(45) #359 Lehigh-B (2-3)

-243.24 (79)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
345 Princeton-B Loss 12-13 22.09 71 20.11% Counts Feb 22nd Bring The Huckus 10 2020
371 MIT-B Win 13-3 22.62 61 20.11% Counts (Why) Feb 22nd Bring The Huckus 10 2020
310 Sacred Heart Loss 6-12 -16.99 58 19.57% Counts Feb 22nd Bring The Huckus 10 2020
369 Yale-B Win 13-4 43.72 133 20.11% Counts (Why) Feb 22nd Bring The Huckus 10 2020
345 Princeton-B Loss 8-13 -71.33 71 20.11% Counts Feb 23rd Bring The Huckus 10 2020
**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.