#183 Vermont-C (4-7)

avg: 525.78  •  sd: 42.7  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
240 Connecticut College Win 7-5 403.47 Mar 29th Northeast Classic 2025
149 Dartmouth Loss 5-7 380.2 Mar 29th Northeast Classic 2025
170 Miami (Florida) Win 5-4 734.35 Mar 29th Northeast Classic 2025
96 Ithaca Loss 4-13 493.91 Mar 30th Northeast Classic 2025
138 Massachusetts Loss 6-8 497.62 Mar 30th Northeast Classic 2025
120 Brown-B Loss 4-7 441.35 Apr 12th New England Dev Womens Conferences 2025
233 Northeastern-B Win 6-3 678.13 Apr 12th New England Dev Womens Conferences 2025
153 Tufts-B Loss 5-7 353.72 Apr 12th New England Dev Womens Conferences 2025
120 Brown-B Loss 6-9 518.94 Apr 13th New England Dev Womens Conferences 2025
153 Tufts-B Win 6-5 806.86 Apr 13th New England Dev Womens Conferences 2025
87 Vermont-B** Loss 2-13 539.77 Ignored Apr 13th New England Dev Womens Conferences 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)