#264 Virginia Tech-B (8-10)

avg: 806.34  •  sd: 63.36  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
63 Duke Loss 7-15 1032.68 Mar 22nd Atlantic Coast Open 2025
140 George Mason Loss 7-11 821.23 Mar 22nd Atlantic Coast Open 2025
111 Liberty Loss 6-12 809.66 Mar 22nd Atlantic Coast Open 2025
165 Massachusetts -B Loss 3-15 606.06 Mar 22nd Atlantic Coast Open 2025
232 George Washington Loss 7-15 324.71 Mar 23rd Atlantic Coast Open 2025
401 George Washington-B** Win 15-5 613.1 Ignored Mar 23rd Atlantic Coast Open 2025
383 James Madison-B Win 14-9 706.35 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
205 North Carolina State-B Loss 5-13 440.51 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
198 North Carolina-B Loss 10-13 733.5 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
198 North Carolina-B Loss 12-13 936.64 Apr 13th Southern Atlantic Coast Dev Mens Conferences 2025
334 South Carolina-B Win 11-9 809.65 Apr 13th Southern Atlantic Coast Dev Mens Conferences 2025
205 North Carolina State-B Win 10-9 1165.51 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
334 South Carolina-B Loss 10-11 435.45 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
396 Maryland-B Win 9-7 387 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
343 Virginia-B Win 13-4 1102.85 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
339 Delaware-B Win 13-6 1131.99 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
205 North Carolina State-B Loss 11-12 915.51 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
334 South Carolina-B Win 13-6 1160.45 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)