#188 Wake Forest (5-12)

avg: 566.45  •  sd: 93.46  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
38 American** Loss 0-13 1123.68 Ignored Feb 17th Commonwealth Cup Weekend 1 2024
190 Michigan-B Loss 3-4 428.14 Feb 17th Commonwealth Cup Weekend 1 2024
163 Catholic Loss 4-10 212.68 Feb 18th Commonwealth Cup Weekend 1 2024
204 Elon Win 8-7 532.21 Feb 18th Commonwealth Cup Weekend 1 2024
229 Virginia-B Win 9-2 759.59 Feb 18th Commonwealth Cup Weekend 1 2024
35 St Olaf** Loss 0-13 1178.48 Ignored Mar 23rd Needle in a Ho Stack 2024
162 Emory Win 10-1 1416.03 Mar 23rd Needle in a Ho Stack 2024
183 South Carolina-B Loss 3-7 6.54 Mar 24th Needle in a Ho Stack 2024
162 Emory Loss 2-10 216.03 Mar 24th Needle in a Ho Stack 2024
249 Emory-B Win 11-3 600 Ignored Mar 24th Needle in a Ho Stack 2024
50 Georgetown** Loss 1-13 1001.27 Ignored Mar 24th Needle in a Ho Stack 2024
104 Appalachian State** Loss 1-15 596.7 Ignored Apr 13th Carolina D I Womens Conferences 2024
103 Clemson** Loss 0-15 599.73 Ignored Apr 13th Carolina D I Womens Conferences 2024
62 Duke** Loss 1-13 884.05 Ignored Apr 13th Carolina D I Womens Conferences 2024
56 North Carolina State** Loss 5-14 943.77 Ignored Apr 13th Carolina D I Womens Conferences 2024
123 East Carolina Loss 2-15 473.86 Apr 14th Carolina D I Womens Conferences 2024
225 North Carolina-Wilmington Win 14-7 800.04 Apr 14th Carolina D I Womens Conferences 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)