(10) #153 Rhode Island (10-9)

1026.41 (44)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
183 Connecticut College Loss 9-11 -19.82 357 4.87% Counts Feb 10th UMass Invite 2024
62 Massachusetts -B Loss 8-10 7.1 149 4.74% Counts Feb 10th UMass Invite 2024
148 Rochester Loss 8-9 -5.54 78 4.61% Counts Feb 10th UMass Invite 2024
146 Yale Loss 9-10 -4.68 8 4.87% Counts Feb 10th UMass Invite 2024
141 Bryant Loss 8-10 -10.69 141 4.74% Counts Feb 11th UMass Invite 2024
141 Bryant Win 8-5 21.06 141 4.03% Counts (Why) Feb 11th UMass Invite 2024
148 Rochester Win 9-8 6.54 78 4.61% Counts Feb 11th UMass Invite 2024
146 Yale Win 8-5 20.46 8 4.03% Counts (Why) Feb 11th UMass Invite 2024
112 Boston College Loss 7-8 2.51 45 6.12% Counts Mar 23rd Ocean State Invite
219 Central Connecticut State Win 8-3 18.64 48 5.36% Counts (Why) Mar 23rd Ocean State Invite
267 Massachusetts-Lowell Win 8-5 -2.65 64 5.7% Counts (Why) Mar 23rd Ocean State Invite
112 Boston College Loss 6-7 2.33 45 5.7% Counts Mar 24th Ocean State Invite
219 Central Connecticut State Win 8-7 -9.51 48 6.12% Counts Mar 24th Ocean State Invite
321 SUNY-Binghamton-B** Win 12-5 0 159 0% Ignored (Why) Mar 30th Northeast Classic 2024
306 Swarthmore Win 11-7 -18.01 69 7.1% Counts Mar 30th Northeast Classic 2024
247 SUNY-Geneseo Win 11-5 15.16 70 6.7% Counts (Why) Mar 30th Northeast Classic 2024
127 College of New Jersey Loss 8-9 -0.52 80 6.9% Counts Mar 31st Northeast Classic 2024
157 Ithaca Loss 9-12 -27.97 570 7.3% Counts Mar 31st Northeast Classic 2024
240 Middlebury-B Win 9-6 4.43 69 6.49% Counts Mar 31st Northeast Classic 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.