(9) #147 Michigan-B (13-4)

982.65 (27)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
138 Wisconsin-Milwaukee Loss 6-9 -28.27 25 7.04% Counts Mar 19th Missouri Loves Company MLC
82 Missouri Loss 1-12 -26 23 7.6% Counts (Why) Mar 19th Missouri Loves Company MLC
108 Vanderbilt Loss 10-15 -25.46 22 7.92% Counts Mar 20th Missouri Loves Company MLC
229 Wisconsin- La Crosse Win 15-10 13.46 21 7.92% Counts Mar 20th Missouri Loves Company MLC
224 Minnesota-B Loss 10-15 -63.72 26 7.92% Counts Mar 20th Missouri Loves Company MLC
177 Michigan Tech Win 15-7 46.12 126 8.39% Counts (Why) Mar 26th D III Midwestern Invite
251 IUPUI Win 15-3 21.87 47 8.39% Counts (Why) Mar 26th D III Midwestern Invite
325 Purdue-B** Win 15-3 0 1 0% Ignored (Why) Mar 26th D III Midwestern Invite
327 Indiana-B** Win 15-6 0 16 0% Ignored (Why) Mar 27th D III Midwestern Invite
168 Carthage Win 15-7 47.74 200 8.39% Counts (Why) Mar 27th D III Midwestern Invite
128 Butler Win 12-9 38.78 32 8.39% Counts Mar 27th D III Midwestern Invite
328 Michigan State-B Win 12-6 -24.04 7 9.17% Counts (Why) Apr 9th Great Lakes Dev College Mens CC 2022
296 Notre Dame-B Win 15-6 0.18 5 9.42% Counts (Why) Apr 9th Great Lakes Dev College Mens CC 2022
371 Chicago-B** Win 15-1 0 6 0% Ignored (Why) Apr 9th Great Lakes Dev College Mens CC 2022
328 Michigan State-B** Win 15-4 0 7 0% Ignored (Why) Apr 10th Great Lakes Dev College Mens CC 2022
325 Purdue-B** Win 15-3 0 1 0% Ignored (Why) Apr 10th Great Lakes Dev College Mens CC 2022
296 Notre Dame-B Win 15-6 0.18 5 9.42% Counts (Why) Apr 10th Great Lakes Dev College Mens CC 2022
**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.