(1) #52 Mallard (12-7)

1329.58 (3)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
56 Scythe Win 13-11 9.32 30 4.74% Counts Jun 29th Spirit of the Plains 2019
25 General Strike Loss 9-13 -9.12 98 4.74% Counts Jun 29th Spirit of the Plains 2019
130 Kansas City Smokestack Win 12-10 -9.69 91 4.74% Counts Jun 29th Spirit of the Plains 2019
102 THE BODY Win 12-5 14.27 13 4.55% Counts (Why) Jun 30th Spirit of the Plains 2019
20 Yogosbo Loss 8-13 -4.61 20 4.74% Counts Jun 30th Spirit of the Plains 2019
60 Swans Win 10-7 15.55 35 4.48% Counts Jun 30th Spirit of the Plains 2019
34 Mad Men Loss 6-13 -25.33 92 5.27% Counts (Why) Jul 13th The Bropen 2019
87 Red Hots - u20 Win 13-10 6.27 70 5.27% Counts Jul 13th The Bropen 2019
175 Milwaukee Revival** Win 13-5 0 72 0% Ignored (Why) Jul 13th The Bropen 2019
100 Timber Win 13-6 17.36 160 5.27% Counts (Why) Jul 13th The Bropen 2019
34 Mad Men Win 12-11 15.02 92 5.27% Counts Jul 14th The Bropen 2019
94 Minnesota Superior U20B Win 13-7 16.66 75 5.27% Counts (Why) Jul 14th The Bropen 2019
20 Yogosbo Loss 6-13 -10.94 20 5.27% Counts (Why) Jul 14th The Bropen 2019
41 MKE Loss 9-13 -29.64 66 8.08% Counts Sep 7th Northwest Plains Mens Club Sectional Championship 2019
100 Timber Win 12-10 -4.39 160 8.08% Counts Sep 7th Northwest Plains Mens Club Sectional Championship 2019
95 HouSE Win 12-9 7.54 50 8.08% Counts Sep 7th Northwest Plains Mens Club Sectional Championship 2019
20 Yogosbo Loss 10-13 6.62 20 8.08% Counts Sep 8th Northwest Plains Mens Club Sectional Championship 2019
175 Milwaukee Revival** Win 13-5 0 72 0% Ignored (Why) Sep 8th Northwest Plains Mens Club Sectional Championship 2019
60 Swans Loss 13-14 -16.11 35 8.08% Counts Sep 8th Northwest 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.