#36 William & Mary (13-8)

avg: 1759.89  •  sd: 73.13  •  top 16/20: 0.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
51 Virginia Win 9-8 1702.69 Jan 27th Winta Binta Vinta 2024
89 Virginia Tech Win 9-2 1906.92 Jan 27th Winta Binta Vinta 2024
64 Penn State Loss 8-9 1351.98 Jan 27th Winta Binta Vinta 2024
65 James Madison Win 6-4 1828.1 Jan 28th Winta Binta Vinta 2024
24 Ohio State Loss 5-10 1319.98 Jan 28th Winta Binta Vinta 2024
64 Penn State Win 9-4 2076.98 Jan 28th Winta Binta Vinta 2024
41 South Carolina Loss 4-13 1098.94 Feb 10th Queen City Tune Up 2024
2 Vermont** Loss 1-15 2077.17 Ignored Feb 10th Queen City Tune Up 2024
51 Virginia Loss 5-12 977.69 Feb 10th Queen City Tune Up 2024
26 Wisconsin Loss 8-10 1614.51 Feb 10th Queen City Tune Up 2024
34 Washington University Loss 5-9 1255.1 Feb 11th Queen City Tune Up 2024
65 James Madison Win 9-7 1741.83 Apr 20th Virginia D I Womens Conferences 2024
51 Virginia Win 10-5 2151.59 Apr 20th Virginia D I Womens Conferences 2024
89 Virginia Tech Win 13-6 1906.92 Apr 20th Virginia D I Womens Conferences 2024
138 Liberty** Win 13-5 1546.76 Ignored Apr 20th Virginia D I Womens Conferences 2024
120 Charleston** Win 15-5 1682.15 Ignored May 4th Atlantic Coast D I College Womens Regionals 2024
62 Duke Win 15-10 1937.66 May 4th Atlantic Coast D I College Womens Regionals 2024
51 Virginia Win 15-12 1878.18 May 4th Atlantic Coast D I College Womens Regionals 2024
41 South Carolina Win 12-11 1823.94 May 5th Atlantic Coast D I College Womens Regionals 2024
6 North Carolina** Loss 2-15 1899.4 Ignored May 5th Atlantic Coast D I College Womens Regionals 2024
56 North Carolina State Win 15-5 2143.77 May 5th Atlantic Coast D I College Womens Regionals 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)