(3) #315 Knox (6-14)

257.91 (15)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
103 John Brown** Loss 5-12 0 5 0% Ignored (Why) Mar 5th Midwest Throwdown 2022
264 Wisconsin-B Loss 6-7 5.61 3 3.8% Counts Mar 5th Midwest Throwdown 2022
319 Northwestern-B Win 7-5 11.67 9 3.65% Counts Mar 5th Midwest Throwdown 2022
227 Macalester College Loss 5-10 -6.48 10 4.09% Counts Mar 6th Midwest Throwdown 2022
319 Northwestern-B Win 8-6 11.5 9 3.95% Counts Mar 6th Midwest Throwdown 2022
221 Loyola-Chicago Loss 2-9 -7.88 6 4.52% Counts (Why) Mar 26th Illinois Invite
230 North Park Loss 6-8 5.32 17 4.69% Counts Mar 26th Illinois Invite
334 Bradley Win 7-6 -0.44 15 4.52% Counts Mar 26th Illinois Invite
286 Notre Dame-B Win 12-9 27.91 11 5.47% Counts Mar 27th Illinois Invite
340 Illinois-B Win 9-7 5.18 12 5.02% Counts Mar 27th Illinois Invite
286 Notre Dame-B Loss 8-13 -20.78 11 5.47% Counts Mar 27th Illinois Invite
230 North Park Loss 3-13 -14.17 17 6.89% Counts (Why) Apr 23rd Illinois D III College Mens CC 2022
141 Wheaton (Illinois)** Loss 4-13 0 29 0% Ignored (Why) Apr 23rd Illinois D III College Mens CC 2022
334 Bradley Win 13-5 34.46 15 6.89% Counts (Why) Apr 23rd Illinois D III College Mens CC 2022
230 North Park Loss 6-9 -0.66 17 6.12% Counts Apr 24th Illinois D III College Mens CC 2022
334 Bradley Loss 6-7 -15.68 15 5.7% Counts Apr 24th Illinois D III College Mens CC 2022
182 Kalamazoo Loss 4-15 -3.11 27 7.3% Counts (Why) Apr 30th Great Lakes D III College Mens Regionals 2022
230 North Park Loss 6-14 -15.08 17 7.3% Counts (Why) Apr 30th Great Lakes D III College Mens Regionals 2022
182 Kalamazoo Loss 4-15 -3.11 27 7.3% Counts (Why) May 1st Great Lakes D III College Mens Regionals 2022
230 North Park Loss 4-13 -15.08 17 7.3% Counts (Why) May 1st Great Lakes 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.