() #111 Washington University (5-5)

1313.46 (69)

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# Opponent Result Effect % of Ranking Status Date Event
50 Stanford Loss 9-10 19.86 9.27% Feb 9th Stanford Open 2019
254 Cal Poly-Pomona Win 10-8 -20.89 9.03% Feb 9th Stanford Open 2019
125 Colorado School of Mines Win 11-7 42.83 9.03% Feb 9th Stanford Open 2019
21 California Loss 3-7 -5.05 6.73% Feb 10th Stanford Open 2019
37 Illinois Loss 2-11 -28.21 12.75% Mar 30th Huck Finn XXIII
79 Tulane Loss 2-7 -51.23 10.08% Mar 30th Huck Finn XXIII
92 John Brown Loss 6-7 -7.89 11.49% Mar 31st Huck Finn XXIII
164 Arizona State Win 6-3 35.57 9.56% Mar 31st Huck Finn XXIII
152 Arkansas Win 6-5 -4.17 10.57% Mar 31st Huck Finn XXIII
106 Illinois State Win 7-6 18.03 11.49% Mar 31st Huck Finn XXIII
**Blowout Eligible


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.