() #46 Brooklyn Book Club (15-6)

1141.1 (26)

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# Opponent Result Effect % of Ranking Status Date Event
100 Roc Paper Scissors** Win 15-0 0 0% Ignored (Why) Jun 22nd Boston Invite 2019
77 Ignite Win 15-7 0.64 4.71% Counts (Why) Jun 22nd Boston Invite 2019
81 BUDA U20G** Win 10-1 0 0% Ignored (Why) Jun 22nd Boston Invite 2019
74 Boston Win 10-6 -2.25 4.32% Counts (Why) Jun 22nd Boston Invite 2019
67 Hot Metal Win 13-8 4.59 4.71% Counts Jun 23rd Boston Invite 2019
40 Pine Baroness Loss 12-14 -7.39 4.71% Counts Jun 23rd Boston Invite 2019
51 Venus Win 11-7 16.2 4.58% Counts Jun 23rd Boston Invite 2019
80 DC Rogue Win 10-5 -5.71 4.91% Counts (Why) Jul 13th Scuffletown Throwdown 2019
48 Taco Truck Win 9-5 21.64 4.74% Counts (Why) Jul 13th Scuffletown Throwdown 2019
94 Suffrage** Win 11-3 0 0% Ignored (Why) Jul 13th Scuffletown Throwdown 2019
30 Warhawks Loss 5-11 -17.25 5.07% Counts (Why) Jul 13th Scuffletown Throwdown 2019
66 Eliza Furnace Win 11-6 7.96 5.23% Counts (Why) Jul 13th Scuffletown Throwdown 2019
65 Broad City Win 10-7 -0.43 5.23% Counts Jul 14th Scuffletown Throwdown 2019
26 Virginia Rebellion Loss 7-12 -10.6 5.52% Counts Jul 14th Scuffletown Throwdown 2019
48 Taco Truck Win 11-10 1.8 5.52% Counts Jul 14th Scuffletown Throwdown 2019
58 Agency Win 12-5 22.35 6.56% Counts (Why) Aug 10th Chesapeake Open 2019
62 Notorious C.L.E. Win 12-10 -10.08 6.84% Counts Aug 10th Chesapeake Open 2019
26 Virginia Rebellion Loss 11-12 15.73 6.84% Counts Aug 10th Chesapeake Open 2019
65 Broad City Win 11-8 -2.34 6.84% Counts Aug 11th Chesapeake Open 2019
41 Vice Loss 9-10 -4.07 6.84% Counts Aug 11th Chesapeake Open 2019
40 Pine Baroness Loss 8-13 -31.18 6.84% Counts Aug 11th Chesapeake Open 2019
**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.