(36) #254 Michigan-B (8-8)

928.81 (522)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
86 Cedarville** Loss 2-13 0 200 0% Ignored (Why) Feb 17th Commonwealth Cup Weekend 1 2024
84 Elon** Loss 5-13 0 334 0% Ignored (Why) Feb 17th Commonwealth Cup Weekend 1 2024
214 North Carolina-B Loss 9-10 1.17 386 5.52% Counts Feb 17th Commonwealth Cup Weekend 1 2024
212 West Virginia Loss 4-9 -21.51 260 4.57% Counts (Why) Feb 18th Commonwealth Cup Weekend 1 2024
395 Chicago-B** Win 11-4 0 0% Ignored (Why) Apr 13th Great Lakes Dev Mens Conferences 2024
369 Illinois-B Win 10-4 2.61 240 7.66% Counts (Why) Apr 13th Great Lakes Dev Mens Conferences 2024
363 Indiana-B Win 9-8 -33.07 428 8.29% Counts Apr 13th Great Lakes Dev Mens Conferences 2024
389 Purdue-C Win 9-7 -39.63 8.04% Counts Apr 13th Great Lakes Dev Mens Conferences 2024
357 Michigan State-B Win 15-6 14.01 530 8.77% Counts (Why) Apr 14th Great Lakes Dev Mens Conferences 2024
323 Purdue-B Win 13-8 19.02 368 8.77% Counts Apr 14th Great Lakes Dev Mens Conferences 2024
222 Ball State Loss 10-13 -23.28 238 9.84% Counts Apr 27th Great Lakes D I College Mens Regionals 2024
83 Indiana Loss 7-14 7.6 311 9.84% Counts Apr 27th Great Lakes D I College Mens Regionals 2024
37 Michigan** Loss 3-15 0 319 0% Ignored (Why) Apr 27th Great Lakes D I College Mens Regionals 2024
222 Ball State Win 11-5 70.95 238 9.03% Counts (Why) Apr 28th Great Lakes D I College Mens Regionals 2024
118 Kentucky Loss 7-15 -12.32 113 9.84% Counts (Why) Apr 28th Great Lakes D I College Mens Regionals 2024
357 Michigan State-B Win 15-6 15.91 530 9.84% Counts (Why) Apr 28th Great Lakes D I College Mens Regionals 2024
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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.