(12) #364 Rensselaer Polytech (1-17)

432.24 (415)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
139 Army** Loss 4-10 0 188 0% Ignored (Why) Mar 16th Free Tournament
130 Penn State-B** Loss 5-13 0 13 0% Ignored (Why) Mar 16th Free Tournament
171 Scranton** Loss 3-13 0 475 0% Ignored (Why) Mar 16th Free Tournament
126 Towson Loss 7-12 35.96 272 7.61% Counts Mar 16th Free Tournament
171 Scranton** Loss 1-15 0 475 0% Ignored (Why) Mar 17th Free Tournament
170 Villanova Loss 7-11 28.24 293 7.41% Counts Mar 17th Free Tournament
315 Vermont-C Loss 4-13 -34.73 314 8.55% Counts (Why) Mar 30th Northeast Classic 2024
267 SUNY-Geneseo Loss 6-12 -12.71 234 8.32% Counts Mar 30th Northeast Classic 2024
318 Swarthmore Loss 8-13 -25.5 331 8.55% Counts Mar 30th Northeast Classic 2024
378 SUNY-Buffalo-B Loss 6-11 -59.56 276 8.08% Counts Mar 31st Northeast Classic 2024
139 Army** Loss 5-13 0 188 0% Ignored (Why) Apr 13th Hudson Valley D III Mens Conferences 2024
260 Hartford Loss 9-13 6.24 9.59% Counts Apr 13th Hudson Valley D III Mens Conferences 2024
199 Connecticut College** Loss 4-13 0 237 0% Ignored (Why) Apr 14th Hudson Valley D III Mens Conferences 2024
245 Skidmore Loss 4-15 -5.75 274 9.59% Counts (Why) Apr 14th Hudson Valley D III Mens Conferences 2024
187 College of New Jersey Loss 7-14 17.89 19 10.77% Counts Apr 27th Metro East D III College Mens Regionals 2024
199 Connecticut College** Loss 1-15 0 237 0% Ignored (Why) Apr 27th Metro East D III College Mens Regionals 2024
252 Hamilton Loss 9-15 -2.04 10.77% Counts Apr 27th Metro East D III College Mens Regionals 2024
376 SUNY-Fredonia Win 15-8 53.27 35 10.77% Counts (Why) Apr 28th Metro East D III College Mens 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.