#205 North Carolina State-B (14-7)

avg: 1040.51  •  sd: 64.38  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
111 Liberty Loss 6-10 892.81 Feb 15th 2025 Commonwealth Cup Weekend 1
144 Oberlin Loss 4-10 670.28 Feb 15th 2025 Commonwealth Cup Weekend 1
334 South Carolina-B Win 7-2 1160.45 Feb 16th 2025 Commonwealth Cup Weekend 1
226 West Virginia Loss 4-7 452.61 Feb 16th 2025 Commonwealth Cup Weekend 1
173 East Carolina Loss 7-8 1041.37 Mar 29th Needle in a Ho Stack 2025
233 Georgia Southern Loss 9-10 793.6 Mar 29th Needle in a Ho Stack 2025
82 Tennessee Loss 3-11 925.87 Mar 29th Needle in a Ho Stack 2025
212 Cedarville Win 15-5 1615.17 Mar 30th Needle in a Ho Stack 2025
265 Georgia-B Win 10-7 1195.85 Mar 30th Needle in a Ho Stack 2025
239 Wake Forest Win 13-8 1400.93 Mar 30th Needle in a Ho Stack 2025
406 William & Mary-B** Win 12-5 556.27 Ignored Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
334 South Carolina-B Win 15-1 1160.45 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
264 Virginia Tech-B Win 13-5 1406.34 Apr 12th Southern Atlantic Coast Dev Mens Conferences 2025
198 North Carolina-B Win 9-8 1186.64 Apr 13th Southern Atlantic Coast Dev Mens Conferences 2025
339 Delaware-B Win 8-5 985.59 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
343 Virginia-B Win 11-9 752.05 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
264 Virginia Tech-B Loss 9-10 681.34 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
396 Maryland-B** Win 13-4 707.67 Ignored Apr 26th Atlantic Coast Dev College Mens Regionals 2025
339 Delaware-B Win 13-7 1089.52 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
334 South Carolina-B Win 13-7 1117.98 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
264 Virginia Tech-B Win 12-11 931.34 Apr 27th Atlantic Coast Dev College Mens Regionals 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)