(4) #170 Boomtown Pandas (10-9)

727.04 (14)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
231 POW! Win 13-7 3.73 21 3.97% Counts (Why) Jul 8th Heavyweights 2023
105 Bandwagon Loss 7-13 -10.6 109 3.97% Counts Jul 8th Heavyweights 2023
86 Mad Udderburn Loss 6-13 -8.52 21 3.97% Counts (Why) Jul 8th Heavyweights 2023
210 ELevate Win 9-7 0.18 10 3.64% Counts Jul 9th Heavyweights 2023
200 Pixel Loss 7-13 -31.43 14 3.97% Counts Jul 9th Heavyweights 2023
179 Frostbite Loss 10-11 -8.52 5 3.97% Counts Jul 9th Heavyweights 2023
159 Pandamonium Win 13-9 27.62 12 5.47% Counts Aug 19th Cooler Classic 34
241 PanIC Win 10-7 -10.67 0 5.17% Counts Aug 19th Cooler Classic 34
176 The Force Win 10-9 2.88 13 5.47% Counts Aug 19th Cooler Classic 34
211 Lake Superior Disc Win 13-5 18.5 19 5.47% Counts (Why) Aug 19th Cooler Classic 34
135 Point of No Return Loss 8-13 -20.93 15 5.47% Counts Aug 20th Cooler Classic 34
116 Jabba Loss 6-15 -19.37 7 5.47% Counts (Why) Aug 20th Cooler Classic 34
176 The Force Loss 10-11 -11.58 13 5.47% Counts Aug 20th Cooler Classic 34
159 Pandamonium Loss 10-11 -4.54 12 6.42% Counts Sep 9th 2023 Mixed Northwest Plains Sectional Championship
60 Minnesota Star Power Loss 3-15 -2.15 12 6.42% Counts (Why) Sep 9th 2023 Mixed Northwest Plains Sectional Championship
244 Underdogs Win 15-7 -2.94 10 6.42% Counts (Why) Sep 9th 2023 Mixed Northwest Plains Sectional Championship
135 Point of No Return Win 14-10 36.57 15 6.42% Counts Sep 10th 2023 Mixed Northwest Plains Sectional Championship
211 Lake Superior Disc Win 15-5 21.93 19 6.42% Counts (Why) Sep 10th 2023 Mixed Northwest Plains Sectional Championship
128 Mousetrap Win 10-9 21.46 16 6.42% Counts Sep 10th 2023 Mixed Northwest Plains Sectional Championship
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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.