#146 New Hampshire (7-13)

avg: 891.89  •  sd: 72.14  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
175 Amherst Win 9-8 820.49 Mar 3rd Grand Northeast Kickoff
109 Brandeis Loss 7-14 583.02 Mar 3rd Grand Northeast Kickoff
109 Brandeis Loss 4-14 565.91 Mar 9th Live Free or Sky 2024
73 Wellesley Loss 2-15 791.76 Mar 9th Live Free or Sky 2024
175 Amherst Win 7-4 1191.65 Mar 30th Northeast Classic 2024
185 Bowdoin Win 9-5 1114.64 Mar 30th Northeast Classic 2024
101 Rhode Island Loss 3-8 613.69 Mar 30th Northeast Classic 2024
130 Boston University Win 8-5 1474.53 Mar 31st Northeast Classic 2024
81 Wesleyan Loss 6-11 806.62 Mar 31st Northeast Classic 2024
73 Wellesley Loss 6-9 973.19 Mar 31st Northeast Classic 2024
101 Rhode Island Loss 4-7 717.53 Mar 31st Northeast Classic 2024
27 Brown** Loss 1-13 1269.14 Ignored Apr 13th Greater New England D I Womens Conferences 2024
- Maine** Win 12-3 600 Ignored Apr 13th Greater New England D I Womens Conferences 2024
126 Massachusetts Loss 7-8 917.94 Apr 13th Greater New England D I Womens Conferences 2024
126 Massachusetts Win 10-4 1642.94 Apr 13th Greater New England D I Womens Conferences 2024
78 Harvard Loss 4-9 764.9 May 4th New England D I College Womens Regionals 2024
181 Vermont-C Win 10-6 1107.1 May 4th New England D I College Womens Regionals 2024
21 Northeastern** Loss 2-15 1359.88 Ignored May 4th New England D I College Womens Regionals 2024
101 Rhode Island Loss 4-10 613.69 May 4th New England D I College Womens Regionals 2024
122 Boston College Loss 7-12 555.25 May 5th New England 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)