#356 Virginia-B (7-10)

avg: 350.83  •  sd: 85.05  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
400 Pennsylvania-B Win 13-4 650.94 Feb 24th Solar Showdown 2018
285 Maryland-B Loss 6-12 64.37 Feb 24th Solar Showdown 2018
404 George Washington-B Loss 9-10 -108.79 Feb 24th Solar Showdown 2018
238 Delaware-B Loss 6-15 194.27 Feb 25th Solar Showdown 2018
279 Penn State-B Win 11-8 1031.91 Feb 25th Solar Showdown 2018
285 Maryland-B Win 11-9 892.89 Feb 25th Solar Showdown 2018
238 Delaware-B Loss 6-13 194.27 Mar 17th Oak Creek Invite 2018
385 Princeton-B Win 13-3 804.07 Mar 17th Oak Creek Invite 2018
326 North Carolina-Wilmington-B Win 12-11 607.82 Mar 17th Oak Creek Invite 2018
256 Christopher Newport Loss 10-13 429.78 Mar 17th Oak Creek Invite 2018
278 James Madison-B Loss 9-15 157.77 Mar 18th Oak Creek Invite 2018
421 American-B Win 14-2 419.11 Mar 24th JMU Beenanza 2018
256 Christopher Newport Loss 7-13 200.39 Mar 24th JMU Beenanza 2018
- Maryland-Baltimore County-B Win 11-6 596.79 Mar 24th JMU Beenanza 2018
365 William & Mary-B Loss 6-13 -275.99 Mar 24th JMU Beenanza 2018
280 South Carolina-B Loss 6-13 65.42 Mar 25th JMU Beenanza 2018
365 William & Mary-B Loss 14-15 199.01 Mar 25th JMU Beenanza 2018
**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)