#341 Virginia-B (10-7)

avg: 517.17  •  sd: 64.77  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
401 George Washington-B Win 10-5 600.78 Mar 29th Fishbowl 2025
379 James Madison-B Win 10-3 846.71 Mar 29th Fishbowl 2025
395 Maryland-B Win 11-9 370.81 Mar 29th Fishbowl 2025
405 William & Mary-B Win 13-5 570.4 Mar 29th Fishbowl 2025
379 James Madison-B Win 10-3 846.71 Mar 30th Fishbowl 2025
226 West Virginia Loss 5-13 363.48 Mar 30th Fishbowl 2025
226 West Virginia Loss 9-12 618.12 Mar 30th Fishbowl 2025
330 South Carolina-B Loss 8-9 450.32 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
405 William & Mary-B Win 12-4 570.4 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
379 James Madison-B Win 11-8 612.32 Apr 13th Southern Atlantic Coast Dev Mens Conferences 2025
330 South Carolina-B Win 10-7 964.99 Apr 13th Southern Atlantic Coast Dev Mens Conferences 2025
337 Delaware-B Loss 7-11 77.68 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
203 North Carolina State-B Loss 9-11 806.53 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
330 South Carolina-B Loss 5-11 -24.68 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
264 Virginia Tech-B Loss 4-13 221.24 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
395 Maryland-B Win 11-4 721.6 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
395 Maryland-B Win 9-7 400.94 Apr 27th Atlantic Coast Dev College Mens 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)