#3 North Carolina (16-1)

avg: 2730.5  •  sd: 71.5  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
34 Northeastern Win 13-8 2551.06 Feb 3rd Queen City Tune Up 2018 College Women
31 Penn State** Win 13-3 2686.19 Ignored Feb 3rd Queen City Tune Up 2018 College Women
8 West Chester Win 13-8 3002.13 Feb 3rd Queen City Tune Up 2018 College Women
32 Florida Win 10-5 2654.14 Feb 3rd Queen City Tune Up 2018 College Women
88 Georgetown** Win 15-0 2178.62 Ignored Feb 24th Commonwealth Cup 2018
21 Michigan Win 15-7 2838.43 Feb 24th Commonwealth Cup 2018
15 North Carolina State Win 15-11 2734.24 Feb 24th Commonwealth Cup 2018
7 Tufts Win 12-10 2746.91 Feb 25th Commonwealth Cup 2018
99 Princeton** Win 13-1 2120.12 Ignored Feb 25th Commonwealth Cup 2018
21 Michigan Win 12-9 2583.8 Feb 25th Commonwealth Cup 2018
15 North Carolina State Win 12-8 2794.23 Mar 20th Atlantic Coast Showcase ACS NCSU vs UNC
69 Boston College** Win 15-0 2350.35 Ignored Mar 24th NW Challenge 2018
26 California Win 11-5 2733.23 Mar 24th NW Challenge 2018
43 Southern California** Win 15-5 2590.28 Ignored Mar 24th NW Challenge 2018
4 Stanford Loss 9-13 2276.95 Mar 24th NW Challenge 2018
16 Western Washington Win 15-11 2725.55 Mar 25th NW Challenge 2018
6 British Columbia Win 15-8 3124.94 Mar 25th NW Challenge 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)