(5) #280 Western Michigan (6-12)

828.64 (326)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
362 Concordia-Wisconsin Win 13-5 14.56 431 6.5% Counts (Why) Mar 16th Grand Rapids College Invite
37 Michigan** Loss 2-13 0 319 0% Ignored (Why) Mar 16th Grand Rapids College Invite
357 Michigan State-B Win 13-7 14.14 530 6.5% Counts (Why) Mar 16th Grand Rapids College Invite
340 DePaul Win 7-3 16.16 241 4.71% Counts (Why) Mar 17th Grand Rapids College Invite
135 Grand Valley Loss 4-13 -3.99 183 6.5% Counts (Why) Mar 17th Grand Rapids College Invite
123 Oberlin Loss 5-12 -2.12 244 6.24% Counts (Why) Mar 17th Grand Rapids College Invite
357 Michigan State-B Win 12-6 16.18 530 6.7% Counts (Why) Mar 22nd Butler Spring Fling
220 Hillsdale Loss 6-9 -12.83 421 6.12% Counts Mar 23rd Butler Spring Fling
236 Loyola-Chicago Loss 1-13 -32.36 445 6.88% Counts (Why) Mar 23rd Butler Spring Fling
173 Xavier Loss 6-13 -14.43 260 6.88% Counts (Why) Mar 23rd Butler Spring Fling
151 Grace Loss 5-10 -5.92 289 6.12% Counts Mar 24th Butler Spring Fling
323 Purdue-B Win 11-6 24.29 368 6.51% Counts (Why) Mar 24th Butler Spring Fling
301 Rose-Hulman Win 11-7 25.32 447 6.7% Counts Mar 24th Butler Spring Fling
223 Eastern Michigan Loss 6-9 -16.26 506 7.27% Counts Apr 13th Michigan D I Mens Conferences 2024
135 Grand Valley Loss 0-13 -5.13 183 8.19% Counts (Why) Apr 13th Michigan D I Mens Conferences 2024
37 Michigan** Loss 5-13 0 319 0% Ignored (Why) Apr 13th Michigan D I Mens Conferences 2024
49 Michigan State** Loss 2-6 0 313 0% Ignored (Why) Apr 13th Michigan D I Mens Conferences 2024
223 Eastern Michigan Loss 9-13 -18.48 506 8.19% Counts Apr 14th Michigan D I Mens Conferences 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.