(6) #196 VU (10-11)

627.44 (34)

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# Opponent Result Effect % of Ranking Status Date Event
97 Absolute Zero Loss 6-9 3.65 4.38% Jun 8th Bay Area Ultimate Classic 2019
35 Lotus** Loss 4-10 0 0% Ignored Jun 8th Bay Area Ultimate Classic 2019
250 Sebastopol Orchard Win 8-6 -7 4.23% Jun 8th Bay Area Ultimate Classic 2019
115 Robot Loss 5-11 -8.33 4.52% Jun 8th Bay Area Ultimate Classic 2019
240 Party Cats-D Win 10-4 11.38 4.3% Jun 9th Bay Area Ultimate Classic 2019
60 Firefly Loss 6-12 7.2 4.79% Jun 9th Bay Area Ultimate Classic 2019
192 Spoiler Alert Loss 10-11 -5.59 4.93% Jun 9th Bay Area Ultimate Classic 2019
223 Feral Cows Win 13-9 9.71 4.93% Jun 9th Bay Area Ultimate Classic 2019
121 Platypi Loss 7-11 -4.1 5.63% Jun 29th Truckee River Ultimate Cooldown 2019
89 Alchemy Loss 4-13 -2.52 5.78% Jun 29th Truckee River Ultimate Cooldown 2019
51 Garage Sale** Loss 3-13 0 0% Ignored Jun 29th Truckee River Ultimate Cooldown 2019
197 Fear and Loathing Win 11-9 15.15 5.78% Jun 29th Truckee River Ultimate Cooldown 2019
131 Argo Loss 7-11 -7.05 5.63% Jun 30th Truckee River Ultimate Cooldown 2019
270 Delta Breeze** Win 15-6 0 0% Ignored Jun 30th Truckee River Ultimate Cooldown 2019
223 Feral Cows Win 13-9 13.64 6.78% Jul 20th Revolution 2019
249 Happy Cows Win 10-4 9.64 5.92% Jul 20th Revolution 2019
192 Spoiler Alert Win 8-7 9.12 6.03% Jul 20th Revolution 2019
206 Sweet Action Loss 7-11 -36.32 6.6% Jul 20th Revolution 2019
240 Party Cats-D Loss 5-11 -62.84 6.22% Jul 21st Revolution 2019
220 Birds of Paradise Win 13-8 21.88 6.78% Jul 21st Revolution 2019
213 Megalodon Win 13-6 32.44 6.78% Jul 21st Revolution 2019
**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.