#125 Mount Holyoke (6-7)

avg: 967.2  •  sd: 81.82  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
105 Rutgers Win 8-6 1457.23 Mar 2nd No Sleep till Brooklyn 2024
58 Cornell Loss 7-9 1248.19 Mar 2nd No Sleep till Brooklyn 2024
203 SUNY-Buffalo** Win 12-4 777.86 Ignored Mar 2nd No Sleep till Brooklyn 2024
105 Rutgers Loss 4-6 791.13 Mar 3rd No Sleep till Brooklyn 2024
75 Columbia Loss 4-7 878.75 Mar 3rd No Sleep till Brooklyn 2024
93 Wesleyan Loss 7-9 993.13 Mar 3rd No Sleep till Brooklyn 2024
105 Rutgers Loss 4-9 556.74 Mar 30th Northeast Classic 2024
208 Connecticut College Win 9-4 705.54 Mar 30th Northeast Classic 2024
163 Temple Win 10-6 1130.73 Mar 30th Northeast Classic 2024
105 Rutgers Loss 2-7 556.74 Mar 31st Northeast Classic 2024
175 Bowdoin Win 10-2 1118.41 Mar 31st Northeast Classic 2024
98 Rochester Loss 5-8 763.57 Mar 31st Northeast Classic 2024
135 NYU Win 6-3 1457.53 Mar 31st Northeast Classic 2024
**Blowout Eligible

FAQ

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
  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
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)