(1) #60 Guerrilla (6-10)

1282.03 (3)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
15 Rhino Slam! Loss 12-14 18.99 49 5.69% Counts Aug 17th TCT Elite Select Challenge 2019
18 Yogosbo Loss 11-15 3.2 6 5.69% Counts Aug 17th TCT Elite Select Challenge 2019
54 Red Circus Win 11-9 17.68 1 5.69% Counts Aug 17th TCT Elite Select Challenge 2019
22 Patrol Loss 9-15 -10.18 1 5.69% Counts Aug 17th TCT Elite Select Challenge 2019
36 Freaks Loss 8-9 3.89 9 5.38% Counts Aug 18th TCT Elite Select Challenge 2019
145 Little Teapots Win 15-5 10.38 15 6.77% Counts (Why) Sep 7th Nor Cal Mens Club Sectional Championship 2019
109 Green River Swordfish Win 15-8 21.41 39 6.77% Counts (Why) Sep 7th Nor Cal Mens Club Sectional Championship 2019
153 The Berkeley Bobcats Win 15-13 -22.52 12 6.77% Counts Sep 7th Nor Cal Mens Club Sectional Championship 2019
55 OAT Loss 6-15 -40.69 10 6.77% Counts (Why) Sep 8th Nor Cal Mens Club Sectional Championship 2019
61 Battery Loss 13-15 -15.75 3 6.77% Counts Sep 8th Nor Cal Mens Club Sectional Championship 2019
55 OAT Loss 13-14 -7.01 10 7.6% Counts Sep 21st Southwest Club Mens Regional Championship 2019
9 SoCal Condors** Loss 4-15 0 17 0% Ignored (Why) Sep 21st Southwest Club Mens Regional Championship 2019
69 Streetgang Loss 12-13 -14.19 46 7.6% Counts Sep 21st Southwest Club Mens Regional Championship 2019
109 Green River Swordfish Win 13-11 -3.38 39 7.6% Counts Sep 22nd Southwest Club Mens Regional Championship 2019
55 OAT Loss 13-14 -7.01 10 7.6% Counts Sep 22nd Southwest Club Mens Regional Championship 2019
70 Sundowners Win 13-6 44.91 11 7.6% Counts (Why) Sep 22nd Southwest Club Mens Regional 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.