#101 Rhode Island (12-11)

avg: 1213.69  •  sd: 86.16  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
230 Clark** Win 10-2 755.08 Ignored Mar 23rd New England Open 2024
78 Harvard Loss 4-8 800.09 Mar 23rd New England Open 2024
68 Vermont-B Loss 10-11 1312.43 Mar 23rd New England Open 2024
126 Massachusetts Loss 5-10 469.04 Mar 23rd New England Open 2024
173 Bentley Win 14-1 1329.06 Mar 24th New England Open 2024
57 Connecticut Loss 4-9 929.14 Mar 24th New England Open 2024
216 Northeastern-B** Win 11-1 905.25 Ignored Mar 24th New England Open 2024
175 Amherst Win 9-3 1295.49 Mar 30th Northeast Classic 2024
185 Bowdoin Win 9-6 1004.14 Mar 30th Northeast Classic 2024
146 New Hampshire Win 8-3 1491.89 Mar 30th Northeast Classic 2024
68 Vermont-B Loss 4-9 837.43 Mar 31st Northeast Classic 2024
146 New Hampshire Win 7-4 1388.04 Mar 31st Northeast Classic 2024
111 NYU Win 8-5 1594.73 Mar 31st Northeast Classic 2024
82 Rochester Loss 7-8 1219.48 Mar 31st Northeast Classic 2024
27 Brown** Loss 2-12 1269.14 Ignored Apr 13th Greater New England D I Womens Conferences 2024
2 Vermont** Loss 1-13 2077.17 Ignored Apr 13th Greater New England D I Womens Conferences 2024
- Maine** Win 13-5 600 Ignored Apr 13th Greater New England D I Womens Conferences 2024
126 Massachusetts Win 8-4 1607.75 Apr 13th Greater New England D I Womens Conferences 2024
2 Vermont** Loss 3-15 2077.17 Ignored May 4th New England D I College Womens Regionals 2024
68 Vermont-B Loss 9-12 1092.07 May 4th New England D I College Womens Regionals 2024
126 Massachusetts Win 12-6 1622.25 May 4th New England D I College Womens Regionals 2024
146 New Hampshire Win 10-4 1491.89 May 4th New England D I College Womens Regionals 2024
78 Harvard Loss 10-14 966.2 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)