#156 George Washington (11-9)

avg: 840.57  •  sd: 63.78  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
204 Elon Win 7-2 1007.21 Feb 17th Commonwealth Cup Weekend 1 2024
229 Virginia-B Win 7-5 487.74 Feb 17th Commonwealth Cup Weekend 1 2024
63 Tennessee Loss 6-13 878.12 Feb 17th Commonwealth Cup Weekend 1 2024
138 Liberty Loss 7-8 821.76 Feb 18th Commonwealth Cup Weekend 1 2024
63 Tennessee Loss 3-6 931.42 Feb 18th Commonwealth Cup Weekend 1 2024
38 American** Loss 1-12 1123.68 Ignored Mar 2nd Cherry Blossom Classic 2024
200 Towson Win 8-7 573.01 Mar 2nd Cherry Blossom Classic 2024
240 American-B** Win 10-1 572.93 Ignored Mar 3rd Cherry Blossom Classic 2024
94 Lehigh Loss 6-10 779.54 Mar 3rd Cherry Blossom Classic 2024
214 Miami (Florida) Win 13-1 917.24 Mar 3rd Cherry Blossom Classic 2024
152 Delaware Win 9-8 990.51 Mar 3rd Cherry Blossom Classic 2024
220 Dickinson Win 13-6 873.22 Mar 30th Atlantic Coast Open 2024
168 Swarthmore Win 12-7 1297.73 Mar 30th Atlantic Coast Open 2024
114 Richmond Win 8-6 1426.78 Mar 30th Atlantic Coast Open 2024
244 Cornell-B** Win 12-3 317.22 Ignored Mar 31st Atlantic Coast Open 2024
125 Johns Hopkins Loss 5-14 462.17 Mar 31st Atlantic Coast Open 2024
98 Maryland Loss 5-15 634.7 Mar 31st Atlantic Coast Open 2024
125 Johns Hopkins Loss 4-11 462.17 Apr 20th Colonial D I Womens Conferences 2024
200 Towson Win 12-1 1048.01 Apr 20th Colonial D I Womens Conferences 2024
152 Delaware Loss 10-11 740.51 Apr 21st Colonial D I Womens Conferences 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)