(18) #117 Satellite (13-6)

957.19 (39)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
193 Carolina Sky Win 13-10 -6.41 57 5.03% Counts Aug 3rd Heavyweights 2019
149 Ditto A Win 13-12 -3.04 146 5.03% Counts Aug 3rd Heavyweights 2019
60 Swans Loss 6-13 -15.16 35 5.03% Counts (Why) Aug 3rd Heavyweights 2019
154 Foxtrot Win 13-8 15.93 140 5.03% Counts Aug 4th Heavyweights 2019
204 Red Imp.ala Win 13-6 3.92 13 5.03% Counts (Why) Aug 4th Heavyweights 2019
101 Imperial Win 13-11 16.51 33 5.03% Counts Aug 4th Heavyweights 2019
175 Milwaukee Revival Win 13-10 0.53 72 5.6% Counts Aug 17th Cooler Classic 31
99 Black Market II Win 11-10 13.06 32 5.6% Counts Aug 17th Cooler Classic 31
130 Kansas City Smokestack Win 13-9 21.24 91 5.6% Counts Aug 17th Cooler Classic 31
56 Scythe Loss 8-13 -9.81 30 5.6% Counts Aug 17th Cooler Classic 31
118 CaSTLe Win 9-8 6.81 133 5.3% Counts Aug 18th Cooler Classic 31
74 DeMo Win 8-7 17.64 69 4.98% Counts Aug 18th Cooler Classic 31
99 Black Market II Win 6-5 9.8 32 4.26% Counts Aug 18th Cooler Classic 31
169 MomINtuM Win 13-5 22.15 139 6.57% Counts (Why) Sep 7th Central Plains Mens Club Sectional Championship 2019
149 Ditto A Loss 12-13 -21.61 146 6.57% Counts Sep 7th Central Plains Mens Club Sectional Championship 2019
231 Black Market III Win 13-7 -18.59 66 6.57% Counts (Why) Sep 7th Central Plains Mens Club Sectional Championship 2019
21 Brickyard** Loss 4-13 0 16 0% Ignored (Why) Sep 7th Central Plains Mens Club Sectional Championship 2019
99 Black Market II Loss 12-15 -14.44 32 6.57% Counts Sep 8th Central Plains Mens Club Sectional Championship 2019
149 Ditto A Loss 11-15 -39.63 146 6.57% Counts Sep 8th Central Plains Mens 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.