() #47 Trainwreck (7-13)

838.18 (3)

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# Opponent Result Effect % of Ranking Status Date Event
26 Elevate Loss 2-15 -1.5 3.89% Jun 16th Fort Collins Summer Solstice 2018
25 Colorado Small Batch Loss 7-15 0.36 3.89% Jun 16th Fort Collins Summer Solstice 2018
50 Cold Cuts Win 12-4 22.51 3.74% Jun 16th Fort Collins Summer Solstice 2018
38 Jackwagon Loss 8-11 -4.95 3.89% Jun 17th Fort Collins Summer Solstice 2018
- Colorado Cutthroat Win 15-8 7.97 3.89% Jun 17th Fort Collins Summer Solstice 2018
52 Deadly Viper Assassination Squad Win 14-12 7.14 3.89% Jun 17th Fort Collins Summer Solstice 2018
69 Viva Win 13-3 9.92 6.29% Aug 18th Ski Town Classic 2018
68 Seven Devils Win 13-5 11.96 6.29% Aug 18th Ski Town Classic 2018
26 Elevate Loss 4-13 -2.49 6.29% Aug 18th Ski Town Classic 2018
52 Deadly Viper Assassination Squad Win 10-7 21.83 5.95% Aug 19th Ski Town Classic 2018
33 Rampage Loss 4-13 -18.44 6.29% Aug 19th Ski Town Classic 2018
38 Jackwagon Loss 9-12 -6.85 6.29% Aug 19th Ski Town Classic 2018
38 Jackwagon Loss 9-12 -8.13 7.38% Sep 8th Rocky Mountain Womens Sectional Championship 2018
25 Colorado Small Batch Loss 6-13 0.71 7.38% Sep 8th Rocky Mountain Womens Sectional Championship 2018
54 Maeve Loss 10-15 -51.41 8.21% Sep 22nd South Central Womens Regional Championship 2018
62 Inferno Win 12-8 15.76 8.21% Sep 22nd South Central Womens Regional Championship 2018
3 Molly Brown** Loss 1-15 0 0% Ignored Sep 22nd South Central Womens Regional Championship 2018
38 Jackwagon Loss 11-14 -6.26 8.21% Sep 22nd South Central Womens Regional Championship 2018
14 Showdown** Loss 0-15 0 0% Ignored Sep 23rd South Central Womens Regional Championship 2018
25 Colorado Small Batch** Loss 3-15 0 0% Ignored Sep 23rd South Central Womens Regional 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.