(9) #102 Lehigh (9-12)

1276.26 (75)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
40 Haverford/Bryn Mawr Win 7-5 41.75 181 4.46% Counts Feb 22nd Bring The Huckus 2025
90 Ithaca Loss 7-8 -1.32 92 4.98% Counts Feb 22nd Bring The Huckus 2025
47 Wesleyan Loss 2-12 -3.14 10 5.38% Counts (Why) Feb 22nd Bring The Huckus 2025
143 SUNY-Geneseo Win 9-3 15.75 123 4.64% Counts (Why) Feb 22nd Bring The Huckus 2025
40 Haverford/Bryn Mawr Loss 4-10 -1.69 181 4.9% Counts (Why) Feb 23rd Bring The Huckus 2025
117 Swarthmore Win 8-7 2.3 166 4.98% Counts Feb 23rd Bring The Huckus 2025
143 SUNY-Geneseo Win 10-7 6.36 123 5.3% Counts Feb 23rd Bring The Huckus 2025
149 Delaware Loss 3-4 -15.91 38 3.61% Counts Mar 1st Cherry Blossom Classic 2025
172 George Mason Win 5-3 -2.19 43 3.85% Counts (Why) Mar 1st Cherry Blossom Classic 2025
100 SUNY-Buffalo Loss 5-6 -4.01 46 4.52% Counts Mar 1st Cherry Blossom Classic 2025
111 SUNY-Binghamton Win 6-5 3.95 49 4.52% Counts Mar 1st Cherry Blossom Classic 2025
134 Catholic Loss 2-7 -36.82 77 4.31% Counts (Why) Mar 2nd Cherry Blossom Classic 2025
210 Johns Hopkins Win 9-4 -9.17 51 4.91% Counts (Why) Mar 2nd Cherry Blossom Classic 2025
168 Miami (Florida) Win 9-5 3.38 37 5.1% Counts (Why) Mar 2nd Cherry Blossom Classic 2025
47 Wesleyan Loss 6-9 8.99 10 6.65% Counts Mar 29th East Coast Invite 2025
106 Temple Loss 7-9 -21.62 148 6.87% Counts Mar 29th East Coast Invite 2025
78 Mount Holyoke Loss 6-10 -20.74 6.87% Counts Mar 29th East Coast Invite 2025
24 Minnesota** Loss 2-15 0 210 0% Ignored (Why) Mar 29th East Coast Invite 2025
76 Columbia Loss 7-9 -3.52 8 6.87% Counts Mar 30th East Coast Invite 2025
119 Yale Win 12-6 38.05 813 7.28% Counts (Why) Mar 30th East Coast Invite 2025
27 Northeastern** Loss 1-8 0 184 0% Ignored (Why) Mar 30th East Coast Invite 2025
**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.