#24 North Carolina-Charlotte (17-7)

avg: 1700.42  •  sd: 54.09  •  top 16/20: 20.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
142 Carleton College-CHOP Win 15-10 1447.01 Jan 28th Carolina Kickoff
75 Richmond Win 15-9 1827.49 Jan 28th Carolina Kickoff
15 North Carolina State Loss 10-14 1406.58 Jan 28th Carolina Kickoff
17 South Carolina Loss 10-13 1445.73 Jan 28th Carolina Kickoff
42 Penn State Win 15-12 1826.2 Jan 29th Carolina Kickoff
15 North Carolina State Loss 10-15 1351.68 Jan 29th Carolina Kickoff
17 South Carolina Loss 12-13 1648.87 Jan 29th Carolina Kickoff
47 Case Western Reserve Loss 11-13 1226.54 Feb 11th Queen City Tune Up1
73 Purdue Win 12-8 1775.86 Feb 11th Queen City Tune Up1
2 North Carolina Loss 11-15 1757.22 Feb 11th Queen City Tune Up1
61 Harvard Win 15-11 1769.62 Feb 11th Queen City Tune Up1
50 Virginia Win 12-8 1884.75 Feb 12th Queen City Tune Up1
35 Washington University Win 13-9 2027.86 Feb 12th Queen City Tune Up1
84 Alabama Win 13-9 1690.75 Feb 25th Easterns Qualifier 2023
63 Cincinnati Win 13-7 1937.75 Feb 25th Easterns Qualifier 2023
55 Georgetown Win 13-9 1829.72 Feb 25th Easterns Qualifier 2023
39 William & Mary Win 13-8 2031.6 Feb 25th Easterns Qualifier 2023
25 North Carolina-Wilmington Win 12-8 2135.28 Feb 26th Easterns Qualifier 2023
50 Virginia Win 15-13 1657.78 Feb 26th Easterns Qualifier 2023
17 South Carolina Loss 11-15 1392.71 Feb 26th Easterns Qualifier 2023
104 Kennesaw State Win 15-10 1625.97 Mar 25th Needle in a Ho Stack2
203 North Carolina-B** Win 15-6 1325.25 Ignored Mar 25th Needle in a Ho Stack2
238 Georgia College** Win 15-2 1147.43 Ignored Mar 25th Needle in a Ho Stack2
133 Davidson Win 11-6 1584.16 Mar 26th Needle in a Ho Stack2
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)