(3) #103 Scythe (12-8)

1203.08 (61)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
147 DINGWOP Win 12-7 9.68 73 3.62% Counts (Why) Jun 24th Spirit of the Plains
233 BeMo Win 13-6 -7.23 75 3.62% Counts (Why) Jun 24th Spirit of the Plains
73 Knights of Ni Loss 9-13 -8.87 81 3.62% Counts Jun 24th Spirit of the Plains
204 Loaded Panda Win 12-6 0.68 71 3.53% Counts (Why) Jun 24th Spirit of the Plains
148 Minnesota Superior A Loss 9-10 -14.99 78 3.62% Counts Jun 25th Spirit of the Plains
192 Minnesota Superior B Win 11-8 -4.11 75 3.62% Counts Jun 25th Spirit of the Plains
46 DeMo Loss 4-13 -9 54 3.62% Counts (Why) Jun 25th Spirit of the Plains
77 BARNSTORM Loss 8-11 -12.06 36 5.86% Counts Aug 26th Ragna Rock 2023
172 Memphis Pharaohs Win 13-8 7.36 45 5.86% Counts Aug 26th Ragna Rock 2023
208 Grit** Win 13-5 0 37 0% Ignored (Why) Aug 26th Ragna Rock 2023
116 Atlanta Arson Loss 8-10 -19.45 63 5.7% Counts Aug 27th Ragna Rock 2023
172 Memphis Pharaohs Win 13-6 13.82 45 5.86% Counts (Why) Aug 27th Ragna Rock 2023
149 Rawhide Win 13-10 3.24 34 5.86% Counts Aug 27th Ragna Rock 2023
17 STL Lounar Loss 6-13 7.41 57 6.51% Counts (Why) Sep 9th 2023 Mens West Plains Sectional Shampionship
143 STL Moonar Win 13-8 18.11 67 6.51% Counts Sep 9th 2023 Mens West Plains Sectional Shampionship
131 NOx Win 15-12 9.48 74 6.51% Counts Sep 9th 2023 Mens West Plains Sectional Shampionship
204 Loaded Panda Win 13-10 -16.21 71 6.51% Counts Sep 9th 2023 Mens West Plains Sectional Shampionship
143 STL Moonar Win 13-8 18.11 67 6.51% Counts Sep 10th 2023 Mens West Plains Sectional Shampionship
36 Kansas City Smokestack Loss 13-14 21.87 68 6.51% Counts Sep 10th 2023 Mens West Plains Sectional Shampionship
46 DeMo Loss 5-15 -16.69 54 6.51% Counts (Why) Sep 10th 2023 Mens West Plains Sectional Shampionship
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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.