#49 Duke (13-4)

avg: 1951.48  •  sd: 82.47  •  top 16/20: 0.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
135 William & Mary** Win 15-1 1873.75 Ignored Jan 27th Winta Binta Vinta Fest 2018
145 Liberty** Win 13-0 1814.02 Ignored Jan 27th Winta Binta Vinta Fest 2018
66 Virginia Win 9-6 2190.27 Jan 27th Winta Binta Vinta Fest 2018
150 Virginia Commonwealth** Win 11-1 1786.24 Ignored Jan 27th Winta Binta Vinta Fest 2018
80 James Madison Win 13-9 2065.63 Jan 28th Winta Binta Vinta Fest 2018
46 North Carolina-Wilmington Loss 4-12 1378.21 Jan 28th Winta Binta Vinta Fest 2018
15 North Carolina State Loss 9-15 1837.59 Feb 22nd Atlantic Coast Showcase ACS NCSU vs Duke
86 Maryland Win 14-12 1813.26 Feb 24th Commonwealth Cup 2018
250 Davidson** Win 15-0 1020.47 Ignored Feb 24th Commonwealth Cup 2018
123 MIT Win 13-9 1777.79 Feb 24th Commonwealth Cup 2018
7 Tufts Loss 6-13 1908.79 Feb 25th Commonwealth Cup 2018
88 Georgetown Win 11-10 1703.62 Feb 25th Commonwealth Cup 2018
46 North Carolina-Wilmington Win 13-7 2535.74 Feb 25th Commonwealth Cup 2018
134 Tennessee Win 15-7 1876.04 Mar 31st Easterns 2018
39 Clemson Win 11-9 2268.35 Mar 31st Easterns 2018
93 Cornell Win 15-7 2140.61 Mar 31st Easterns 2018
15 North Carolina State Loss 6-14 1753.08 Mar 31st Easterns 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)