#87 Bates (14-6)

avg: 1332.33  •  sd: 91.79  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
81 Wesleyan Loss 6-9 934.75 Mar 2nd No Sleep till Brooklyn 2024
73 Wellesley Loss 2-12 791.76 Mar 2nd No Sleep till Brooklyn 2024
201 Columbia-B Win 6-3 988.97 Mar 2nd No Sleep till Brooklyn 2024
201 Columbia-B** Win 14-2 1042.28 Ignored Mar 3rd No Sleep till Brooklyn 2024
164 SUNY-Stony Brook Win 9-2 1406.94 Mar 3rd No Sleep till Brooklyn 2024
130 Boston University Win 8-6 1321.42 Mar 30th Northeast Classic 2024
111 NYU Win 10-4 1741.12 Mar 30th Northeast Classic 2024
52 Haverford/Bryn Mawr Win 7-5 1898.01 Mar 30th Northeast Classic 2024
150 RIT Win 11-3 1468.05 Mar 31st Northeast Classic 2024
73 Wellesley Win 10-6 1887.92 Mar 31st Northeast Classic 2024
81 Wesleyan Win 8-4 1918.12 Mar 31st Northeast Classic 2024
52 Haverford/Bryn Mawr Loss 8-11 1204.26 Mar 31st Northeast Classic 2024
145 Dartmouth Loss 6-7 781.1 Apr 13th North New England D III Womens Conferences 2024
- Colby** Win 11-2 600 Ignored Apr 13th North New England D III Womens Conferences 2024
185 Bowdoin** Win 14-0 1185.58 Ignored Apr 13th North New England D III Womens Conferences 2024
92 Middlebury Loss 5-6 1179.95 Apr 13th North New England D III Womens Conferences 2024
166 Smith Win 12-2 1386.69 May 4th New England D III College Womens Regionals 2024
73 Wellesley Win 10-9 1516.76 May 4th New England D III College Womens Regionals 2024
109 Brandeis Win 9-6 1584.48 May 4th New England D III College Womens Regionals 2024
105 Mount Holyoke Loss 3-11 588.61 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)