(6) #163 Xavier (15-6)

973.48 (32)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
284 Pacific Lutheran Win 13-4 2.73 7 4.54% Counts (Why) Feb 10th DIII Grand Prix
80 Lewis & Clark Win 10-8 29.11 16 4.42% Counts Feb 10th DIII Grand Prix
59 Whitman Loss 4-13 -6.51 10 4.54% Counts (Why) Feb 10th DIII Grand Prix
279 Whitworth Win 13-1 5.06 3 4.54% Counts (Why) Feb 10th DIII Grand Prix
234 Claremont Loss 7-9 -23.92 9 4.17% Counts Feb 11th DIII Grand Prix
190 Portland Win 10-8 6.99 11 4.42% Counts Feb 11th DIII Grand Prix
286 Reed Win 12-8 -5.25 9 4.54% Counts Feb 11th DIII Grand Prix
242 Butler Win 13-6 16.85 68 5.4% Counts (Why) Mar 2nd FCS D III Tune Up 2024
231 Christopher Newport Win 13-8 13.44 59 5.4% Counts Mar 2nd FCS D III Tune Up 2024
125 Davidson Loss 6-11 -20.13 6 5.11% Counts Mar 2nd FCS D III Tune Up 2024
137 Union (Tennessee) Loss 5-13 -27.6 16 5.4% Counts (Why) Mar 2nd FCS D III Tune Up 2024
99 Elon Loss 10-13 -3.38 23 5.4% Counts Mar 3rd FCS D III Tune Up 2024
118 Michigan Tech Loss 8-13 -16.91 3 5.4% Counts Mar 3rd FCS D III Tune Up 2024
179 Missouri S&T Win 13-7 27.89 36 5.4% Counts (Why) Mar 3rd FCS D III Tune Up 2024
242 Butler Win 12-10 -4.6 68 6.43% Counts Mar 23rd Butler Spring Fling
364 Michigan State-B** Win 13-5 0 77 0% Ignored (Why) Mar 23rd Butler Spring Fling
319 Purdue-B** Win 13-5 0 125 0% Ignored (Why) Mar 23rd Butler Spring Fling
275 Western Michigan Win 13-6 8.89 60 6.43% Counts (Why) Mar 23rd Butler Spring Fling
249 Hillsdale Win 9-7 -4.07 95 5.9% Counts Mar 24th Butler Spring Fling
318 Rose-Hulman Win 11-6 -10.33 77 6.08% Counts (Why) Mar 24th Butler Spring Fling
262 Loyola-Chicago Win 13-2 11.85 100 6.43% Counts (Why) Mar 24th Butler Spring Fling
**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.