(20) #26 LIT Ultimate (11-7)

1492.01 (312)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
22 Donuts Loss 10-11 -6.12 312 5.69% Counts Jun 11th Bay Area Ultimate Classic
52 Firefly Loss 9-13 -38.02 312 5.69% Counts Jun 11th Bay Area Ultimate Classic
171 Moonlight Ultimate** Win 15-6 0 296 0% Ignored (Why) Jun 11th Bay Area Ultimate Classic
45 Mango Win 13-12 -2.76 312 5.69% Counts Jun 12th Bay Area Ultimate Classic
22 Donuts Loss 8-12 -25.2 312 5.69% Counts Jun 12th Bay Area Ultimate Classic
52 Firefly Loss 7-11 -39.78 312 5.54% Counts Jun 12th Bay Area Ultimate Classic
70 Cutthroat Win 11-8 0.69 312 6.33% Counts Jun 25th Truckee River Ultimate Cooldown TRUC
48 Hive Win 13-8 20.83 312 6.33% Counts Jun 25th Truckee River Ultimate Cooldown TRUC
43 Sacramento Tower Ultimate Win 13-8 24.2 312 6.33% Counts Jun 25th Truckee River Ultimate Cooldown TRUC
15 Classy Win 9-6 32.15 312 5.63% Counts Jun 26th Truckee River Ultimate Cooldown TRUC
117 DR** Win 13-5 0 312 0% Ignored (Why) Jun 26th Truckee River Ultimate Cooldown TRUC
43 Sacramento Tower Ultimate Win 13-8 24.2 312 6.33% Counts Jun 26th Truckee River Ultimate Cooldown TRUC
62 Pegasus Win 13-7 20.36 312 7.05% Counts (Why) Jul 9th Revolution
15 Classy Loss 6-9 -19.9 312 6.26% Counts Jul 9th Revolution
52 Firefly Win 11-5 26.87 312 6.47% Counts (Why) Jul 9th Revolution
45 Mango Loss 10-11 -22.42 312 7.05% Counts Jul 10th Revolution
22 Donuts Win 10-8 21.08 312 6.86% Counts Jul 10th Revolution
35 Lights Out Loss 10-11 -15.56 312 7.05% Counts Jul 10th Revolution
**Blowout Eligible. Learn more about how this works here.

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.