#140 North Carolina-Wilmington (8-15)

avg: 1013.23  •  sd: 80.9  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
32 Georgetown** Loss 4-11 1407.01 Ignored Jan 25th Winta Binta Vinta 2025
48 Liberty** Loss 2-11 1219.58 Ignored Jan 25th Winta Binta Vinta 2025
20 Virginia** Loss 0-13 1668.93 Ignored Jan 25th Winta Binta Vinta 2025
21 Ohio State** Loss 0-13 1666.62 Ignored Jan 26th Winta Binta Vinta 2025
77 Penn State Loss 5-9 968.2 Jan 26th Winta Binta Vinta 2025
245 Virginia-B** Win 13-2 600 Ignored Jan 26th Winta Binta Vinta 2025
49 William & Mary** Loss 2-13 1213.92 Ignored Feb 15th Queen City Tune Up 2025
6 Vermont** Loss 1-13 2071.2 Ignored Feb 15th Queen City Tune Up 2025
30 Wisconsin** Loss 1-13 1422.97 Ignored Feb 15th Queen City Tune Up 2025
55 Appalachian State Loss 6-7 1574.38 Feb 16th Queen City Tune Up 2025
123 Northwestern Loss 4-6 776.9 Feb 16th Queen City Tune Up 2025
176 Charleston Win 9-6 1192.58 Mar 15th Southerns 2025
98 Denver Loss 4-8 758.88 Mar 15th Southerns 2025
233 Florida-B** Win 13-1 835.72 Ignored Mar 15th Southerns 2025
141 Georgia College Win 6-5 1137.61 Mar 15th Southerns 2025
141 Georgia College Win 9-7 1291.94 Mar 15th Southerns 2025
82 Case Western Reserve Loss 1-13 845.74 Mar 29th Needle in a Ho Stack 2025
118 Clemson Loss 6-7 1069.37 Mar 29th Needle in a Ho Stack 2025
99 Emory Loss 4-11 721.96 Mar 29th Needle in a Ho Stack 2025
212 Georgia-B Win 8-6 777.47 Mar 29th Needle in a Ho Stack 2025
142 Berry Win 8-7 1127.17 Mar 30th Needle in a Ho Stack 2025
114 Cedarville Loss 6-9 792.45 Mar 30th Needle in a Ho Stack 2025
151 Davidson Win 7-5 1298.98 Mar 30th Needle in a Ho Stack 2025
**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)