#208 Virginia Commonwealth (8-10)

avg: 785.38  •  sd: 76.02  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
70 Case Western Reserve Loss 5-12 766.71 Jan 27th Mid Atlantic Warm Up
96 Connecticut Loss 7-10 859.73 Jan 27th Mid Atlantic Warm Up
111 SUNY-Binghamton Loss 8-12 750.57 Jan 27th Mid Atlantic Warm Up
96 Connecticut Loss 2-15 649.4 Jan 28th Mid Atlantic Warm Up
156 Johns Hopkins Win 11-10 1144.03 Jan 28th Mid Atlantic Warm Up
123 Pennsylvania Loss 0-15 547.48 Jan 28th Mid Atlantic Warm Up
224 American Win 11-7 1198.64 Feb 24th Monument Melee
280 Drexel Loss 6-8 173.13 Feb 24th Monument Melee
175 Maryland-Baltimore County Win 11-7 1394.89 Feb 24th Monument Melee
224 American Win 14-11 1045.09 Feb 25th Monument Melee
189 East Carolina Win 10-7 1251.7 Feb 25th Monument Melee
166 Villanova Loss 7-12 438.03 Feb 25th Monument Melee
156 Johns Hopkins Loss 7-9 739.7 Mar 30th Atlantic Coast Open 2024
144 Pittsburgh-B Loss 10-15 608.42 Mar 30th Atlantic Coast Open 2024
298 Mary Washington Win 15-10 817.39 Mar 30th Atlantic Coast Open 2024
256 Virginia Tech-B Win 11-10 701.62 Mar 30th Atlantic Coast Open 2024
252 Dickinson Win 12-9 955.79 Mar 31st Atlantic Coast Open 2024
206 George Washington Loss 8-14 267.27 Mar 31st Atlantic Coast Open 2024
**Blowout Eligible

FAQ

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
  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
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)