(28) #193 SUNY-Geneseo (4-16)

538.01 (60)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
130 Boston University Loss 4-11 -5.56 6 4.53% Counts (Why) Feb 24th Bring The Huckus 2024
145 Dartmouth Loss 6-7 10.36 42 4.09% Counts Feb 24th Bring The Huckus 2024
52 Haverford/Bryn Mawr** Loss 3-12 0 8 0% Ignored (Why) Feb 24th Bring The Huckus 2024
94 Lehigh Loss 5-10 7.52 105 4.39% Counts Feb 24th Bring The Huckus 2024
145 Dartmouth Loss 6-8 2.99 42 4.24% Counts Feb 25th Bring The Huckus 2024
94 Lehigh Loss 7-10 17.06 105 4.67% Counts Feb 25th Bring The Huckus 2024
168 Swarthmore Loss 7-8 5.24 204 4.39% Counts Feb 25th Bring The Huckus 2024
236 SUNY-Cortland Win 5-3 -3.87 60 4.04% Counts (Why) Mar 23rd King of New York 2024
122 Boston College Loss 5-9 0.49 220 5.34% Counts Mar 24th King of New York 2024
142 Ithaca Win 5-4 22.7 286 4.28% Counts Mar 24th King of New York 2024
94 Lehigh Loss 5-9 11.77 105 5.34% Counts Mar 24th King of New York 2024
236 SUNY-Cortland Win 6-2 3.88 60 4.16% Counts (Why) Mar 24th King of New York 2024
157 Hamilton Loss 5-7 -1.89 6.23% Counts Apr 20th Western NY D III Womens Conferences 2024
142 Ithaca Loss 1-9 -15.11 286 6.49% Counts (Why) Apr 20th Western NY D III Womens Conferences 2024
82 Rochester** Loss 2-11 0 127 0% Ignored (Why) Apr 20th Western NY D III Womens Conferences 2024
144 Skidmore Loss 3-9 -16.66 363 6.87% Counts (Why) Apr 27th Metro East D III College Womens Regionals 2024
142 Ithaca Loss 1-15 -19.73 286 8.31% Counts (Why) Apr 27th Metro East D III College Womens Regionals 2024
215 Vassar Win 11-4 31.16 7.62% Counts (Why) Apr 27th Metro East D III College Womens Regionals 2024
157 Hamilton Loss 5-11 -24.78 7.62% Counts (Why) Apr 28th Metro East D III College Womens Regionals 2024
215 Vassar Loss 7-8 -27.69 7.38% Counts Apr 28th Metro East D III College Womens Regionals 2024
**Blowout Eligible. Learn more about how this works here.

FAQ

The results on this page ("USAU") are the results of an implementation of the USA Ultimate Top 20 algorithm, which is used to allocate post season bids to both colleg and club ultimate teams. The data was obtained by scraping USAU's score reporting website. Learn more about the algorithm here. TL;DR, here is the rating function. Every game a team plays gets a rating equal to the opponents rating +/- the score value. With all these data points, we iterate team ratings until convergence. There is also a rule for discounting blowout games (see next FAQ)
For reference, here is handy table with frequent game scrores and the resulting game value:
"...if a team is rated more than 600 points higher than its opponent, and wins with a score that is more than twice the losing score plus one, the game is ignored for ratings purposes. However, this is only done if the winning team has at least N other results that are not being ignored, where N=5."

Translation: if a team plays a game where even earning the max point win would hurt them, they can have the game ignored provided they win by enough and have suffficient unignored results.