(5) #72 Duke (5-5)

1442.96 (4)

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# Opponent Result Effect % of Ranking Status Date Event
81 Appalachian State Win 13-8 43.96 9.82% Jan 25th Carolina Kickoff 2019
1 North Carolina Loss 7-13 27.18 9.82% Jan 25th Carolina Kickoff 2019
95 Richmond Loss 7-12 -78.72 9.82% Jan 26th Carolina Kickoff 2019
71 Carleton College-GoP Loss 10-13 -35.06 9.82% Jan 26th Carolina Kickoff 2019
100 Clemson Win 15-8 34.09 9.82% Jan 27th Carolina Kickoff 2019
- Portland Win 13-9 55.65 11.14% Feb 9th Stanford Open 2019
28 California Loss 6-13 -32.12 11.14% Feb 9th Stanford Open 2019
141 Cal Poly-SLO-B Win 11-2 2.99 10.22% Feb 9th Stanford Open 2019
133 Claremont Win 8-4 5.01 8.85% Feb 10th Stanford Open 2019
57 Stanford Loss 6-8 -22.62 9.56% Feb 10th Stanford Open 2019
**Blowout Eligible

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.