(1) #69 Sawtooth (14-11)

1080.45 (59)

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# Opponent Result Effect % of Ranking Status Date Event
22 Rhino Loss 2-13 -2.13 2.84% Jun 24th Eugene Summer Solstice 39
114 SURE Win 13-8 5.92 2.84% Jun 24th Eugene Summer Solstice 39
75 Ham Win 13-10 8.14 2.84% Jun 24th Eugene Summer Solstice 39
- Old Growth** Win 13-1 0 0% Ignored Jun 24th Eugene Summer Solstice 39
128 Union Win 13-4 5.48 2.84% Jun 25th Eugene Summer Solstice 39
78 Ghost Train Loss 8-10 -9.6 2.84% Jun 25th Eugene Summer Solstice 39
52 Republic Loss 4-13 -20.54 4.35% Aug 19th Ski Town Classic 2017
113 Thundersnow Win 11-6 12.2 4.35% Aug 19th Ski Town Classic 2017
- Big Sky** Win 13-4 0 0% Ignored Aug 19th Ski Town Classic 2017
123 DTH Win 13-6 11.5 4.35% Aug 19th Ski Town Classic 2017
52 Republic Win 11-8 23.42 4.35% Aug 20th Ski Town Classic 2017
51 Sundowners Loss 8-11 -9.62 4.35% Aug 20th Ski Town Classic 2017
91 Rip City Ultimate Win 9-8 -0.5 4.35% Aug 20th Ski Town Classic 2017
71 PowderHogs Loss 11-13 -13.65 5.11% Sep 9th 2017 Big Sky Mens Sectionals
79 The Killjoys Loss 11-15 -24.19 5.11% Sep 9th 2017 Big Sky Mens Sectionals
- Madd Dogg Win 15-7 5.21 5.11% Sep 9th 2017 Big Sky Mens Sectionals
71 PowderHogs Win 15-10 23.1 5.11% Sep 10th 2017 Big Sky Mens Sectionals
79 The Killjoys Loss 12-15 -19.84 5.11% Sep 10th 2017 Big Sky Mens Sectionals
22 Rhino Loss 6-13 -4.38 5.68% Sep 23rd Northwest Mens Regionals 2017
78 Ghost Train Win 13-11 9.85 5.68% Sep 23rd Northwest Mens Regionals 2017
2 Sockeye** Loss 5-13 0 0% Ignored Sep 23rd Northwest Mens Regionals 2017
75 Ham Win 12-10 11.34 5.68% Sep 23rd Northwest Mens Regionals 2017
71 PowderHogs Loss 9-14 -30.05 5.68% Sep 24th Northwest Mens Regionals 2017
34 Dark Star Loss 10-15 -6.05 5.68% Sep 24th Northwest Mens Regionals 2017
78 Ghost Train Win 11-7 24.19 5.68% Sep 24th Northwest Mens Regionals 2017
**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.