#103 Clemson (8-13)

avg: 1199.73  •  sd: 82.9  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
62 Duke Loss 4-9 884.05 Jan 20th Carolina Kickoff Womens 2024
6 North Carolina** Loss 3-12 1899.4 Ignored Jan 20th Carolina Kickoff Womens 2024
151 North Carolina-B Loss 5-8 414.35 Jan 20th Carolina Kickoff Womens 2024
56 North Carolina State Loss 3-14 943.77 Jan 21st Carolina Kickoff Womens 2024
61 Florida Loss 5-12 893.44 Mar 16th Tally Classic XVIII
23 Notre Dame** Loss 3-12 1331.53 Ignored Mar 16th Tally Classic XVIII
170 Jacksonville State Win 10-5 1335.67 Mar 16th Tally Classic XVIII
234 Florida Tech** Win 15-1 661.95 Ignored Mar 17th Tally Classic XVIII
170 Jacksonville State Win 15-2 1361.77 Mar 17th Tally Classic XVIII
104 Appalachian State Loss 8-9 1071.7 Apr 13th Carolina D I Womens Conferences 2024
188 Wake Forest** Win 15-0 1166.45 Ignored Apr 13th Carolina D I Womens Conferences 2024
56 North Carolina State Loss 8-9 1418.77 Apr 13th Carolina D I Womens Conferences 2024
62 Duke Loss 5-10 910.16 Apr 13th Carolina D I Womens Conferences 2024
120 Charleston Win 9-8 1207.15 Apr 14th Carolina D I Womens Conferences 2024
225 North Carolina-Wilmington** Win 15-5 817.16 Ignored Apr 14th Carolina D I Womens Conferences 2024
56 North Carolina State Loss 6-13 943.77 Apr 14th Carolina D I Womens Conferences 2024
38 American Loss 8-11 1358.07 May 4th Atlantic Coast D I College Womens Regionals 2024
104 Appalachian State Win 14-9 1670.57 May 4th Atlantic Coast D I College Womens Regionals 2024
50 Georgetown Loss 5-14 1001.27 May 4th Atlantic Coast D I College Womens Regionals 2024
89 Virginia Tech Win 14-11 1620.25 May 4th 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
**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)