(1) #139 Auburn (5-15)

640.3 (54)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
50 Carnegie Mellon** Loss 3-15 0 56 0% Ignored (Why) Feb 26th Commonwealth Cup Weekend 2
26 Brown** Loss 2-15 0 63 0% Ignored (Why) Feb 26th Commonwealth Cup Weekend 2
48 Penn State Loss 5-11 1.71 55 4.64% Counts (Why) Feb 26th Commonwealth Cup Weekend 2
100 Case Western Reserve Loss 9-13 -8.14 50 5.05% Counts Feb 27th Commonwealth Cup Weekend 2
48 Penn State Loss 4-7 5.56 55 3.84% Counts Feb 27th Commonwealth Cup Weekend 2
69 Charleston Loss 5-11 -7.63 47 5.51% Counts (Why) Mar 19th College Southerns XX
23 Carleton College-Eclipse** Loss 5-13 0 51 0% Ignored (Why) Mar 19th College Southerns XX
183 Florida-B Win 11-3 17.62 56 5.51% Counts (Why) Mar 19th College Southerns XX
116 Wisconsin-Eau Claire Win 10-7 31.35 29 5.68% Counts Mar 20th College Southerns XX
23 Carleton College-Eclipse** Loss 1-15 0 51 0% Ignored (Why) Mar 20th College Southerns XX
69 Charleston Loss 3-11 -7.63 47 5.51% Counts (Why) Mar 20th College Southerns XX
166 LSU Loss 10-11 -26.76 55 8.02% Counts Apr 23rd Gulf Coast D I College Womens CC 2022
127 Jacksonville State Win 8-7 14.54 55 7.13% Counts Apr 23rd Gulf Coast D I College Womens CC 2022
218 Vanderbilt Win 15-2 0.3 53 8.02% Counts (Why) Apr 23rd Gulf Coast D I College Womens CC 2022
86 Alabama Loss 10-13 2.54 57 8.02% Counts Apr 24th Gulf Coast D I College Womens CC 2022
123 Tulane Loss 7-12 -37.85 57 8.02% Counts Apr 24th Gulf Coast D I College Womens CC 2022
47 Florida** Loss 5-12 0 50 0% Ignored (Why) Apr 30th Southeast D I College Womens Regionals 2022
166 LSU Win 13-7 34.88 55 8.5% Counts (Why) Apr 30th Southeast D I College Womens Regionals 2022
81 Emory Loss 9-11 11.78 65 8.5% Counts Apr 30th Southeast D I College Womens Regionals 2022
110 Tennessee-Chattanooga Loss 6-11 -33.07 57 8.04% Counts Apr 30th Southeast D I College Womens Regionals 2022
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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.