(6) #148 Rowdy (6-15)

859.89 (6)

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# Opponent Result Effect % of Ranking Status Date Event
43 Murmur Loss 8-13 7.03 4.57% Counts Jun 22nd Summer Glazed Daze 2019
115 NC Galaxy Win 10-9 14.25 4.57% Counts Jun 22nd Summer Glazed Daze 2019
18 Loco** Loss 4-13 0 0% Ignored (Why) Jun 22nd Summer Glazed Daze 2019
100 Rat City Loss 4-11 -16.08 4.19% Counts (Why) Jun 23rd Summer Glazed Daze 2019
31 Storm Loss 8-13 14.22 4.57% Counts Jun 23rd Summer Glazed Daze 2019
59 8 Bit Heroes Loss 6-13 -3.67 4.57% Counts (Why) Jun 23rd Summer Glazed Daze 2019
115 NC Galaxy Loss 8-11 -10.95 5.36% Counts Jul 13th Hometown Mix Up 2019
236 RnB Win 13-3 3.45 5.36% Counts (Why) Jul 13th Hometown Mix Up 2019
169 APEX Win 10-9 0.17 5.36% Counts Jul 13th Hometown Mix Up 2019
35 Superlame** Loss 5-12 0 0% Ignored (Why) Jul 13th Hometown Mix Up 2019
115 NC Galaxy Win 7-5 22.29 4.26% Counts Jul 14th Hometown Mix Up 2019
102 Seoulmates Win 10-8 27.02 5.22% Counts Jul 14th Hometown Mix Up 2019
35 Superlame** Loss 4-13 0 0% Ignored (Why) Jul 14th Hometown Mix Up 2019
73 Bexar Loss 6-13 -12.23 6.64% Counts (Why) Aug 10th HoDown ShowDown 23 GOAT
79 Auburn HeyDay Loss 9-11 9.73 6.64% Counts Aug 10th HoDown ShowDown 23 GOAT
55 Malice in Wonderland Loss 5-12 -2.55 6.37% Counts (Why) Aug 10th HoDown ShowDown 23 GOAT
169 APEX Win 13-12 0.21 6.64% Counts Aug 10th HoDown ShowDown 23 GOAT
137 BATL Cows Loss 10-14 -23.05 6.64% Counts Aug 11th HoDown ShowDown 23 GOAT
168 Moonshine Loss 8-9 -15.77 6.28% Counts Aug 11th HoDown ShowDown 23 GOAT
110 sKNO cone Loss 10-12 -3.36 6.64% Counts Aug 11th HoDown ShowDown 23 GOAT
136 Jackpot Loss 7-9 -11.76 6.09% Counts Aug 11th HoDown ShowDown 23 GOAT
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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.