(10) #242 RnB (3-15)

465.07 (161)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
73 Petey's Pirates** Loss 5-13 0 48 0% Ignored (Why) Jun 22nd Summer Glazed Daze 2019
140 Crucible Loss 6-13 -5.41 6 6.22% Counts (Why) Jun 22nd Summer Glazed Daze 2019
237 Stormborn Win 13-7 38.05 70 6.22% Counts (Why) Jun 22nd Summer Glazed Daze 2019
223 District Cocktails Loss 7-12 -26.36 50 6.22% Counts Jun 23rd Summer Glazed Daze 2019
195 Heavy Flow Loss 5-13 -24.09 54 6.22% Counts (Why) Jun 23rd Summer Glazed Daze 2019
167 Possum Loss 4-13 -15.18 56 6.22% Counts (Why) Jun 23rd Summer Glazed Daze 2019
265 ThunderCats Win 13-3 30.46 283 6.22% Counts (Why) Jun 23rd Summer Glazed Daze 2019
165 APEX Loss 9-12 2.73 137 7.29% Counts Jul 13th Hometown Mix Up 2019
38 Superlame** Loss 2-13 0 15 0% Ignored (Why) Jul 13th Hometown Mix Up 2019
111 NC Galaxy** Loss 3-13 0 91 0% Ignored (Why) Jul 13th Hometown Mix Up 2019
159 Rowdy Loss 3-13 -12.94 74 7.29% Counts (Why) Jul 13th Hometown Mix Up 2019
167 Possum Loss 7-13 -14.67 56 7.29% Counts Jul 14th Hometown Mix Up 2019
274 Rampage Loss 11-13 -34.65 56 7.29% Counts Jul 14th Hometown Mix Up 2019
270 Baltimore BENCH Win 13-7 48.45 59 11.17% Counts (Why) Sep 7th Capital Mixed Club Sectional Championship 2019
90 Fleet Loss 6-13 16.62 16 11.17% Counts (Why) Sep 7th Capital Mixed Club Sectional Championship 2019
23 Rally** Loss 2-13 0 14 0% Ignored (Why) Sep 7th Capital Mixed Club Sectional Championship 2019
115 Rat City** Loss 3-13 0 84 0% Ignored (Why) Sep 7th Capital Mixed Club Sectional Championship 2019
223 District Cocktails Loss 12-13 -0.27 50 11.17% Counts Sep 8th Capital Mixed 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.