#98 Maryland (10-12)

avg: 1234.7  •  sd: 75.73  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
41 South Carolina Loss 7-11 1232.05 Feb 24th Commonwealth Cup Weekend 2 2024
78 Harvard Loss 8-11 999.29 Feb 24th Commonwealth Cup Weekend 2 2024
64 Penn State Loss 5-11 876.98 Feb 24th Commonwealth Cup Weekend 2 2024
57 Connecticut Loss 7-8 1404.14 Feb 25th Commonwealth Cup Weekend 2 2024
89 Virginia Tech Loss 5-10 733.02 Feb 25th Commonwealth Cup Weekend 2 2024
121 Temple Win 10-6 1574.66 Feb 25th Commonwealth Cup Weekend 2 2024
200 Towson Win 12-6 1027.32 Mar 9th Kernel Kup 2024
244 Cornell-B** Win 13-1 317.22 Ignored Mar 30th Atlantic Coast Open 2024
125 Johns Hopkins Win 9-8 1187.17 Mar 30th Atlantic Coast Open 2024
176 Mary Washington Win 13-7 1247.64 Mar 30th Atlantic Coast Open 2024
156 George Washington Win 15-5 1440.57 Mar 31st Atlantic Coast Open 2024
114 Richmond Loss 9-10 1001.29 Mar 31st Atlantic Coast Open 2024
38 American Loss 8-11 1358.07 Apr 20th Colonial D I Womens Conferences 2024
50 Georgetown Loss 4-13 1001.27 Apr 20th Colonial D I Womens Conferences 2024
152 Delaware Win 9-7 1144.84 Apr 20th Colonial D I Womens Conferences 2024
50 Georgetown Loss 7-14 1018.38 Apr 21st Colonial D I Womens Conferences 2024
125 Johns Hopkins Win 13-7 1619.71 Apr 21st Colonial D I Womens Conferences 2024
62 Duke Loss 8-15 919.25 May 4th Atlantic Coast D I College Womens Regionals 2024
65 James Madison Loss 10-12 1224.37 May 4th Atlantic Coast D I College Womens Regionals 2024
125 Johns Hopkins Win 13-9 1480.74 May 4th Atlantic Coast D I College Womens Regionals 2024
6 North Carolina** Loss 4-15 1899.4 Ignored May 4th Atlantic Coast D I College Womens Regionals 2024
51 Virginia Win 12-10 1815.81 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)