1094.17 Ignored Jan 28th Winta Binta Vinta Fest 2018
145 Liberty Win 12-5 1814.02 Jan 28th Winta Binta Vinta Fest 2018
150 Virginia Commonwealth Loss 9-12 840.88 Jan 28th Winta Binta Vinta Fest 2018
59 South Carolina Loss 5-14 1227.83 Feb 24th Commonwealth Cup 2018
62 Central Florida Loss 7-10 1409.21 Feb 24th Commonwealth Cup 2018
148 Virginia Tech Loss 7-11 722.69 Feb 24th Commonwealth Cup 2018
181 Pittsburgh-B Win 12-6 1573.72 Feb 25th Commonwealth Cup 2018
171 Catholic Win 11-10 1171.87 Feb 25th Commonwealth Cup 2018
160 Richmond Win 10-7 1519.23 Feb 25th Commonwealth Cup 2018
83 Brandeis Loss 6-11 1072.93 Mar 17th Capital City Shootout 2018
188 Mary Washington Win 12-3 1542.86 Mar 17th Capital City Shootout 2018
255 Christopher Newport** Win 13-4 937.52 Ignored Mar 17th Capital City Shootout 2018
83 Brandeis Loss 7-10 1229.96 Mar 17th Capital City Shootout 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)