() #15 Rhino Slam! (12-7) NW 3

1853.54 (47)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
156 Cojones** Win 13-3 0 38 0% Ignored (Why) Jun 22nd Eugene Summer Solstice 2019
53 Ghost Train Win 13-9 -6.12 22 4.7% Counts Jun 22nd Eugene Summer Solstice 2019
166 Rip City** Win 13-4 0 75 0% Ignored (Why) Jun 22nd Eugene Summer Solstice 2019
40 Blackfish Win 13-5 7.85 40 4.7% Counts (Why) Jun 22nd Eugene Summer Solstice 2019
13 Furious George Loss 15-16 -4.87 194 4.7% Counts Jun 23rd Eugene Summer Solstice 2019
45 Red Dawn Win 15-8 4.42 24 4.7% Counts (Why) Jun 23rd Eugene Summer Solstice 2019
39 Inception Win 13-6 9.4 3 5.51% Counts (Why) Jul 13th TCT Pro Elite Challenge 2019
14 Doublewide Win 14-13 8.39 38 5.51% Counts Jul 13th TCT Pro Elite Challenge 2019
2 Truck Stop Loss 7-13 -14.09 33 5.51% Counts Jul 13th TCT Pro Elite Challenge 2019
11 Johnny Bravo Win 13-9 27.06 31 5.51% Counts Jul 14th TCT Pro Elite Challenge 2019
1 Sockeye Loss 8-12 -0.11 35 5.51% Counts Jul 14th TCT Pro Elite Challenge 2019
5 Revolver Loss 7-13 -17.59 26 5.51% Counts Jul 14th TCT Pro Elite Challenge 2019
3 PoNY Loss 6-13 -16.66 38 5.51% Counts (Why) Jul 14th TCT Pro Elite Challenge 2019
63 Guerrilla Win 14-12 -29.13 202 7.2% Counts Aug 17th TCT Elite Select Challenge 2019
20 Yogosbo Win 15-9 30.64 20 7.2% Counts Aug 17th TCT Elite Select Challenge 2019
18 Patrol Win 12-8 25.28 57 7.2% Counts Aug 17th TCT Elite Select Challenge 2019
9 SoCal Condors Loss 7-10 -19.93 135 6.81% Counts Aug 18th TCT Elite Select Challenge 2019
30 Black Market I Win 11-7 11.21 0 7.01% Counts Aug 18th TCT Elite Select Challenge 2019
12 Pittsburgh Temper Loss 10-12 -15.65 36 7.2% Counts Aug 18th TCT Elite Select Challenge 2019
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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.