#66 Virginia (9-14)

avg: 1771.7  •  sd: 54.56  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
135 William & Mary Win 11-5 1873.75 Jan 27th Winta Binta Vinta Fest 2018
145 Liberty Win 11-3 1814.02 Jan 27th Winta Binta Vinta Fest 2018
150 Virginia Commonwealth Win 10-3 1786.24 Jan 27th Winta Binta Vinta Fest 2018
49 Duke Loss 6-9 1532.91 Jan 27th Winta Binta Vinta Fest 2018
80 James Madison Win 11-9 1896.27 Jan 28th Winta Binta Vinta Fest 2018
88 Georgetown Win 10-4 2178.62 Jan 28th Winta Binta Vinta Fest 2018
46 North Carolina-Wilmington Loss 6-14 1378.21 Jan 28th Winta Binta Vinta Fest 2018
25 Notre Dame Win 10-8 2402.37 Feb 3rd Queen City Tune Up 2018 College Women
48 Georgia Loss 9-10 1830.58 Feb 3rd Queen City Tune Up 2018 College Women
93 Cornell Loss 7-8 1415.61 Feb 3rd Queen City Tune Up 2018 College Women
1 Dartmouth Loss 6-13 2297.25 Feb 3rd Queen City Tune Up 2018 College Women
7 Tufts** Loss 2-15 1908.79 Ignored Feb 24th Commonwealth Cup 2018
48 Georgia Loss 9-11 1706.37 Feb 24th Commonwealth Cup 2018
46 North Carolina-Wilmington Loss 10-14 1579.51 Feb 24th Commonwealth Cup 2018
99 Princeton Win 13-5 2120.12 Feb 25th Commonwealth Cup 2018
48 Georgia Loss 7-9 1676.24 Feb 25th Commonwealth Cup 2018
15 North Carolina State Loss 8-15 1788.27 Mar 16th Atlantic Coast Showcase ACS NCSU vs Virginia
42 Wisconsin Loss 8-10 1741.03 Mar 24th Womens Centex 2018
7 Tufts** Loss 2-13 1908.79 Ignored Mar 24th Womens Centex 2018
109 Texas Christian Win 14-12 1660.5 Mar 24th Womens Centex 2018
44 Colorado State Loss 5-10 1407.7 Mar 24th Womens Centex 2018
78 Boston University Loss 10-11 1549.47 Mar 25th Womens Centex 2018
96 St Olaf Win 14-11 1839.4 Mar 25th Womens Centex 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)