() #237 Robotic Snakes (4-16)

170.3 (22)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
225 EDM Loss 7-13 -25.91 18 5.52% Counts Jun 19th Colorado Ultimate ONE TEAM Summer Solstice
127 The Strangers Loss 3-7 2.3 25 4% Counts (Why) Jun 19th Colorado Ultimate ONE TEAM Summer Solstice
108 Fox Force Five Loss 7-13 11.5 22 5.52% Counts Jun 19th Colorado Ultimate ONE TEAM Summer Solstice
225 EDM Win 11-9 21.18 18 5.52% Counts Jun 20th Colorado Ultimate ONE TEAM Summer Solstice
170 BZ etc. Loss 10-15 -0.61 20 6.83% Counts Jul 17th The Royal Experience 2021
97 7 Sins** Loss 3-15 0 19 0% Ignored (Why) Jul 17th The Royal Experience 2021
28 Impact** Loss 4-15 0 23 0% Ignored (Why) Jul 17th The Royal Experience 2021
28 Impact** Loss 4-15 0 23 0% Ignored (Why) Jul 18th The Royal Experience 2021
230 Boomtown Pandas Win 12-9 34.74 22 7.59% Counts Jul 31st Heavyweights 2021
148 Jabba Loss 5-13 -3.48 26 7.59% Counts (Why) Jul 31st Heavyweights 2021
151 Prion Loss 3-13 -5.07 24 7.59% Counts (Why) Jul 31st Heavyweights 2021
77 Mad Udderburn** Loss 2-13 0 21 0% Ignored (Why) Jul 31st Heavyweights 2021
230 Boomtown Pandas Win 11-9 26.83 22 7.59% Counts Aug 1st Heavyweights 2021
122 ELevate** Loss 6-15 0 25 0% Ignored (Why) Aug 1st Heavyweights 2021
129 Mousetrap** Loss 5-13 0 21 0% Ignored (Why) Aug 14th Cooler Classic 32 Redux
159 Pushovers Loss 8-13 0.85 22 8.45% Counts Aug 14th Cooler Classic 32 Redux
186 Mastodon Loss 6-13 -21.14 22 8.45% Counts (Why) Aug 14th Cooler Classic 32 Redux
210 Stackcats Win 13-12 29.83 23 8.45% Counts Aug 14th Cooler Classic 32 Redux
230 Boomtown Pandas Loss 7-15 -48.24 22 8.45% Counts (Why) Aug 15th Cooler Classic 32 Redux
210 Stackcats Loss 10-15 -23.57 23 8.45% Counts Aug 15th Cooler Classic 32 Redux
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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.