(22) #182 Knox (9-9)

609.1 (65)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
102 Iowa** Loss 4-13 0 40 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
127 Wisconsin-Eau Claire Loss 2-9 -10.84 27 6.06% Counts (Why) Mar 2nd Midwest Throwdown 2024
177 Missouri State Loss 6-7 -3.3 143 6.06% Counts Mar 2nd Midwest Throwdown 2024
231 Wisconsin-B Win 7-6 -22.19 59 6.06% Counts Mar 3rd Midwest Throwdown 2024
127 Wisconsin-Eau Claire Loss 4-8 -8.21 27 5.82% Counts Mar 3rd Midwest Throwdown 2024
129 Illinois Loss 7-8 27.11 50 8.2% Counts Mar 30th Illinois Invite 2024
237 Northwestern-B Win 13-0 1.29 48 9.23% Counts (Why) Mar 30th Illinois Invite 2024
190 Michigan-B Win 9-2 44.98 7 7.64% Counts (Why) Mar 30th Illinois Invite 2024
195 Washington University-B Win 7-2 36.05 109 6.7% Counts (Why) Mar 30th Illinois Invite 2024
129 Illinois Loss 5-12 -16.68 50 8.86% Counts (Why) Mar 31st Illinois Invite 2024
190 Michigan-B Win 9-8 6.61 7 8.73% Counts Mar 31st Illinois Invite 2024
100 Davenport** Loss 1-9 0 25 0% Ignored (Why) Apr 13th Great Lakes D III Womens Conferences 2024
246 Kalamazoo** Win 9-1 0 0% Ignored (Why) Apr 13th Great Lakes D III Womens Conferences 2024
247 North Park** Win 8-2 0 0% Ignored (Why) Apr 13th Great Lakes D III Womens Conferences 2024
167 Wheaton (Illinois) Loss 4-8 -34.77 20 8.23% Counts Apr 13th Great Lakes D III Womens Conferences 2024
224 Butler Win 9-7 -11.52 343 9.51% Counts Apr 14th Great Lakes D III Womens Conferences 2024
224 Butler Win 8-6 -8.64 343 8.89% Counts Apr 14th Great Lakes D III Womens Conferences 2024
100 Davenport** Loss 3-12 0 25 0% Ignored (Why) Apr 14th Great Lakes D III Womens Conferences 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.