#149 Davidson (11-8)

avg: 704.52  •  sd: 52.82  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
151 North Carolina-B Win 7-4 1185.38 Feb 15th 2025 Commonwealth Cup Weekend 1
187 Wake Forest Win 7-4 990.97 Feb 15th 2025 Commonwealth Cup Weekend 1
211 Georgetown-B Win 9-3 874.31 Feb 15th 2025 Commonwealth Cup Weekend 1
212 Georgia-B Win 6-1 872.62 Feb 15th 2025 Commonwealth Cup Weekend 1
115 Cedarville Loss 3-4 822.08 Feb 16th 2025 Commonwealth Cup Weekend 1
49 Kenyon** Loss 1-8 898.8 Ignored Feb 16th 2025 Commonwealth Cup Weekend 1
159 Charleston Win 8-5 1118.6 Mar 29th Needle in a Ho Stack 2025
125 Georgia College Loss 6-9 437.58 Mar 29th Needle in a Ho Stack 2025
228 Elon Win 7-2 765.12 Mar 29th Needle in a Ho Stack 2025
89 Williams Loss 6-10 622.58 Mar 29th Needle in a Ho Stack 2025
83 Clemson Loss 5-10 589.77 Mar 30th Needle in a Ho Stack 2025
226 South Carolina-B Win 11-5 787.46 Mar 30th Needle in a Ho Stack 2025
126 North Carolina-Wilmington Loss 5-7 519.14 Mar 30th Needle in a Ho Stack 2025
141 Catholic Win 8-7 859.02 Apr 12th Atlantic Coast D III Womens Conferences 2025
228 Elon Win 8-7 290.12 Apr 12th Atlantic Coast D III Womens Conferences 2025
84 Richmond Loss 4-11 548.86 Apr 12th Atlantic Coast D III Womens Conferences 2025
141 Catholic Win 6-5 859.02 Apr 13th Atlantic Coast D III Womens Conferences 2025
210 Mary Washington Win 7-5 606.27 Apr 13th Atlantic Coast D III Womens Conferences 2025
84 Richmond Loss 2-12 548.86 Apr 13th Atlantic Coast D III Womens Conferences 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)