(9) #138 RIT (10-10)

1092.92 (21)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
122 Boston University Win 11-7 22.53 100 3.99% Counts Jan 25th Mid Atlantic Warm Up 2025
60 Michigan State Loss 3-13 -8.84 88 4.1% Counts (Why) Jan 25th Mid Atlantic Warm Up 2025
78 Richmond Loss 5-13 -14.76 68 4.1% Counts (Why) Jan 25th Mid Atlantic Warm Up 2025
272 Virginia Commonwealth Win 10-3 0.68 44 3.58% Counts (Why) Jan 25th Mid Atlantic Warm Up 2025
206 Christopher Newport Win 13-10 0.58 84 4.1% Counts Jan 26th Mid Atlantic Warm Up 2025
66 Dartmouth Loss 4-15 -10.3 18 4.1% Counts (Why) Jan 26th Mid Atlantic Warm Up 2025
101 Yale Loss 8-11 -8.39 46 4.1% Counts Jan 26th Mid Atlantic Warm Up 2025
71 Case Western Reserve Loss 9-11 3.65 41 5.48% Counts Mar 1st Oak Creek Challenge 2025
177 Towson Loss 7-9 -23.64 47 5.03% Counts Mar 1st Oak Creek Challenge 2025
336 SUNY-Cortland** Win 10-3 0 243 0% Ignored (Why) Mar 1st Oak Creek Challenge 2025
56 Cornell Loss 7-13 -7.33 82 5.48% Counts Mar 2nd Oak Creek Challenge 2025
177 Towson Win 10-5 20.79 47 4.87% Counts (Why) Mar 2nd Oak Creek Challenge 2025
116 West Chester Loss 10-11 -1.49 101 5.48% Counts Mar 2nd Oak Creek Challenge 2025
247 George Washington Win 15-4 9.26 38 6.51% Counts (Why) Mar 22nd Atlantic Coast Open 2025
113 Lehigh Loss 7-13 -31.08 4 6.51% Counts Mar 22nd Atlantic Coast Open 2025
43 Virginia Tech Loss 9-13 7.02 19 6.51% Counts Mar 22nd Atlantic Coast Open 2025
255 Wake Forest Win 15-3 6.52 9 6.51% Counts (Why) Mar 22nd Atlantic Coast Open 2025
180 American Win 15-12 7.89 31 6.51% Counts Mar 23rd Atlantic Coast Open 2025
184 East Carolina Win 15-9 21.75 0 6.51% Counts Mar 23rd Atlantic Coast Open 2025
170 Massachusetts -B Win 15-13 5.65 70 6.51% Counts Mar 23rd Atlantic Coast Open 2025
**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.