#11 North Carolina State (19-7)

avg: 2027.57  •  sd: 38.27  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
94 Appalachian State Win 13-6 1972.43 Jan 26th Carolina Kickoff 2019
55 Florida State Win 13-2 2211.67 Jan 26th Carolina Kickoff 2019
73 Temple Win 13-3 2080.87 Jan 26th Carolina Kickoff 2019
69 Emory Win 15-9 2023.94 Jan 27th Carolina Kickoff 2019
78 Carleton College-GoP Win 15-5 2057.72 Jan 27th Carolina Kickoff 2019
1 North Carolina Loss 12-15 1931.43 Jan 27th Carolina Kickoff 2019
36 Alabama Win 11-7 2190.03 Feb 9th Queen City Tune Up 2019 Men
57 Carnegie Mellon Win 12-8 2028.53 Feb 9th Queen City Tune Up 2019 Men
52 Notre Dame Win 13-8 2122.83 Feb 9th Queen City Tune Up 2019 Men
108 North Carolina-Charlotte Win 13-7 1882.6 Feb 9th Queen City Tune Up 2019 Men
9 Massachusetts Loss 16-17 1940.5 Feb 10th Queen City Tune Up 2019 Men
14 Ohio State Win 15-13 2206.24 Feb 10th Queen City Tune Up 2019 Men
26 North Carolina-Wilmington Win 15-11 2162.14 Feb 10th Queen City Tune Up 2019 Men
62 Duke Win 13-9 1969.57 Mar 7th Atlantic Coast Showcase 3719
25 South Carolina Win 13-8 2282.85 Mar 9th Classic City Invite 2019
61 Tennessee Win 13-4 2154.19 Mar 9th Classic City Invite 2019
20 Tufts Win 13-10 2192.29 Mar 9th Classic City Invite 2019
4 Pittsburgh Loss 5-10 1611.02 Mar 10th Classic City Invite 2019
9 Massachusetts Loss 8-11 1699.89 Mar 10th Classic City Invite 2019
26 North Carolina-Wilmington Loss 8-9 1655.98 Mar 10th Classic City Invite 2019
2 Brown Loss 10-13 1901.02 Mar 30th Easterns 2019 Men
24 Auburn Win 13-8 2292.94 Mar 30th Easterns 2019 Men
47 Maryland Win 13-8 2152.49 Mar 30th Easterns 2019 Men
28 Northeastern Win 13-8 2271.99 Mar 30th Easterns 2019 Men
7 Carleton College-CUT Loss 8-13 1622.48 Mar 31st Easterns 2019 Men
20 Tufts Win 12-10 2102.27 Mar 31st Easterns 2019 Men
**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)