(5) #167 Texas-San Antonio (9-9)

1261.11 (321)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
95 Arkansas Loss 7-13 -14.49 423 4.85% Counts Feb 24th Mardi Gras XXXVI college
89 Florida State Loss 8-10 1.36 304 4.72% Counts Feb 24th Mardi Gras XXXVI college
43 Tulane Loss 7-13 1.01 297 4.85% Counts Feb 24th Mardi Gras XXXVI college
82 Mississippi State Loss 9-11 3.7 372 4.85% Counts Feb 25th Mardi Gras XXXVI college
197 Texas State Win 13-5 23.91 415 4.85% Counts (Why) Feb 25th Mardi Gras XXXVI college
370 LSU-B** Win 13-4 0 207 0% Ignored (Why) Feb 25th Mardi Gras XXXVI college
63 Iowa Loss 3-13 -10.05 349 5.45% Counts (Why) Mar 9th Centex Tier 2 2024
295 Texas A&M-B Win 13-9 -6.12 385 5.45% Counts Mar 9th Centex Tier 2 2024
207 Texas-B Win 11-10 -2.73 327 5.45% Counts Mar 9th Centex Tier 2 2024
281 Trinity Win 11-5 8.73 323 5% Counts (Why) Mar 9th Centex Tier 2 2024
228 Oklahoma State Win 15-8 18.78 423 5.45% Counts (Why) Mar 10th Centex Tier 2 2024
109 Tarleton State Loss 11-15 -10.06 181 5.45% Counts Mar 10th Centex Tier 2 2024
128 Houston Loss 10-11 0.17 281 7.27% Counts Apr 13th South Texas D I Mens Conferences 2024
38 Texas A&M Loss 8-11 20.29 295 7.27% Counts Apr 13th South Texas D I Mens Conferences 2024
295 Texas A&M-B Win 12-7 -0.33 385 7.27% Counts (Why) Apr 13th South Texas D I Mens Conferences 2024
286 Sam Houston Win 15-9 3.44 46 7.27% Counts Apr 14th South Texas D I Mens Conferences 2024
197 Texas State Loss 5-15 -57.33 415 7.27% Counts (Why) Apr 14th South Texas D I Mens Conferences 2024
207 Texas-B Win 13-9 19.3 327 7.27% Counts Apr 14th South Texas D I Mens Conferences 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.