#309 Washington University-B (5-17)

avg: 640.96  •  sd: 56.18  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
159 Kansas Loss 6-13 632.13 Feb 22nd Dust Bowl 2025
322 Kansas State Win 12-7 1121.67 Feb 22nd Dust Bowl 2025
176 Northern Iowa Loss 7-13 613.3 Feb 22nd Dust Bowl 2025
245 Texas-Dallas Loss 9-10 776.38 Feb 22nd Dust Bowl 2025
272 Oklahoma Loss 7-8 680.29 Feb 23rd Dust Bowl 2025
256 Illinois-B Loss 7-12 340.31 Mar 1st Midwest Throwdown 2025
73 Iowa State** Loss 2-13 1001.89 Ignored Mar 1st Midwest Throwdown 2025
150 Macalester Loss 6-13 677.34 Mar 1st Midwest Throwdown 2025
238 Illinois State Loss 8-12 483.37 Mar 2nd Midwest Throwdown 2025
195 Minnesota-B Loss 4-13 483.86 Mar 2nd Midwest Throwdown 2025
72 St Olaf** Loss 2-13 1006.39 Ignored Mar 2nd Midwest Throwdown 2025
222 Wisconsin-B Loss 6-9 571.4 Mar 2nd Midwest Throwdown 2025
253 St Thomas Loss 10-11 737.99 Mar 29th Old Capitol Open 2025
402 Wisconsin-Milwaukee-B** Win 12-5 617.81 Ignored Mar 29th Old Capitol Open 2025
301 Luther Loss 6-10 184.46 Mar 29th Old Capitol Open 2025
418 Iowa State-B** Win 11-1 103.12 Ignored Mar 30th Old Capitol Open 2025
317 Minnesota-C Win 12-9 961.53 Mar 30th Old Capitol Open 2025
301 Luther Loss 6-7 555.62 Mar 30th Old Capitol Open 2025
225 Arkansas Loss 9-10 851.3 Apr 12th Ozarks D I Mens Conferences 2025
201 Saint Louis Loss 13-15 845.86 Apr 12th Ozarks D I Mens Conferences 2025
322 Kansas State Win 10-9 726.16 Apr 13th Ozarks D I Mens Conferences 2025
272 Oklahoma Loss 7-13 247.76 Apr 13th Ozarks D I Mens 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)