#60 South Carolina (12-12)

avg: 1384.06  •  sd: 66.18  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
2 Carleton College** Loss 1-13 1963.52 Ignored Feb 15th Queen City Tune Up 2025
65 Florida Win 9-8 1443.59 Feb 15th Queen City Tune Up 2025
26 Northeastern Loss 6-13 1199.41 Feb 15th Queen City Tune Up 2025
81 Case Western Reserve Win 7-1 1800.8 Feb 16th Queen City Tune Up 2025
31 Pittsburgh Loss 3-10 1091.14 Feb 16th Queen City Tune Up 2025
64 Connecticut Win 10-1 1919.26 Mar 29th East Coast Invite 2025
34 Cornell Loss 7-11 1173.86 Mar 29th East Coast Invite 2025
109 Temple Win 14-5 1621.02 Mar 29th East Coast Invite 2025
115 West Chester Win 12-5 1550.96 Mar 29th East Coast Invite 2025
25 Georgetown Loss 8-14 1263.76 Mar 30th East Coast Invite 2025
53 Maryland Loss 7-10 1066.65 Mar 30th East Coast Invite 2025
39 Wesleyan Loss 4-8 1022.03 Mar 30th East Coast Invite 2025
43 Duke Win 13-8 2060.56 Apr 12th Carolina D I Womens Conferences 2025
167 East Carolina** Win 13-1 1226.11 Ignored Apr 12th Carolina D I Womens Conferences 2025
69 North Carolina State Win 13-10 1621.39 Apr 12th Carolina D I Womens Conferences 2025
188 Wake Forest** Win 13-0 1095.1 Ignored Apr 12th Carolina D I Womens Conferences 2025
84 Clemson Win 13-9 1581.94 Apr 13th Carolina D I Womens Conferences 2025
84 Clemson Loss 10-12 925.26 Apr 13th Carolina D I Womens Conferences 2025
9 North Carolina** Loss 5-15 1518.27 Ignored Apr 13th Carolina D I Womens Conferences 2025
47 American Loss 8-11 1175.96 Apr 26th Atlantic Coast D I College Womens Regionals 2025
25 Georgetown Loss 5-13 1199.8 Apr 26th Atlantic Coast D I College Womens Regionals 2025
57 James Madison Loss 10-15 951.24 Apr 26th Atlantic Coast D I College Womens Regionals 2025
128 North Carolina-Wilmington Win 15-2 1447.3 Apr 26th Atlantic Coast D I College Womens Regionals 2025
103 Virginia Tech Win 15-4 1648.67 Apr 27th Atlantic Coast D I College Womens Regionals 2025
**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)