(8) #155 FLI (8-13)

687.92 (65)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
207 Face Off Win 11-7 6.83 65 4.18% Counts Jul 17th Boston Invite
241 Sorted Beans Win 11-4 0.66 70 3.94% Counts (Why) Jul 17th Boston Invite
254 Pink Pear** Win 11-3 0 65 0% Ignored (Why) Jul 17th Boston Invite
188 Unlimited Swipes Win 11-2 18.17 62 3.94% Counts (Why) Jul 17th Boston Invite
101 Funk Loss 7-9 -0.04 62 3.94% Counts Jul 17th Boston Invite
182 Lampshade Loss 8-10 -16.77 61 4.18% Counts Jul 18th Boston Invite
188 Unlimited Swipes Loss 8-9 -11.94 62 4.06% Counts Jul 18th Boston Invite
61 8 Bit Heroes Loss 3-8 -6.61 47 3.92% Counts (Why) Aug 7th Philly Open 2021
200 District Cocktails Loss 6-7 -16.89 57 4.17% Counts Aug 7th Philly Open 2021
150 Philly Twist Win 7-6 6.5 58 4.17% Counts Aug 7th Philly Open 2021
54 Loco Loss 3-11 -3.75 59 4.62% Counts (Why) Aug 7th Philly Open 2021
101 Funk Loss 5-6 6.11 62 3.83% Counts Aug 7th Philly Open 2021
118 Eat Lightning Loss 12-15 -6.45 66 5.04% Counts Aug 8th Philly Open 2021
153 PS Win 15-6 31.95 59 5.04% Counts (Why) Aug 8th Philly Open 2021
181 Nautilus Win 13-9 21.38 68 6.58% Counts Sep 11th Metro New York Mixed Club Sectional Championship 2021
118 Eat Lightning Loss 7-11 -19.7 66 6.4% Counts Sep 11th Metro New York Mixed Club Sectional Championship 2021
50 Deadweight Loss 7-11 5.24 68 6.4% Counts Sep 11th Metro New York Mixed Club Sectional Championship 2021
36 XIST Loss 7-11 16.49 109 6.4% Counts Sep 11th Metro New York Mixed Club Sectional Championship 2021
118 Eat Lightning Loss 5-11 -27.05 66 6.04% Counts (Why) Sep 12th Metro New York Mixed Club Sectional Championship 2021
114 Heat Wave Loss 9-12 -10.46 59 6.58% Counts Sep 12th Metro New York Mixed Club Sectional Championship 2021
188 Unlimited Swipes Win 11-9 6.49 62 6.58% Counts Sep 12th Metro New York Mixed Club Sectional Championship 2021
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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.