#217 Virginia-B (2-10)

avg: 79.69  •  sd: 152.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
34 James Madison** Loss 0-13 1032.11 Ignored Jan 25th Winta Binta Vinta Fest 2020
107 Georgetown** Loss 1-13 434.49 Ignored Jan 25th Winta Binta Vinta Fest 2020
168 Virginia Commonwealth Loss 2-8 -54.45 Jan 25th Winta Binta Vinta Fest 2020
107 Georgetown** Loss 0-15 434.49 Ignored Jan 26th Winta Binta Vinta Fest 2020
12 Virginia** Loss 1-15 1435.27 Ignored Jan 26th Winta Binta Vinta Fest 2020
166 West Virginia Loss 2-10 -44.67 Jan 26th Winta Binta Vinta Fest 2020
132 George Mason** Loss 5-13 240.98 Ignored Feb 15th Commonwealth Cup 2020 Weekend 1
164 Pittsburgh-B Loss 2-12 -37.75 Feb 15th Commonwealth Cup 2020 Weekend 1
123 Swarthmore Loss 8-11 550.46 Feb 15th Commonwealth Cup 2020 Weekend 1
236 Franciscan Win 9-7 32.56 Feb 16th Commonwealth Cup 2020 Weekend 1
219 Michigan-B Loss 8-9 -61.25 Feb 16th Commonwealth Cup 2020 Weekend 1
248 Ohio State-B** Win 12-4 -52.53 Ignored Feb 16th Commonwealth Cup 2020 Weekend 1
**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)