#52 Haverford/Bryn Mawr (21-2)

avg: 1569.87  •  sd: 72.08  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
130 Boston University Win 8-7 1145.93 Feb 24th Bring The Huckus 2024
145 Dartmouth Win 11-5 1506.1 Feb 24th Bring The Huckus 2024
193 SUNY-Geneseo** Win 12-3 1138.01 Ignored Feb 24th Bring The Huckus 2024
94 Lehigh Win 10-3 1875.7 Feb 24th Bring The Huckus 2024
145 Dartmouth Win 11-8 1271.71 Feb 25th Bring The Huckus 2024
168 Swarthmore** Win 10-2 1377.22 Ignored Feb 25th Bring The Huckus 2024
82 Rochester Win 15-5 1944.48 Feb 25th Bring The Huckus 2024
87 Bates Loss 5-7 1004.19 Mar 30th Northeast Classic 2024
130 Boston University Win 11-6 1567.63 Mar 30th Northeast Classic 2024
111 NYU Win 10-4 1741.12 Mar 30th Northeast Classic 2024
87 Bates Win 11-8 1697.94 Mar 31st Northeast Classic 2024
185 Bowdoin** Win 11-4 1185.58 Ignored Mar 31st Northeast Classic 2024
82 Rochester Win 10-3 1944.48 Mar 31st Northeast Classic 2024
68 Vermont-B Win 8-6 1737.92 Mar 31st Northeast Classic 2024
168 Swarthmore** Win 13-3 1377.22 Ignored Apr 14th Pennsylvania D III Womens Conferences 2024
84 Scranton Loss 7-12 819.61 Apr 14th Pennsylvania D III Womens Conferences 2024
207 Messiah** Win 13-5 977.96 Ignored Apr 14th Pennsylvania D III Womens Conferences 2024
94 Lehigh Win 10-8 1538.36 Apr 14th Pennsylvania D III Womens Conferences 2024
168 Swarthmore Win 9-5 1306.28 Apr 27th Ohio Valley D III College Womens Regionals 2024
84 Scranton Win 14-4 1940.12 Apr 27th Ohio Valley D III College Womens Regionals 2024
159 Kenyon** Win 15-6 1425.76 Ignored Apr 27th Ohio Valley D III College Womens Regionals 2024
159 Kenyon** Win 15-4 1425.76 Ignored Apr 28th Ohio Valley D III College Womens Regionals 2024
84 Scranton Win 15-7 1940.12 Apr 28th Ohio Valley 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)