#78 Harvard (11-10)

avg: 1364.9  •  sd: 68.58  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
41 South Carolina Loss 6-15 1098.94 Feb 24th Commonwealth Cup Weekend 2 2024
64 Penn State Loss 6-7 1351.98 Feb 24th Commonwealth Cup Weekend 2 2024
98 Maryland Win 11-8 1600.31 Feb 24th Commonwealth Cup Weekend 2 2024
55 Georgia Tech Loss 5-9 1019.9 Feb 25th Commonwealth Cup Weekend 2 2024
71 Columbia Win 7-5 1735.96 Feb 25th Commonwealth Cup Weekend 2 2024
65 James Madison Loss 5-7 1134.35 Feb 25th Commonwealth Cup Weekend 2 2024
230 Clark** Win 13-0 755.08 Ignored Mar 23rd New England Open 2024
101 Rhode Island Win 8-4 1778.5 Mar 23rd New England Open 2024
68 Vermont-B Loss 4-8 872.62 Mar 23rd New England Open 2024
126 Massachusetts Win 9-6 1461.51 Mar 23rd New England Open 2024
109 Brandeis Win 9-3 1765.91 Mar 24th New England Open 2024
57 Connecticut Loss 2-7 929.14 Mar 24th New England Open 2024
126 Massachusetts Win 8-3 1642.94 Mar 24th New England Open 2024
122 Boston College Win 10-9 1200.76 Apr 20th Metro Boston D I Womens Conferences 2024
130 Boston University Win 12-7 1541.44 Apr 20th Metro Boston D I Womens Conferences 2024
21 Northeastern Loss 8-10 1697.21 Apr 20th Metro Boston D I Womens Conferences 2024
90 MIT Loss 7-9 1027.06 Apr 20th Metro Boston D I Womens Conferences 2024
21 Northeastern Loss 5-15 1359.88 May 4th New England D I College Womens Regionals 2024
146 New Hampshire Win 9-4 1491.89 May 4th New England D I College Womens Regionals 2024
90 MIT Loss 8-11 940.79 May 4th New England D I College Womens Regionals 2024
101 Rhode Island Win 14-10 1612.4 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)