(4) #146 AK Pipeline (6-20)

493.29 (36)

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# Opponent Result Effect % of Ranking Status Date Event
86 Mango Tree Loss 6-13 -4.6 3.42% Jul 8th MoTown Throwdown 2017
40 Black Market** Loss 2-13 0 0% Ignored Jul 8th MoTown Throwdown 2017
152 Dirty D Loss 12-14 -11.22 3.42% Jul 8th MoTown Throwdown 2017
41 Illusion** Loss 0-15 0 0% Ignored Jul 8th MoTown Throwdown 2017
136 Low Five Loss 11-15 -10.21 3.42% Jul 9th MoTown Throwdown 2017
159 Black Market II Loss 7-11 -23.12 3.42% Jul 9th MoTown Throwdown 2017
- SEMI Win 13-7 -4.05 3.42% Jul 9th MoTown Throwdown 2017
166 First Order Win 13-7 10.5 3.81% Jul 22nd Stonewalled 2017
- Carolina Sky Win 11-9 9.94 3.81% Jul 22nd Stonewalled 2017
83 JAWN Loss 9-13 3.32 3.81% Jul 22nd Stonewalled 2017
- Foggy Bottom Boys Loss 11-12 4.17 3.81% Jul 22nd Stonewalled 2017
121 Munch Box Loss 4-11 -13.92 3.81% Jul 23rd Stonewalled 2017
161 Bomb Squad Win 10-9 -2.92 3.81% Jul 23rd Stonewalled 2017
107 Watchdogs Loss 13-14 10.92 4.47% Aug 12th Nuccis Cup 2017
149 Club M - Magma Loss 12-13 -8.84 4.47% Aug 12th Nuccis Cup 2017
96 Adelphos Loss 13-15 10.19 4.47% Aug 12th Nuccis Cup 2017
135 Helots Loss 12-14 -5.8 4.47% Aug 12th Nuccis Cup 2017
143 Garden Party Win 13-12 7.2 4.47% Aug 13th Nuccis Cup 2017
143 Garden Party Loss 9-11 -10.31 4.47% Aug 13th Nuccis Cup 2017
62 Bruises** Loss 6-15 0 0% Ignored Aug 13th Nuccis Cup 2017
138 Midnight Meat Train Win 13-12 11.32 5.53% Sep 9th 2017 East Plains Mens Sectionals
67 Four Loss 3-11 -0.2 5.53% Sep 9th 2017 East Plains Mens Sectionals
93 Black Lung Loss 4-11 -9.13 5.53% Sep 9th 2017 East Plains Mens Sectionals
35 CLE Smokestack Loss 7-10 32.04 5.53% Sep 9th 2017 East Plains Mens Sectionals
139 Solar Eclipse Loss 12-13 -4.31 5.53% Sep 10th 2017 East Plains Mens Sectionals
76 Enigma Loss 8-11 9.51 5.53% Sep 10th 2017 East Plains Mens Sectionals
**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.