#94 Duke (10-8)

avg: 1267.64  •  sd: 82.82  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
156 Clemson Win 9-4 1322.32 Jan 20th Carolina Kickoff Womens 2024
4 North Carolina** Loss 1-14 2022.41 Ignored Jan 20th Carolina Kickoff Womens 2024
150 North Carolina-B Win 15-2 1392.78 Jan 20th Carolina Kickoff Womens 2024
26 North Carolina State** Loss 3-13 1328.54 Ignored Jan 20th Carolina Kickoff Womens 2024
4 North Carolina Loss 6-13 2022.41 Jan 21st Carolina Kickoff Womens 2024
150 North Carolina-B Win 13-4 1392.78 Jan 21st Carolina Kickoff Womens 2024
75 Columbia Loss 3-15 774.91 Feb 24th Commonwealth Cup Weekend 2 2024
163 Temple Win 14-9 1108.44 Feb 24th Commonwealth Cup Weekend 2 2024
104 Massachusetts Loss 12-13 1043.38 Feb 24th Commonwealth Cup Weekend 2 2024
75 Columbia Loss 3-5 956.34 Feb 25th Commonwealth Cup Weekend 2 2024
42 Purdue Loss 8-11 1335.18 Feb 25th Commonwealth Cup Weekend 2 2024
70 James Madison Loss 4-9 819.57 Feb 25th Commonwealth Cup Weekend 2 2024
127 Dartmouth Win 9-7 1227.02 Mar 23rd Rodeo 2024
123 Liberty Win 8-7 1103.52 Mar 23rd Rodeo 2024
150 North Carolina-B Win 6-4 1158.39 Mar 23rd Rodeo 2024
80 Williams Win 7-4 1839.99 Mar 23rd Rodeo 2024
150 North Carolina-B Win 12-3 1392.78 Mar 24th Rodeo 2024
80 Williams Win 8-7 1468.83 Mar 24th Rodeo 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)