#96 Connecticut (14-7)

avg: 1249.4  •  sd: 34.9  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
70 Case Western Reserve Loss 9-10 1241.71 Jan 27th Mid Atlantic Warm Up
111 SUNY-Binghamton Loss 9-11 942.52 Jan 27th Mid Atlantic Warm Up
208 Virginia Commonwealth Win 10-7 1175.04 Jan 27th Mid Atlantic Warm Up
61 William & Mary Loss 9-10 1307.01 Jan 27th Mid Atlantic Warm Up
224 American Win 14-4 1331.75 Jan 28th Mid Atlantic Warm Up
208 Virginia Commonwealth Win 15-2 1385.38 Jan 28th Mid Atlantic Warm Up
116 Liberty Win 12-10 1421.08 Jan 28th Mid Atlantic Warm Up
142 Boston University Win 10-8 1331.38 Mar 2nd No Sleep till Brooklyn 2024
198 Delaware Win 9-8 959.68 Mar 2nd No Sleep till Brooklyn 2024
31 Middlebury Loss 5-12 1057.12 Mar 2nd No Sleep till Brooklyn 2024
167 Columbia Win 10-8 1220.92 Mar 3rd No Sleep till Brooklyn 2024
198 Delaware Win 8-6 1135.17 Mar 3rd No Sleep till Brooklyn 2024
46 Williams Loss 10-11 1399.96 Mar 3rd No Sleep till Brooklyn 2024
150 Navy Win 12-11 1159.29 Mar 30th East Coast Invite 2024
113 Syracuse Win 11-10 1313.84 Mar 30th East Coast Invite 2024
278 SUNY-Stony Brook** Win 11-4 1097.13 Ignored Mar 30th East Coast Invite 2024
25 McGill Loss 9-13 1355.69 Mar 30th East Coast Invite 2024
167 Columbia Win 9-7 1237.59 Mar 31st East Coast Invite 2024
123 Pennsylvania Loss 10-11 1022.48 Mar 31st East Coast Invite 2024
146 Yale Win 12-7 1580.56 Mar 31st East Coast Invite 2024
107 Princeton Win 7-6 1333.6 Mar 31st East Coast Invite 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)