#109 Brandeis (12-8)

avg: 1165.91  •  sd: 58.84  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
175 Amherst Win 10-2 1295.49 Mar 3rd Grand Northeast Kickoff
146 New Hampshire Win 14-7 1474.77 Mar 3rd Grand Northeast Kickoff
73 Wellesley Loss 11-13 1162.92 Mar 9th Live Free or Sky 2024
146 New Hampshire Win 14-4 1491.89 Mar 9th Live Free or Sky 2024
173 Bentley Win 7-3 1329.06 Mar 23rd New England Open 2024
216 Northeastern-B** Win 13-2 905.25 Ignored Mar 23rd New England Open 2024
92 Middlebury Loss 6-7 1179.95 Mar 23rd New England Open 2024
57 Connecticut Loss 0-13 929.14 Mar 23rd New England Open 2024
78 Harvard Loss 3-9 764.9 Mar 24th New England Open 2024
230 Clark** Win 11-1 755.08 Ignored Mar 24th New England Open 2024
216 Northeastern-B** Win 15-2 905.25 Ignored Mar 24th New England Open 2024
172 Stonehill Win 15-6 1350.41 Apr 20th Metro Boston D III Womens Conferences 2024
173 Bentley Win 15-3 1329.06 Apr 20th Metro Boston D III Womens Conferences 2024
73 Wellesley Loss 10-13 1063.62 Apr 20th Metro Boston D III Womens Conferences 2024
172 Stonehill Win 15-0 1350.41 May 4th New England D III College Womens Regionals 2024
175 Amherst Win 11-6 1242.18 May 4th New England D III College Womens Regionals 2024
87 Bates Loss 6-9 913.76 May 4th New England D III College Womens Regionals 2024
105 Mount Holyoke Win 9-7 1467.95 May 4th New England D III College Womens Regionals 2024
73 Wellesley Loss 3-8 791.76 May 5th New England D III College Womens Regionals 2024
92 Middlebury Loss 3-9 704.95 May 5th New England D III College Womens Regionals 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)