(7) #121 Iowa State (9-10)

1155.06 (41)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
325 Carleton College-Karls-C** Win 13-0 0 46 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
195 Grinnell Win 9-8 -10.3 116 5.3% Counts Mar 2nd Midwest Throwdown 2024
95 Wisconsin-Eau Claire Loss 9-11 -9.16 30 5.61% Counts Mar 2nd Midwest Throwdown 2024
317 Washington University-B** Win 13-4 0 156 0% Ignored (Why) Mar 2nd Midwest Throwdown 2024
78 Carleton College-CHOP Win 11-8 33.23 7 5.61% Counts Mar 3rd Midwest Throwdown 2024
83 Northwestern Loss 7-10 -11.72 140 5.3% Counts Mar 3rd Midwest Throwdown 2024
170 Minnesota-Duluth Win 10-9 -4.71 109 5.61% Counts Mar 3rd Midwest Throwdown 2024
98 Dartmouth Win 8-6 22.33 16 5.4% Counts Mar 16th College Mens Centex Tier 1
40 Illinois Loss 9-11 11.78 18 6.29% Counts Mar 16th College Mens Centex Tier 1
31 Middlebury Loss 9-13 5.61 9 6.29% Counts Mar 16th College Mens Centex Tier 1
14 Texas** Loss 3-13 0 30 0% Ignored (Why) Mar 16th College Mens Centex Tier 1
128 Colorado College Loss 7-12 -36.24 232 6.29% Counts Mar 17th College Mens Centex Tier 1
53 Colorado State Win 11-10 29.58 118 6.29% Counts Mar 17th College Mens Centex Tier 1
91 Indiana Loss 8-11 -18.99 100 7.06% Counts Mar 30th Huck Finn 2024
209 Oklahoma Win 11-6 12.58 77 6.68% Counts (Why) Mar 30th Huck Finn 2024
105 Mississippi State Loss 9-10 -5.27 61 7.06% Counts Mar 30th Huck Finn 2024
132 Arkansas Loss 9-10 -12.78 34 7.06% Counts Mar 31st Huck Finn 2024
82 Central Florida Loss 7-12 -25.71 52 7.06% Counts Mar 31st Huck Finn 2024
204 Ohio Win 13-2 19.35 15 7.06% Counts (Why) Mar 31st Huck Finn 2024
**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.