#138 Massachusetts (9-12)

avg: 798.11  •  sd: 86.21  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
235 Cornell-B** Win 5-1 720.28 Ignored Mar 1st Garden State 2025
93 NYU Loss 4-6 745.83 Mar 1st Garden State 2025
162 Colby Win 5-3 1078.33 Mar 2nd Garden State 2025
104 Yale Win 4-3 1165.63 Mar 2nd Garden State 2025
56 Rochester** Loss 2-6 821.56 Ignored Mar 2nd Garden State 2025
93 NYU Loss 2-4 615.28 Mar 2nd Garden State 2025
51 Middlebury** Loss 2-13 881.55 Ignored Mar 29th Northeast Classic 2025
86 Wellesley Loss 4-11 543.71 Mar 29th Northeast Classic 2025
112 SUNY-Binghamton Loss 3-8 370.01 Mar 29th Northeast Classic 2025
149 Dartmouth Loss 7-9 429.01 Mar 30th Northeast Classic 2025
163 SUNY-Geneseo Loss 6-8 345.71 Mar 30th Northeast Classic 2025
183 Vermont-C Win 8-6 826.27 Mar 30th Northeast Classic 2025
61 Brown Loss 2-8 751.12 Apr 12th Greater New England D I Womens Conferences 2025
241 Maine** Win 11-2 650.72 Ignored Apr 12th Greater New England D I Womens Conferences 2025
5 Vermont** Loss 2-14 1686.29 Ignored Apr 12th Greater New England D I Womens Conferences 2025
174 New Hampshire Win 5-4 706.82 Apr 12th Greater New England D I Womens Conferences 2025
151 Boston College Win 12-10 931.51 Apr 26th New England D I College Womens Regionals 2025
131 Harvard Win 10-7 1222.96 Apr 26th New England D I College Womens Regionals 2025
3 Tufts** Loss 1-15 1886.95 Ignored Apr 26th New England D I College Womens Regionals 2025
61 Brown Loss 4-15 751.12 Apr 27th New England D I College Womens Regionals 2025
87 Vermont-B Win 9-8 1264.77 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)