#147 Boston University (7-14)

avg: 722.6  •  sd: 88.56  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
30 UCLA** Loss 2-13 1114.42 Ignored Mar 22nd Womens Centex 2025
73 Colorado College Loss 5-13 660.16 Mar 22nd Womens Centex 2025
255 Texas-B** Win 13-0 464.54 Ignored Mar 22nd Womens Centex 2025
44 Texas-Dallas** Loss 3-11 953.39 Ignored Mar 22nd Womens Centex 2025
105 San Diego State Loss 11-14 722.47 Mar 23rd Womens Centex 2025
135 Trinity Win 14-6 1402.96 Mar 23rd Womens Centex 2025
157 Bates Loss 5-6 546.73 Mar 29th New England Open 2025
232 Northeastern-B Win 11-1 731.39 Mar 29th New England Open 2025
93 Rhode Island Loss 2-12 502.07 Mar 29th New England Open 2025
134 Bowdoin Win 8-2 1404.28 Mar 29th New England Open 2025
157 Bates Win 10-8 934.39 Mar 30th New England Open 2025
137 Rutgers Loss 6-9 374.18 Mar 30th New England Open 2025
90 SUNY-Buffalo Loss 5-10 542.44 Mar 30th New England Open 2025
150 Boston College Loss 7-11 226.43 Apr 13th Metro Boston D I Womens Conferences 2025
3 Tufts** Loss 0-15 1888.77 Ignored Apr 13th Metro Boston D I Womens Conferences 2025
129 Harvard Loss 10-11 708.28 Apr 13th Metro Boston D I Womens Conferences 2025
62 Brown** Loss 3-15 751.28 Ignored Apr 26th New England D I College Womens Regionals 2025
119 Brown-B Win 12-10 1175.58 Apr 26th New England D I College Womens Regionals 2025
86 Vermont-B Loss 7-14 556.9 Apr 26th New England D I College Womens Regionals 2025
150 Boston College Win 10-9 818.33 Apr 27th New England D I College Womens Regionals 2025
129 Harvard Loss 7-11 366.38 Apr 27th New England 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)