(11) #127 Jacksonville State (10-11)

760.32 (49)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
87 Alabama Loss 3-11 -14.03 48 4.39% Counts (Why) Feb 26th TOTS
42 Tennessee** Loss 1-13 0 41 0% Ignored (Why) Feb 26th TOTS
217 Vanderbilt Win 7-3 -2.27 53 3.47% Counts (Why) Feb 26th TOTS
69 Union (Tennessee) Loss 3-13 -10.48 44 4.78% Counts (Why) Feb 26th TOTS
223 Purdue-B Win 12-6 -6.2 66 4.66% Counts (Why) Feb 27th TOTS
237 Emory-B** Win 12-0 0 32 0% Ignored (Why) Feb 27th TOTS
217 Vanderbilt Win 10-8 -19.56 53 4.66% Counts Feb 27th TOTS
124 Tulane Loss 3-4 -3.43 53 3.26% Counts Mar 12th Tally Classic XVI
91 South Carolina Win 5-2 29.65 17 3.26% Counts (Why) Mar 12th Tally Classic XVI
215 Notre Dame-B** Win 10-2 0 123 0% Ignored (Why) Mar 12th Tally Classic XVI
47 Florida Loss 7-10 10.12 27 5.08% Counts Mar 12th Tally Classic XVI
76 Notre Dame Loss 8-11 -1.02 11 5.37% Counts Mar 13th Tally Classic XVI
197 Florida Tech Win 8-5 -0.07 62 4.44% Counts (Why) Mar 13th Tally Classic XVI
152 Harvard Win 11-7 16.99 96 5.23% Counts Mar 13th Tally Classic XVI
140 Auburn Loss 7-8 -13.84 49 6.75% Counts Apr 23rd Gulf Coast D I College Womens CC 2022
163 LSU Win 12-6 26.52 55 7.39% Counts (Why) Apr 23rd Gulf Coast D I College Womens CC 2022
87 Alabama Loss 7-15 -25.11 48 7.59% Counts (Why) Apr 24th Gulf Coast D I College Womens CC 2022
124 Tulane Win 9-8 11.47 53 7.18% Counts Apr 24th Gulf Coast D I College Womens CC 2022
87 Alabama Loss 9-10 14.83 48 8.05% Counts Apr 30th Southeast D I College Womens Regionals 2022
51 Central Florida Loss 8-12 7.49 40 8.05% Counts Apr 30th Southeast D I College Womens Regionals 2022
124 Tulane Loss 5-7 -20.83 53 6.39% Counts Apr 30th Southeast D I College Womens 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.