(1) #155 Minnesota-Duluth (4-3)

1148.05 (468)

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# Opponent Result Effect % of Ranking Status Date Event
81 Purdue Win 10-9 111.01 15.32% Mar 3rd Midwest Throwdown 2018
238 Washington University-B Win 12-4 3.8 14.7% Mar 3rd Midwest Throwdown 2018
198 Marquette Win 8-4 45.13 12.17% Mar 3rd Midwest Throwdown 2018
106 St Benedict Loss 4-9 -40.06 12.67% Mar 3rd Midwest Throwdown 2018
144 Texas-Dallas Loss 7-10 -52.65 14.49% Mar 4th Midwest Throwdown 2018
151 Grinnell College Loss 9-15 -87.46 15.32% Mar 4th Midwest Throwdown 2018
156 Missouri S&T Win 11-10 21.61 15.32% Mar 4th Midwest Throwdown 2018
**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.