#75 Columbia (8-10)

avg: 1374.91  •  sd: 60.21  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
94 Duke Win 15-3 1867.64 Feb 24th Commonwealth Cup Weekend 2 2024
104 Massachusetts Loss 8-9 1043.38 Feb 24th Commonwealth Cup Weekend 2 2024
163 Temple** Win 11-2 1234.57 Ignored Feb 24th Commonwealth Cup Weekend 2 2024
31 Brown Loss 5-6 1749.19 Feb 25th Commonwealth Cup Weekend 2 2024
74 Harvard Loss 5-7 1054.45 Feb 25th Commonwealth Cup Weekend 2 2024
94 Duke Win 5-3 1686.21 Feb 25th Commonwealth Cup Weekend 2 2024
135 NYU Win 9-5 1439.89 Mar 2nd No Sleep till Brooklyn 2024
80 Williams Loss 6-7 1218.83 Mar 2nd No Sleep till Brooklyn 2024
176 SUNY-Stony Brook** Win 10-4 1105.03 Ignored Mar 2nd No Sleep till Brooklyn 2024
125 Mount Holyoke Win 7-4 1463.36 Mar 3rd No Sleep till Brooklyn 2024
85 Wellesley Win 5-4 1438.8 Mar 3rd No Sleep till Brooklyn 2024
58 Cornell Loss 5-8 1073.93 Mar 3rd No Sleep till Brooklyn 2024
90 Carnegie Mellon Loss 6-7 1165.85 Mar 30th East Coast Invite 2024
17 Pennsylvania Loss 6-13 1524.71 Mar 30th East Coast Invite 2024
29 Wisconsin Loss 4-13 1313.61 Mar 30th East Coast Invite 2024
41 SUNY-Binghamton Loss 8-11 1337.98 Mar 30th East Coast Invite 2024
61 Penn State Loss 5-8 1049.89 Mar 31st East Coast Invite 2024
114 West Chester Win 10-1 1660.72 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)