(23) #133 Arizona State (13-8)

1375.09 (183)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
82 Mississippi State Win 10-9 14.9 372 4.28% Counts Feb 24th Mardi Gras XXXVI college
99 Tennessee-Chattanooga Loss 8-9 0.8 209 4.05% Counts Feb 24th Mardi Gras XXXVI college
203 Spring Hill Win 10-7 5.4 285 4.05% Counts Feb 24th Mardi Gras XXXVI college
370 LSU-B** Win 10-4 0 207 0% Ignored (Why) Feb 24th Mardi Gras XXXVI college
286 Sam Houston Win 13-7 -1.26 46 4.28% Counts (Why) Feb 25th Mardi Gras XXXVI college
43 Tulane Loss 8-11 4.37 297 4.28% Counts Feb 25th Mardi Gras XXXVI college
46 Florida Loss 7-12 -4.91 215 4.28% Counts Feb 25th Mardi Gras XXXVI college
95 Arkansas Win 11-7 27.26 423 4.17% Counts Feb 25th Mardi Gras XXXVI college
219 Arizona Win 7-4 7.9 280 4.35% Counts (Why) Mar 30th 2024 Sinvite
334 California-Santa Barbara-B** Win 13-3 0 179 0% Ignored (Why) Mar 30th 2024 Sinvite
235 Claremont Win 8-5 3.66 292 4.73% Counts (Why) Mar 30th 2024 Sinvite
221 California-B Win 13-4 16.61 222 5.72% Counts (Why) Mar 30th 2024 Sinvite
124 San Jose State Loss 6-11 -30.28 266 5.41% Counts Mar 31st 2024 Sinvite
255 Cal State-Long Beach Win 9-6 -1.81 201 5.08% Counts Mar 31st 2024 Sinvite
219 Arizona Win 10-7 4.33 280 6.07% Counts Apr 14th Desert D I Mens Conferences 2024
247 Northern Arizona Win 12-10 -11.78 115 6.42% Counts Apr 14th Desert D I Mens Conferences 2024
71 Grand Canyon Loss 7-12 -18.25 289 6.42% Counts Apr 14th Desert D I Mens Conferences 2024
67 Stanford Loss 8-9 12.54 267 6.82% Counts Apr 27th Southwest D I College Mens Regionals 2024
144 Santa Clara Loss 6-7 -10.39 343 5.96% Counts Apr 27th Southwest D I College Mens Regionals 2024
158 UCLA-B Loss 8-11 -35.07 317 7.21% Counts Apr 28th Southwest D I College Mens Regionals 2024
230 California-Davis Win 10-5 14.65 167 6.4% Counts (Why) Apr 28th Southwest D I College Mens Regionals 2024
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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.