(17) #305 SUNY-Binghamton-B (2-7)

431.96 (45)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
227 Temple-B Loss 8-11 0.22 20 9.79% Counts Feb 25th Bring The Huckus1
224 Haverford Loss 6-12 -20.82 23 9.53% Counts Feb 25th Bring The Huckus1
239 Stevens Tech Loss 6-12 -26.29 64 9.53% Counts Feb 25th Bring The Huckus1
357 SUNY-Albany-B Win 13-2 5.91 230 9.79% Counts (Why) Feb 25th Bring The Huckus1
223 SUNY-Stony Brook Win 11-9 92.86 47 12.34% Counts Mar 25th Strong Island 2023
239 Stevens Tech Loss 8-12 -15.67 64 12.34% Counts Mar 25th Strong Island 2023
205 SUNY-Cortland Loss 6-12 -11.31 122 12.01% Counts Mar 25th Strong Island 2023
190 MIT Loss 4-13 -5.68 27 12.34% Counts (Why) Mar 26th Strong Island 2023
208 Rhode Island Loss 6-15 -17.83 10 12.34% Counts (Why) Mar 26th Strong Island 2023
**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.