(2) #179 LORD (9-12)

681.22 (9)

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# Opponent Result Effect % of Ranking Status Date Event
207 District Cocktails Win 10-9 -0.89 4.18% Jul 14th Battle for the Beltway 2018
- Swing Vote Win 13-3 4.93 4.18% Jul 14th Battle for the Beltway 2018
87 Sparkle Ponies Loss 5-11 -4.14 3.84% Jul 14th Battle for the Beltway 2018
173 Fake Newport News Win 10-9 8.09 4.18% Jul 14th Battle for the Beltway 2018
207 District Cocktails Win 9-5 14.28 3.59% Jul 15th Battle for the Beltway 2018
144 Rat City Loss 6-13 -17.04 4.18% Jul 15th Battle for the Beltway 2018
- Swing Vote Win 13-9 -2.99 4.18% Jul 15th Battle for the Beltway 2018
50 Grand Army** Loss 5-13 0 0% Ignored Aug 11th Chesapeake Open 2018
79 8 Bit Heroes Loss 6-13 -2.07 5.17% Aug 11th Chesapeake Open 2018
126 American Hyperbole Loss 7-11 -8.8 5.04% Aug 11th Chesapeake Open 2018
114 Buffalo Lake Effect Loss 8-9 12.12 4.89% Aug 11th Chesapeake Open 2018
101 Tyrannis Loss 8-12 -0.54 5.17% Aug 12th Chesapeake Open 2018
149 Crucible Loss 8-12 -13.24 5.17% Aug 12th Chesapeake Open 2018
101 Tyrannis Loss 5-11 -10.54 5.88% Sep 8th Capital Mixed Sectional Championship 2018
156 Heavy Flow Loss 6-9 -15.7 5.69% Sep 8th Capital Mixed Sectional Championship 2018
95 Ant Madness Loss 5-11 -8.36 5.88% Sep 8th Capital Mixed Sectional Championship 2018
232 Baltimore BENCH Win 10-7 -0.15 6.06% Sep 8th Capital Mixed Sectional Championship 2018
239 Pandatime Win 11-3 5.37 5.88% Sep 8th Capital Mixed Sectional Championship 2018
156 Heavy Flow Loss 7-8 2.01 5.69% Sep 9th Capital Mixed Sectional Championship 2018
- Hott Olson Win 11-6 15.02 6.06% Sep 9th Capital Mixed Sectional Championship 2018
207 District Cocktails Win 8-4 22.49 5.09% Sep 9th Capital 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.