#216 Washington University-B (4-13)

avg: 264.3  •  sd: 83.05  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
132 Iowa Loss 2-12 226.85 Mar 1st Midwest Throwdown 2025
142 Saint Louis Loss 1-13 138.41 Mar 1st Midwest Throwdown 2025
147 Wisconsin-La Crosse Loss 2-11 124.89 Mar 1st Midwest Throwdown 2025
253 Northwestern-B Win 7-6 35.42 Mar 2nd Midwest Throwdown 2025
210 Vanderbilt Loss 8-9 156.56 Mar 2nd Midwest Throwdown 2025
246 Wisconsin-B Win 8-6 328.45 Mar 2nd Midwest Throwdown 2025
198 Indiana Loss 4-6 90.47 Mar 29th Corny Classic College 2025
121 Loyola-Chicago** Loss 3-13 329.71 Ignored Mar 29th Corny Classic College 2025
223 North Park Win 6-5 338.92 Mar 29th Corny Classic College 2025
214 Dayton Loss 7-8 144.87 Mar 30th Corny Classic College 2025
244 Notre Dame-B Win 4-3 161.06 Mar 30th Corny Classic College 2025
97 Arkansas** Loss 2-15 493.15 Ignored Apr 12th Ozarks D I Womens Conferences 2025
28 Missouri** Loss 0-15 1134.08 Ignored Apr 12th Ozarks D I Womens Conferences 2025
111 Kansas** Loss 6-14 401.06 Ignored Apr 13th Ozarks D I Womens Conferences 2025
142 Saint Louis Loss 9-10 613.41 Apr 13th Ozarks D I Womens Conferences 2025
27 Texas** Loss 2-15 1170.67 Ignored Apr 26th South Central D I College Womens Regionals 2025
97 Arkansas Loss 5-11 493.15 Apr 27th South Central 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)