#193 SUNY-Geneseo (4-16)

avg: 538.01  •  sd: 56.68  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
130 Boston University Loss 4-11 420.93 Feb 24th Bring The Huckus 2024
145 Dartmouth Loss 6-7 781.1 Feb 24th Bring The Huckus 2024
52 Haverford/Bryn Mawr** Loss 3-12 969.87 Ignored Feb 24th Bring The Huckus 2024
94 Lehigh Loss 5-10 701.8 Feb 24th Bring The Huckus 2024
145 Dartmouth Loss 6-8 605.61 Feb 25th Bring The Huckus 2024
94 Lehigh Loss 7-10 886.03 Feb 25th Bring The Huckus 2024
168 Swarthmore Loss 7-8 652.22 Feb 25th Bring The Huckus 2024
236 SUNY-Cortland Win 5-3 445.94 Mar 23rd King of New York 2024
122 Boston College Loss 5-9 546.7 Mar 24th King of New York 2024
142 Ithaca Win 5-4 1045.19 Mar 24th King of New York 2024
94 Lehigh Loss 5-9 746.64 Mar 24th King of New York 2024
236 SUNY-Cortland Win 6-2 627.37 Mar 24th King of New York 2024
157 Hamilton Loss 5-7 509.56 Apr 20th Western NY D III Womens Conferences 2024
142 Ithaca Loss 1-9 320.19 Apr 20th Western NY D III Womens Conferences 2024
82 Rochester** Loss 2-11 744.48 Ignored Apr 20th Western NY D III Womens Conferences 2024
144 Skidmore Loss 3-9 312.28 Apr 27th Metro East D III College Womens Regionals 2024
142 Ithaca Loss 1-15 320.19 Apr 27th Metro East D III College Womens Regionals 2024
215 Vassar Win 11-4 915.55 Apr 27th Metro East D III College Womens Regionals 2024
157 Hamilton Loss 5-11 237.7 Apr 28th Metro East D III College Womens Regionals 2024
215 Vassar Loss 7-8 190.55 Apr 28th Metro East 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)