(2) #204 Loaded Panda (5-15)

642.29 (71)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
135 Trident II Loss 6-12 -7.14 100 3.48% Counts Jun 18th Spirit of the Plains
127 Nomads Win 11-9 24.42 73 3.58% Counts Jun 18th Spirit of the Plains
147 DINGWOP Loss 5-13 -11.85 73 3.78% Counts (Why) Jun 24th Spirit of the Plains
233 BeMo Win 12-10 0.26 75 3.78% Counts Jun 24th Spirit of the Plains
192 Minnesota Superior B Loss 8-10 -6.74 75 3.67% Counts Jun 24th Spirit of the Plains
103 Scythe Loss 6-12 -0.71 61 3.67% Counts Jun 24th Spirit of the Plains
73 Knights of Ni Loss 8-13 9.71 81 3.78% Counts Jun 25th Spirit of the Plains
147 DINGWOP Loss 7-11 -10.08 73 5.63% Counts Aug 19th Cooler Classic 34
179 Timber Loss 12-13 2.66 73 5.78% Counts Aug 19th Cooler Classic 34
106 MKE Loss 5-13 -3.68 61 5.78% Counts (Why) Aug 19th Cooler Classic 34
191 DCVIII Win 13-8 36.18 78 5.78% Counts Aug 19th Cooler Classic 34
219 THE BODY Loss 11-14 -26.03 76 5.78% Counts Aug 20th Cooler Classic 34
179 Timber Loss 11-12 2.66 73 5.78% Counts Aug 20th Cooler Classic 34
241 Middleton High School Win 13-4 12.74 75 5.78% Counts (Why) Aug 20th Cooler Classic 34
17 STL Lounar** Loss 3-13 0 57 0% Ignored (Why) Sep 9th 2023 Mens West Plains Sectional Shampionship
143 STL Moonar Loss 8-13 -12.5 67 6.79% Counts Sep 9th 2023 Mens West Plains Sectional Shampionship
103 Scythe Loss 10-13 16.94 61 6.79% Counts Sep 9th 2023 Mens West Plains Sectional Shampionship
131 NOx Loss 5-14 -14.83 74 6.79% Counts (Why) Sep 10th 2023 Mens West Plains Sectional Shampionship
131 NOx Loss 5-15 -14.83 74 6.79% Counts (Why) Sep 10th 2023 Mens West Plains Sectional Shampionship
214 Meadowlark Win 12-11 2.29 45 6.79% Counts Sep 10th 2023 Mens West Plains Sectional Shampionship
**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.