#25 North Carolina-Wilmington (14-6)

avg: 1667.14  •  sd: 54.24  •  top 16/20: 18.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
74 Indiana Win 12-9 1557.34 Jan 27th Carolina Kickoff 2024
34 South Carolina Loss 14-15 1435.75 Jan 27th Carolina Kickoff 2024
92 Tennessee Win 15-6 1683.19 Jan 27th Carolina Kickoff 2024
100 Appalachian State Win 15-8 1591.56 Jan 28th Carolina Kickoff 2024
15 Penn State Loss 9-14 1323.02 Jan 28th Carolina Kickoff 2024
42 North Carolina-Charlotte Loss 12-15 1166.75 Jan 28th Carolina Kickoff 2024
23 McGill Loss 12-14 1488.61 Feb 10th Queen City Tune Up 2024
74 Indiana Win 14-10 1610.68 Feb 10th Queen City Tune Up 2024
58 Virginia Win 13-10 1658.71 Feb 10th Queen City Tune Up 2024
4 North Carolina Loss 10-12 1874.92 Feb 10th Queen City Tune Up 2024
34 South Carolina Win 15-8 2125.56 Feb 11th Queen City Tune Up 2024
15 Penn State Loss 8-12 1355.74 Feb 11th Queen City Tune Up 2024
66 Emory Win 12-9 1600.65 Feb 24th Easterns Qualifier 2024
68 Cincinnati Win 12-7 1770.67 Feb 24th Easterns Qualifier 2024
72 James Madison Win 12-8 1670.32 Feb 24th Easterns Qualifier 2024
61 Auburn Win 12-6 1870.91 Feb 24th Easterns Qualifier 2024
34 South Carolina Win 12-8 2001.91 Feb 25th Easterns Qualifier 2024
148 Rutgers** Win 13-5 1330.6 Ignored Feb 25th Easterns Qualifier 2024
15 Penn State Win 12-11 1921.89 Feb 25th Easterns Qualifier 2024
42 North Carolina-Charlotte Win 10-8 1729.91 Feb 25th Easterns Qualifier 2024
**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)