#26 North Carolina State (7-5)

avg: 1928.54  •  sd: 94.31  •  top 16/20: 6.7%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
94 Duke** Win 13-3 1867.64 Ignored Jan 20th Carolina Kickoff Womens 2024
4 North Carolina Loss 6-9 2203.84 Jan 20th Carolina Kickoff Womens 2024
150 North Carolina-B** Win 14-0 1392.78 Ignored Jan 20th Carolina Kickoff Womens 2024
156 Clemson** Win 14-3 1322.32 Ignored Jan 21st Carolina Kickoff Womens 2024
4 North Carolina** Loss 2-7 2022.41 Ignored Jan 21st Carolina Kickoff Womens 2024
150 North Carolina-B** Win 15-1 1392.78 Ignored Jan 21st Carolina Kickoff Womens 2024
90 Carnegie Mellon** Win 15-4 1890.85 Ignored Feb 24th Commonwealth Cup Weekend 2 2024
12 Michigan Loss 11-15 1930.44 Feb 24th Commonwealth Cup Weekend 2 2024
41 SUNY-Binghamton Win 12-7 2224.1 Feb 24th Commonwealth Cup Weekend 2 2024
39 Virginia Loss 8-9 1613.89 Feb 25th Commonwealth Cup Weekend 2 2024
104 Massachusetts** Win 11-3 1768.38 Ignored Feb 25th Commonwealth Cup Weekend 2 2024
17 Pennsylvania Loss 7-10 1735.04 Feb 25th Commonwealth Cup Weekend 2 2024
**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)