(3) #173 Alt Stacks (8-9)

792.17 (101)

Click on column to sort  • 
# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
247 Pandatime Win 13-3 13.28 215 4.94% Counts (Why) Jul 13th Ow My Knee
180 Varsity Win 10-7 18.13 103 4.67% Counts Jul 13th Ow My Knee
96 Birds Loss 4-13 -13.14 85 5.79% Counts (Why) Aug 3rd Philly Open 2019
194 Nautilus Loss 7-10 -27.73 74 5.48% Counts Aug 3rd Philly Open 2019
231 Buffalo Brain Freeze Win 13-7 17 121 5.79% Counts (Why) Aug 3rd Philly Open 2019
216 Espionage Win 12-8 16.47 47 5.79% Counts Aug 3rd Philly Open 2019
117 PS Loss 7-13 -15.39 53 5.79% Counts Aug 3rd Philly Open 2019
94 Soft Boiled Loss 5-8 -3.21 3 4.79% Counts Aug 4th Philly Open 2019
142 Philly Twist Loss 9-15 -21.85 104 5.79% Counts Aug 4th Philly Open 2019
208 TBD Win 15-13 5.15 31 5.79% Counts Aug 4th Philly Open 2019
280 Skyscrapers Win 15-5 0.95 7.56% Counts (Why) Sep 7th Metro New York Mixed Club Sectional Championship 2019
180 Varsity Win 11-9 18.8 103 7.56% Counts Sep 7th Metro New York Mixed Club Sectional Championship 2019
56 Grand Army** Loss 5-13 0 81 0% Ignored (Why) Sep 7th Metro New York Mixed Club Sectional Championship 2019
68 Metro North Loss 5-15 -6.29 3 7.56% Counts (Why) Sep 7th Metro New York Mixed Club Sectional Championship 2019
96 Birds Loss 6-14 -17.49 85 7.56% Counts (Why) Sep 8th Metro New York Mixed Club Sectional Championship 2019
177 Unlimited Swipes Win 13-12 9.3 58 7.56% Counts Sep 8th Metro New York Mixed Club Sectional Championship 2019
120 Funk Loss 12-14 6.03 3 7.56% Counts Sep 8th Metro New York 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.