(2) #85 Lady Forward (7-14)

257.2 (60)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
84 Autonomous Loss 9-10 -3.56 2 3.94% Counts Jun 22nd SCINNY 2019
46 Indy Rogue Loss 7-14 10.66 68 3.94% Counts Jun 22nd SCINNY 2019
97 Belle Win 11-8 -2.66 44 3.94% Counts Jun 22nd SCINNY 2019
65 Eliza Furnace Loss 8-12 1.12 44 3.94% Counts Jun 23rd SCINNY 2019
90 Sureshot Loss 9-14 -22.53 73 3.94% Counts Jun 23rd SCINNY 2019
84 Autonomous Loss 7-10 -19 2 5.13% Counts Aug 3rd Heavyweights 2019
87 Cold Cuts Loss 10-12 -14.82 41 5.42% Counts Aug 3rd Heavyweights 2019
94 Inferno Loss 8-13 -38.06 6 5.42% Counts Aug 3rd Heavyweights 2019
53 Stellar** Loss 4-13 0 126 0% Ignored (Why) Aug 3rd Heavyweights 2019
87 Cold Cuts Loss 9-13 -25.16 41 5.42% Counts Aug 4th Heavyweights 2019
106 Frenzy Win 13-5 0 0% Ignored (Why) Aug 4th Heavyweights 2019
84 Autonomous Win 10-8 19.87 2 6.19% Counts Aug 24th Indy Invite Club 2019
72 Helix Loss 9-10 17.1 49 6.36% Counts Aug 24th Indy Invite Club 2019
63 Huntsville Laika Loss 7-12 -0.86 15 6.36% Counts Aug 24th Indy Invite Club 2019
90 Sureshot Win 13-10 17.16 73 6.36% Counts Aug 24th Indy Invite Club 2019
84 Autonomous Win 13-10 24.9 2 6.36% Counts Aug 25th Indy Invite Club 2019
63 Huntsville Laika Loss 7-10 7.57 15 6.02% Counts Aug 25th Indy Invite Club 2019
87 Cold Cuts Win 12-9 24.77 41 7.08% Counts Sep 7th Northwest Plains Womens Club Sectional Championship 2019
60 Crackle Loss 7-13 1.4 47 7.08% Counts Sep 7th Northwest Plains Womens Club Sectional Championship 2019
31 Fusion** Loss 2-13 0 109 0% Ignored (Why) Sep 7th Northwest Plains Womens Club Sectional Championship 2019
91 MystiKuE Win 13-12 3.74 22 7.08% Counts Sep 7th Northwest Plains Womens Club Sectional Championship 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.