#138 George Washington (9-13)

avg: 791.3  •  sd: 62.5  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
223 Dickinson Win 11-1 805.15 Feb 22nd Bring The Huckus 2025
118 Swarthmore Win 8-4 1504.04 Feb 22nd Bring The Huckus 2025
160 Syracuse Win 5-4 788.44 Feb 22nd Bring The Huckus 2025
184 Skidmore Win 8-4 1086.2 Feb 22nd Bring The Huckus 2025
36 Haverford/Bryn Mawr** Loss 3-10 1019.05 Ignored Feb 23rd Bring The Huckus 2025
94 Ithaca Loss 5-10 520.18 Feb 23rd Bring The Huckus 2025
45 American Loss 4-9 942.41 Mar 1st Cherry Blossom Classic 2025
119 Brown-B Win 8-7 1062.46 Mar 1st Cherry Blossom Classic 2025
53 Maryland** Loss 0-8 857.11 Ignored Mar 1st Cherry Blossom Classic 2025
244 Pennsylvania-B Win 3-1 635.03 Mar 1st Cherry Blossom Classic 2025
166 East Carolina Win 8-3 1225.91 Mar 2nd Cherry Blossom Classic 2025
74 Penn State Loss 3-8 659.73 Mar 2nd Cherry Blossom Classic 2025
45 American** Loss 3-11 942.41 Ignored Apr 12th Colonial D I Womens Conferences 2025
168 Delaware Win 9-7 888.55 Apr 12th Colonial D I Womens Conferences 2025
26 Georgetown** Loss 2-15 1201 Ignored Apr 12th Colonial D I Womens Conferences 2025
45 American** Loss 1-14 942.41 Ignored Apr 13th Colonial D I Womens Conferences 2025
168 Delaware Win 11-8 974.83 Apr 13th Colonial D I Womens Conferences 2025
159 Charleston Loss 10-13 336.85 Apr 26th Atlantic Coast D I College Womens Regionals 2025
42 Duke** Loss 5-14 965.5 Ignored Apr 26th Atlantic Coast D I College Womens Regionals 2025
53 Maryland Loss 5-11 857.11 Apr 26th Atlantic Coast D I College Womens Regionals 2025
37 William & Mary** Loss 1-14 1002.87 Ignored Apr 26th Atlantic Coast D I College Womens Regionals 2025
126 North Carolina-Wilmington Loss 5-12 247.29 Apr 27th Atlantic Coast D I College Womens Regionals 2025
**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)