() #89 Tempo (3-17)

234.07 (1)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
69 Trash. Loss 3-13 -13.52 2 7.06% Counts (Why) Jun 22nd Eugene Summer Solstice 2019
59 Portland Ivy Loss 3-13 -0.79 4 7.06% Counts (Why) Jun 22nd Eugene Summer Solstice 2019
47 Korra** Loss 3-9 0 4 0% Ignored (Why) Jun 22nd Eugene Summer Solstice 2019
36 Seattle Soul** Loss 1-13 0 4 0% Ignored (Why) Jun 22nd Eugene Summer Solstice 2019
58 Venom Loss 5-9 3.94 3 6.06% Counts Jun 23rd Eugene Summer Solstice 2019
75 Koi Loss 6-11 -16.26 1 6.68% Counts Jun 23rd Eugene Summer Solstice 2019
85 Seven Devils Loss 5-7 -16.03 3 5.61% Counts Jun 23rd Eugene Summer Solstice 2019
93 Ultraviolet Loss 7-9 -33.58 2 8.65% Counts Jul 27th The Friend Zone
93 Ultraviolet Win 6-3 32.71 2 6.49% Counts (Why) Jul 27th The Friend Zone
76 Viva Win 9-4 76.59 3 7.8% Counts (Why) Jul 27th The Friend Zone
76 Viva Loss 3-9 -24.9 3 7.8% Counts (Why) Jul 27th The Friend Zone
93 Ultraviolet Loss 6-8 -48.56 2 11.44% Counts Sep 8th Nor Cal Womens Club Sectional Championship 2019
32 FAB** Loss 1-13 0 7 0% Ignored (Why) Sep 8th Nor Cal Womens Club Sectional Championship 2019
- 2nd Wave Loss 3-8 -9.07 2 10.37% Counts (Why) Sep 8th Nor Cal Womens Club Sectional Championship 2019
22 LOL** Loss 1-13 0 8 0% Ignored (Why) Sep 8th Nor Cal Womens Club Sectional Championship 2019
32 FAB** Loss 3-13 0 7 0% Ignored (Why) Sep 21st Southwest Club Womens Regional Championship 2019
42 Rampage** Loss 5-13 0 1 0% Ignored (Why) Sep 21st Southwest Club Womens Regional Championship 2019
22 LOL** Loss 3-13 0 8 0% Ignored (Why) Sep 21st Southwest Club Womens Regional Championship 2019
10 Nightlock** Loss 1-13 0 7 0% Ignored (Why) Sep 21st Southwest Club Womens Regional Championship 2019
93 Ultraviolet Win 11-8 51.1 2 14.97% Counts Sep 22nd Southwest Club Womens Regional Championship 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.