(3) #182 Sebastopol Orchard (6-14)

672.27 (8)

Click on column to sort  • 
# Opponent Result Effect % of Ranking Status Date Event
161 AC Bandits Loss 4-11 -22.09 4.47% Jun 9th Bay Area Ultimate Classic 2018
74 Alchemy Loss 4-12 -0.35 4.68% Jun 9th Bay Area Ultimate Classic 2018
35 Classy** Loss 2-15 0 0% Ignored Jun 9th Bay Area Ultimate Classic 2018
245 Hot Stix** Win 8-0 0 0% Ignored Jun 10th Bay Area Ultimate Classic 2018
190 DR Loss 6-10 -24.96 4.47% Jun 10th Bay Area Ultimate Classic 2018
119 Buckwild Loss 6-15 -12.35 4.87% Jun 10th Bay Area Ultimate Classic 2018
245 Hot Stix** Win 14-4 0 0% Ignored Jul 21st Revolution 2018
193 Feral Cows Win 11-4 35.65 6.16% Jul 21st Revolution 2018
71 Robot** Loss 2-15 0 0% Ignored Jul 21st Revolution 2018
120 Mimosas Loss 7-9 4.68 6.16% Jul 22nd Revolution 2018
109 Superstition Loss 6-13 -14.37 6.71% Jul 22nd Revolution 2018
170 Spoiler Alert Win 10-6 38.21 6.16% Jul 22nd Revolution 2018
51 Cutthroat** Loss 4-11 0 0% Ignored Sep 8th Nor Cal Mixed Sectional Championship 2018
236 Delta Breeze Win 11-6 8.49 9.22% Sep 8th Nor Cal Mixed Sectional Championship 2018
61 Donuts** Loss 3-11 0 0% Ignored Sep 8th Nor Cal Mixed Sectional Championship 2018
119 Buckwild Loss 5-11 -23.68 8.94% Sep 8th Nor Cal Mixed Sectional Championship 2018
7 Blackbird Loss 5-11 60.82 8.94% Sep 8th Nor Cal Mixed Sectional Championship 2018
210 VU Win 11-10 -2.23 9.74% Sep 9th Nor Cal Mixed Sectional Championship 2018
187 Megalodon Loss 12-13 -16.61 9.74% Sep 9th Nor Cal Mixed Sectional Championship 2018
193 Feral Cows Loss 11-13 -30.81 9.74% Sep 9th Nor Cal Mixed 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.