(23) #167 Indiana (2-4)

234 (734)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
66 St. Olaf** Loss 1-11 0 306 0% Ignored (Why) Mar 4th Midwest Throwdown 2023
148 Truman State Loss 4-8 -76.09 446 18.49% Counts Mar 4th Midwest Throwdown 2023
185 Northwestern-B Win 11-2 86.45 1209 21.35% Counts (Why) Mar 4th Midwest Throwdown 2023
119 Purdue Loss 2-11 -16.41 354 21.35% Counts (Why) Mar 4th Midwest Throwdown 2023
170 Wisconsin-Milwaukee Win 7-5 67.06 728 18.49% Counts Mar 5th Midwest Throwdown 2023
134 Washington University-B Loss 3-10 -59.91 563 20.32% Counts (Why) Mar 5th Midwest Throwdown 2023
**Blowout Eligible. Learn more about how this works here.


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.