(34) #177 Michigan Tech (9-7)

885.97 (126)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
147 Michigan-B Loss 7-15 -30.85 27 5.77% Counts (Why) Mar 26th D III Midwestern Invite
325 Purdue-B** Win 15-4 0 1 0% Ignored (Why) Mar 26th D III Midwestern Invite
251 IUPUI Win 11-6 16.3 47 5.46% Counts (Why) Mar 26th D III Midwestern Invite
282 Rose-Hulman Win 15-7 10.18 45 5.77% Counts (Why) Mar 27th D III Midwestern Invite
128 Butler Loss 11-13 -3.33 32 5.77% Counts Mar 27th D III Midwestern Invite
87 Wisconsin-Platteville Loss 7-13 -15.97 28 7.28% Counts Apr 23rd Lake Superior D III College Mens CC 2022
222 Luther Win 12-8 20.51 69 7.28% Counts Apr 23rd Lake Superior D III College Mens CC 2022
168 Carthage Win 10-9 11.2 200 7.28% Counts Apr 23rd Lake Superior D III College Mens CC 2022
312 Milwaukee School of Engineering Win 13-3 0.32 117 7.28% Counts (Why) Apr 23rd Lake Superior D III College Mens CC 2022
168 Carthage Loss 8-12 -33.23 200 7.28% Counts Apr 24th Lake Superior D III College Mens CC 2022
36 St. Olaf** Loss 3-13 0 10 0% Ignored (Why) May 7th North Central D III College Mens Regionals 2022
162 Grinnell Loss 12-13 -8.43 42 8.17% Counts May 7th North Central D III College Mens Regionals 2022
255 St. Thomas Win 13-9 10.28 202 8.17% Counts May 7th North Central D III College Mens Regionals 2022
253 St John's Win 13-8 19.07 120 8.17% Counts May 7th North Central D III College Mens Regionals 2022
168 Carthage Win 13-12 12.69 200 8.17% Counts May 8th North Central D III College Mens Regionals 2022
162 Grinnell Loss 12-13 -8.43 42 8.17% Counts May 8th North Central D III College Mens Regionals 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.