(2) #218 Great Minnesota Get Together (7-10)

612.32 (190)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
209 Pushovers-B Loss 8-11 -17.58 10 5.23% Counts Jul 20th Minnesota Ultimate Disc Invitational
248 Dinosaur Fancy Win 10-9 -3.02 88 5.23% Counts Jul 21st Minnesota Ultimate Disc Invitational
154 Melt Loss 5-13 -16.48 1 5.23% Counts (Why) Jul 21st Minnesota Ultimate Disc Invitational
171 Mousetrap Loss 6-10 -15.58 69 4.8% Counts Jul 21st Minnesota Ultimate Disc Invitational
279 Identity Theft Win 11-5 9.97 122 4.8% Counts (Why) Jul 21st Minnesota Ultimate Disc Invitational
156 ELevate Loss 8-12 -9.73 41 6.48% Counts Aug 17th Cooler Classic 31
171 Mousetrap Loss 9-12 -10.95 69 6.48% Counts Aug 17th Cooler Classic 31
214 Stackcats Loss 7-11 -29.73 21 6.3% Counts Aug 17th Cooler Classic 31
213 Mastodon Loss 7-9 -15.55 33 5.94% Counts Aug 18th Cooler Classic 31
241 EDM Win 9-6 16.9 231 5.75% Counts Aug 18th Cooler Classic 31
228 Midwestern Mediocrity Win 8-7 2.36 85 5.75% Counts Aug 18th Cooler Classic 31
248 Dinosaur Fancy Win 13-8 26.03 88 7.6% Counts Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
141 Mad Udderburn Loss 8-11 -0.79 60 7.6% Counts Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
154 Melt Loss 10-13 -2.19 1 7.6% Counts Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
32 NOISE** Loss 1-13 0 2 0% Ignored (Why) Sep 7th Northwest Plains Mixed Club Sectional Championship 2019
226 Boomtown Pandas Win 13-9 31.08 45 7.6% Counts Sep 8th Northwest Plains Mixed Club Sectional Championship 2019
244 Madison United Mixed Ultimate Win 13-6 36.96 1 7.6% Counts (Why) Sep 8th Northwest Plains Mixed 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.