#110 Brandeis (7-4)

avg: 1118.17  •  sd: 170.19  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
190 Amherst** Win 10-2 956.01 Ignored Mar 3rd Grand Northeast Kickoff
154 New Hampshire Win 14-7 1343.78 Mar 3rd Grand Northeast Kickoff
85 Wellesley Loss 11-13 1084.96 Mar 9th Live Free or Sky 2024
154 New Hampshire Win 14-4 1360.89 Mar 9th Live Free or Sky 2024
166 Bentley Win 7-3 1178.3 Mar 23rd New England Open 2024
222 Northeastern-B** Win 13-2 318.46 Ignored Mar 23rd New England Open 2024
108 Middlebury Loss 6-7 1021.44 Mar 23rd New England Open 2024
47 Connecticut Loss 0-13 1055.8 Mar 23rd New England Open 2024
74 Harvard Loss 3-9 782.6 Mar 24th New England Open 2024
227 Clark** Win 11-1 -281.54 Ignored Mar 24th New England Open 2024
222 Northeastern-B** Win 15-2 318.46 Ignored Mar 24th New England Open 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)