#16 North Carolina-Wilmington (19-2)

avg: 1884.51  •  sd: 44.49  •  top 16/20: 93.8%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
69 Carleton College-GoP Win 13-7 2006.99 Jan 20th Carolina Kickoff 2018 NC Ultimate
37 Central Florida Win 12-7 2155.26 Jan 20th Carolina Kickoff 2018 NC Ultimate
12 North Carolina State Win 11-8 2284.47 Jan 21st Carolina Kickoff 2018 NC Ultimate
14 Florida Win 11-10 2011.82 Jan 21st Carolina Kickoff 2018 NC Ultimate
91 Penn State Win 13-7 1931.44 Jan 21st Carolina Kickoff 2018 NC Ultimate
30 Auburn Win 10-9 1834.26 Feb 3rd Queen City Tune Up 2018 College Open
64 North Carolina-Charlotte Win 11-7 1929.4 Feb 3rd Queen City Tune Up 2018 College Open
91 Penn State Win 10-8 1636.57 Feb 3rd Queen City Tune Up 2018 College Open
133 Case Western Reserve** Win 11-4 1775.77 Ignored Feb 3rd Queen City Tune Up 2018 College Open
151 George Mason Win 11-6 1663.53 Feb 3rd Queen City Tune Up 2018 College Open
124 Indiana Win 13-8 1722.42 Mar 10th Tally Classic XIII
168 South Florida** Win 13-5 1663.99 Ignored Mar 10th Tally Classic XIII
28 Carnegie Mellon Win 14-12 1939.61 Mar 10th Tally Classic XIII
88 Alabama-Huntsville Win 13-6 1988.31 Mar 10th Tally Classic XIII
224 Georgia Southern** Win 13-3 1461.24 Ignored Mar 10th Tally Classic XIII
52 Harvard Win 15-12 1836.51 Mar 11th Tally Classic XIII
9 Georgia Win 15-14 2074.28 Mar 11th Tally Classic XIII
7 Pittsburgh Loss 12-13 1862.46 Mar 31st Easterns 2018
37 Central Florida Win 15-10 2088.36 Mar 31st Easterns 2018
65 California-Santa Barbara Win 12-11 1587.37 Mar 31st Easterns 2018
2 Carleton College Loss 5-15 1628.2 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)