#1 North Carolina (18-2)

avg: 2530.07  •  sd: 72.35  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
91 Case Western Reserve** Win 13-1 1802.67 Ignored Feb 9th Queen City Tune Up 2019 Women
43 Georgia Tech** Win 13-3 2155.59 Ignored Feb 9th Queen City Tune Up 2019 Women
20 North Carolina-Wilmington Win 12-5 2560.18 Feb 9th Queen City Tune Up 2019 Women
32 Brigham Young Win 11-5 2310.48 Feb 9th Queen City Tune Up 2019 Women
3 Ohio State Win 14-10 2771.7 Feb 10th Queen City Tune Up 2019 Women
5 Carleton College-Syzygy Win 15-10 2719.1 Feb 10th Queen City Tune Up 2019 Women
11 Pittsburgh Win 15-10 2536.87 Feb 10th Queen City Tune Up 2019 Women
28 North Carolina State Win 13-7 2331.19 Feb 23rd Commonwealth Cup 2019
58 Penn State** Win 13-1 2051.04 Ignored Feb 23rd Commonwealth Cup 2019
22 Tufts Win 12-8 2375.76 Feb 23rd Commonwealth Cup 2019
3 Ohio State Loss 9-11 2123.79 Feb 24th Commonwealth Cup 2019
40 Michigan** Win 13-1 2169.43 Ignored Feb 24th Commonwealth Cup 2019
28 North Carolina State Win 13-7 2331.19 Mar 21st Atlantic Coast Showcase 32119
13 Stanford Win 15-5 2655.63 Mar 29th NW Challenge Tier 1 Womens
2 California-San Diego Win 15-8 2983.87 Mar 29th NW Challenge Tier 1 Womens
16 Oregon Win 15-7 2617.73 Mar 30th NW Challenge Tier 1 Womens
7 Western Washington Win 12-10 2437.79 Mar 30th NW Challenge Tier 1 Womens
8 Dartmouth Win 15-5 2758.85 Mar 30th NW Challenge Tier 1 Womens
6 British Columbia Loss 11-13 2002.93 Mar 31st NW Challenge Tier 1 Womens
5 Carleton College-Syzygy Win 13-7 2823.03 Mar 31st NW Challenge Tier 1 Womens
**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)