#57 Connecticut (15-9)

avg: 1529.14  •  sd: 79.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
55 Georgia Tech Loss 7-8 1423.96 Feb 24th Commonwealth Cup Weekend 2 2024
16 Pennsylvania Loss 5-12 1499.13 Feb 24th Commonwealth Cup Weekend 2 2024
90 MIT Win 10-4 1906.4 Feb 24th Commonwealth Cup Weekend 2 2024
65 James Madison Loss 6-7 1337.49 Feb 24th Commonwealth Cup Weekend 2 2024
121 Temple Win 13-2 1678.5 Feb 25th Commonwealth Cup Weekend 2 2024
98 Maryland Win 8-7 1359.7 Feb 25th Commonwealth Cup Weekend 2 2024
173 Bentley** Win 11-3 1329.06 Ignored Mar 23rd New England Open 2024
109 Brandeis Win 13-0 1765.91 Mar 23rd New England Open 2024
92 Middlebury Win 12-1 1904.95 Mar 23rd New England Open 2024
216 Northeastern-B** Win 13-0 905.25 Ignored Mar 23rd New England Open 2024
101 Rhode Island Win 9-4 1813.69 Mar 24th New England Open 2024
78 Harvard Win 7-2 1964.9 Mar 24th New England Open 2024
68 Vermont-B Win 13-5 2037.43 Mar 24th New England Open 2024
110 Rutgers Win 9-3 1765.12 Apr 13th Eastern Metro East D I Womens Conferences 2024
164 SUNY-Stony Brook** Win 9-1 1406.94 Ignored Apr 13th Eastern Metro East D I Womens Conferences 2024
239 SUNY-Albany** Win 13-0 584.99 Ignored Apr 13th Eastern Metro East D I Womens Conferences 2024
71 Columbia Win 11-5 2007.82 Apr 14th Eastern Metro East D I Womens Conferences 2024
44 Yale Loss 9-13 1227.92 Apr 14th Eastern Metro East D I Womens Conferences 2024
111 NYU Loss 7-10 751.46 Apr 27th Metro East D I College Womens Regionals 2024
44 Yale Loss 4-10 1046.48 Apr 27th Metro East D I College Womens Regionals 2024
150 RIT** Win 13-3 1468.05 Ignored Apr 27th Metro East D I College Womens Regionals 2024
58 Cornell Loss 10-11 1401.29 Apr 27th Metro East D I College Womens Regionals 2024
39 SUNY-Binghamton Loss 8-9 1595.35 Apr 28th Metro East D I College Womens Regionals 2024
54 Ottawa Loss 7-10 1165.24 Apr 28th Metro East 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)