#89 Columbia (6-11)

avg: 1078.66  •  sd: 75.35  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
32 SUNY-Binghamton Loss 5-13 1051.59 Feb 25th Commonwealth Cup Weekend2 2023
10 Northeastern** Loss 1-13 1534.33 Ignored Feb 25th Commonwealth Cup Weekend2 2023
59 Penn State Loss 8-10 1038.58 Feb 25th Commonwealth Cup Weekend2 2023
14 Virginia Loss 5-11 1330.66 Feb 25th Commonwealth Cup Weekend2 2023
69 Case Western Reserve Loss 8-12 809.3 Feb 26th Commonwealth Cup Weekend2 2023
36 Brown Loss 5-11 980.07 Feb 26th Commonwealth Cup Weekend2 2023
33 Ohio State Loss 8-11 1268.29 Feb 26th Commonwealth Cup Weekend2 2023
151 Rutgers Win 9-6 1024.08 Mar 4th No Sleep Till Brooklyn 2023
76 Bates Win 8-6 1481.86 Mar 4th No Sleep Till Brooklyn 2023
55 Cornell Loss 7-9 1066.65 Mar 4th No Sleep Till Brooklyn 2023
96 Harvard Win 8-5 1475.25 Mar 5th No Sleep Till Brooklyn 2023
58 Williams Loss 6-8 1024.27 Mar 5th No Sleep Till Brooklyn 2023
63 Haverford/Bryn Mawr Loss 3-8 676.27 Mar 25th Garden State1
113 Ithaca Win 7-5 1233.41 Mar 25th Garden State1
111 Lehigh Win 10-6 1414.36 Mar 25th Garden State1
185 Messiah** Win 13-0 863.48 Ignored Mar 26th Garden State1
111 Lehigh Loss 2-8 318.2 Mar 26th Garden State1
**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)