#120 Charleston (11-12)

avg: 1082.15  •  sd: 79.43  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
37 Carleton College-Eclipse** Loss 5-13 1149.41 Ignored Mar 16th Southerns 2024
241 Florida-B** Win 13-1 435.05 Ignored Mar 16th Southerns 2024
225 North Carolina-Wilmington** Win 13-1 817.16 Ignored Mar 16th Southerns 2024
226 Georgia Southern** Win 13-2 798.86 Ignored Mar 16th Southerns 2024
37 Carleton College-Eclipse** Loss 6-15 1149.41 Ignored Mar 17th Southerns 2024
194 Georgia College Win 14-12 740.16 Mar 17th Southerns 2024
127 Wisconsin-Eau Claire Loss 7-14 458.18 Mar 17th Southerns 2024
158 Case Western Reserve Loss 6-7 709.5 Mar 23rd Needle in a Ho Stack 2024
249 Emory-B** Win 13-0 600 Ignored Mar 23rd Needle in a Ho Stack 2024
104 Appalachian State Loss 5-12 596.7 Mar 24th Needle in a Ho Stack 2024
132 Cedarville Win 10-5 1576.43 Mar 24th Needle in a Ho Stack 2024
123 East Carolina Win 8-6 1374.35 Mar 24th Needle in a Ho Stack 2024
41 South Carolina** Loss 2-13 1098.94 Ignored Apr 13th Carolina D I Womens Conferences 2024
225 North Carolina-Wilmington** Win 13-3 817.16 Ignored Apr 13th Carolina D I Womens Conferences 2024
6 North Carolina** Loss 1-15 1899.4 Ignored Apr 13th Carolina D I Womens Conferences 2024
123 East Carolina Win 6-4 1439.46 Apr 13th Carolina D I Womens Conferences 2024
103 Clemson Loss 8-9 1074.73 Apr 14th Carolina D I Womens Conferences 2024
123 East Carolina Win 13-4 1673.86 Apr 14th Carolina D I Womens Conferences 2024
51 Virginia Loss 2-15 977.69 May 4th Atlantic Coast D I College Womens Regionals 2024
36 William & Mary** Loss 5-15 1159.89 Ignored May 4th Atlantic Coast D I College Womens Regionals 2024
62 Duke Loss 10-12 1245.93 May 4th Atlantic Coast D I College Womens Regionals 2024
125 Johns Hopkins Win 11-10 1187.17 May 4th Atlantic Coast D I College Womens Regionals 2024
104 Appalachian State Loss 5-7 868.56 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)