#238 Virginia Commonwealth (2-15)

avg: 905.77  •  sd: 57.5  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
116 Boston University Loss 4-11 763.62 Jan 25th Mid Atlantic Warm Up 2025
61 Michigan State Loss 7-13 1078.54 Jan 25th Mid Atlantic Warm Up 2025
77 Richmond** Loss 4-13 964.2 Ignored Jan 25th Mid Atlantic Warm Up 2025
115 RIT Loss 3-10 767 Jan 25th Mid Atlantic Warm Up 2025
181 American Loss 6-12 559.65 Jan 26th Mid Atlantic Warm Up 2025
140 George Mason Loss 6-9 869.56 Feb 22nd Monument Melee 2025
155 Johns Hopkins Loss 6-11 691.82 Feb 22nd Monument Melee 2025
300 Maryland-Baltimore County Loss 4-5 560.62 Feb 22nd Monument Melee 2025
173 East Carolina Loss 8-9 1041.37 Feb 23rd Monument Melee 2025
232 George Washington Loss 8-10 662.04 Feb 23rd Monument Melee 2025
332 Villanova Win 9-8 694.58 Feb 23rd Monument Melee 2025
58 James Madison Loss 7-9 1371.33 Apr 12th Virginia D I Mens Conferences 2025
111 Liberty Loss 7-9 1109.64 Apr 12th Virginia D I Mens Conferences 2025
29 Virginia** Loss 1-15 1261.99 Ignored Apr 12th Virginia D I Mens Conferences 2025
45 Virginia Tech Loss 6-12 1173.26 Apr 12th Virginia D I Mens Conferences 2025
140 George Mason Loss 9-15 772.64 Apr 13th Virginia D I Mens Conferences 2025
369 Radford Win 14-7 905.76 Apr 13th Virginia 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)