() #124 Wisconsin Hops (12-8)

696.35 (36)

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# Opponent Result Effect % of Ranking Status Date Event
159 Midnight Meat Train Win 13-4 6.78 4.64% Aug 4th Heavyweights 2018
73 Greater Gary Goblins Y Loss 9-13 -4.82 4.64% Aug 4th Heavyweights 2018
117 THE BODY Loss 8-9 -4.15 4.38% Aug 4th Heavyweights 2018
164 Fifty-Fifty Win 13-6 2.01 4.64% Aug 5th Heavyweights 2018
- Kettering** Win 13-2 0 0% Ignored Aug 5th Heavyweights 2018
120 KC SmokeStack Loss 6-11 -24.36 4.38% Aug 5th Heavyweights 2018
123 Satellite Loss 11-13 -12.18 5.16% Aug 18th Cooler Classic 30
149 Chimney Win 13-9 3.77 5.16% Aug 18th Cooler Classic 30
152 Green Bay Quackers Win 13-7 10.52 5.16% Aug 18th Cooler Classic 30
116 Greater Gary Goblins X Win 13-10 20.28 5.16% Aug 18th Cooler Classic 30
123 Satellite Win 9-8 6.66 4.88% Aug 19th Cooler Classic 30
111 Cryptic Loss 11-15 -16.91 5.16% Aug 19th Cooler Classic 30
103 houSE Win 15-11 27.64 5.16% Aug 19th Cooler Classic 30
59 Mallard Win 15-14 33.93 6.05% Sep 8th Northwest Plains Mens Sectional Championship 2018
70 Imperial Loss 8-15 -14.85 6.05% Sep 8th Northwest Plains Mens Sectional Championship 2018
163 Hippie Mafia Win 15-7 3.36 6.05% Sep 8th Northwest Plains Mens Sectional Championship 2018
117 THE BODY Loss 11-15 -22.32 6.05% Sep 8th Northwest Plains Mens Sectional Championship 2018
132 DingWop Win 8-6 11.69 5.19% Sep 9th Northwest Plains Mens Sectional Championship 2018
152 Green Bay Quackers Win 13-7 12.47 6.05% Sep 9th Northwest Plains Mens Sectional Championship 2018
161 Ironside Loss 11-12 -39.56 6.05% Sep 9th Northwest Plains Mens Sectional Championship 2018
**Blowout Eligible

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.