#65 James Madison (11-12)

avg: 1462.49  •  sd: 76.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
50 Georgetown Loss 6-9 1182.7 Jan 27th Winta Binta Vinta 2024
229 Virginia-B** Win 10-4 759.59 Ignored Jan 27th Winta Binta Vinta 2024
138 Liberty Win 9-2 1546.76 Jan 27th Winta Binta Vinta 2024
24 Ohio State Loss 3-11 1293.87 Jan 27th Winta Binta Vinta 2024
50 Georgetown Loss 7-8 1476.27 Jan 28th Winta Binta Vinta 2024
36 William & Mary Loss 4-6 1394.28 Jan 28th Winta Binta Vinta 2024
229 Virginia-B Win 5-4 284.59 Jan 28th Winta Binta Vinta 2024
55 Georgia Tech Loss 6-8 1248.46 Feb 24th Commonwealth Cup Weekend 2 2024
57 Connecticut Win 7-6 1654.14 Feb 24th Commonwealth Cup Weekend 2 2024
90 MIT Win 7-5 1634.54 Feb 24th Commonwealth Cup Weekend 2 2024
16 Pennsylvania Loss 4-9 1499.13 Feb 24th Commonwealth Cup Weekend 2 2024
62 Duke Win 9-4 2084.05 Feb 25th Commonwealth Cup Weekend 2 2024
78 Harvard Win 7-5 1693.04 Feb 25th Commonwealth Cup Weekend 2 2024
64 Penn State Loss 8-9 1351.98 Feb 25th Commonwealth Cup Weekend 2 2024
36 William & Mary Loss 7-9 1480.55 Apr 20th Virginia D I Womens Conferences 2024
51 Virginia Loss 5-7 1249.55 Apr 20th Virginia D I Womens Conferences 2024
89 Virginia Tech Loss 9-10 1181.92 Apr 20th Virginia D I Womens Conferences 2024
138 Liberty Win 14-5 1546.76 Apr 20th Virginia D I Womens Conferences 2024
125 Johns Hopkins Win 15-2 1662.17 May 4th Atlantic Coast D I College Womens Regionals 2024
98 Maryland Win 12-10 1472.82 May 4th Atlantic Coast D I College Womens Regionals 2024
6 North Carolina** Loss 1-15 1899.4 Ignored May 4th Atlantic Coast D I College Womens Regionals 2024
51 Virginia Win 13-11 1806.53 May 4th Atlantic Coast D I College Womens Regionals 2024
41 South Carolina Loss 8-11 1333.33 May 5th Atlantic Coast D I College Womens Regionals 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)