(6) #155 Cream City Crooks (5-22)

379.67 (64)

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# Opponent Result Effect % of Ranking Status Date Event
76 Enigma Loss 8-15 3.13 3.92% Jul 22nd Heavyweights 2017
81 South Shore Line** Loss 4-15 0 0% Ignored Jul 22nd Heavyweights 2017
162 Hippie Mafia Win 13-11 5.74 3.92% Jul 22nd Heavyweights 2017
117 Satellite Loss 8-15 -7.86 3.92% Jul 23rd Heavyweights 2017
133 Auxiliary Loss 7-15 -14.41 3.92% Jul 23rd Heavyweights 2017
- Kettering** Win 15-4 0 0% Ignored Jul 23rd Heavyweights 2017
88 Wisconsin Hops Loss 8-11 9.89 4.6% Aug 12th The Bropen 2017
30 Mad Men** Loss 3-11 0 0% Ignored Aug 12th The Bropen 2017
63 Haymaker Loss 5-11 7.07 4.6% Aug 12th The Bropen 2017
28 Brickyard Loss 6-11 27.1 4.6% Aug 12th The Bropen 2017
40 Black Market** Loss 3-11 0 0% Ignored Aug 12th The Bropen 2017
88 Wisconsin Hops Loss 6-11 1.16 4.6% Aug 13th The Bropen 2017
68 Imperial Loss 10-15 12.15 4.6% Aug 13th The Bropen 2017
109 houSE Loss 6-15 -6.55 4.6% Aug 13th The Bropen 2017
129 Baemaker Loss 11-13 2.31 4.85% Aug 19th Cooler Classic 29
159 Black Market II Win 13-5 26.94 4.85% Aug 19th Cooler Classic 29
117 Satellite Loss 4-13 -11.62 4.85% Aug 19th Cooler Classic 29
148 Black Penguins Club Win 13-6 33.24 4.85% Aug 19th Cooler Classic 29
97 Climax Win 15-13 37.7 4.85% Aug 20th Cooler Classic 29
124 DeMo Loss 10-15 -5.36 4.85% Aug 20th Cooler Classic 29
129 Baemaker Loss 5-11 -16.61 4.85% Aug 20th Cooler Classic 29
49 MKE** Loss 1-15 0 0% Ignored Sep 9th 2017 Northwest Plains Mens Sectionals
68 Imperial** Loss 2-15 0 0% Ignored Sep 9th 2017 Northwest Plains Mens Sectionals
130 DingWop Loss 4-15 -19.92 5.69% Sep 9th 2017 Northwest Plains Mens Sectionals
162 Hippie Mafia Loss 10-15 -32.69 5.69% Sep 9th 2017 Northwest Plains Mens Sectionals
- Snip Snip Loss 9-15 -30.41 5.69% Sep 10th 2017 Northwest Plains Mens Sectionals
- Green Bay Quackers Loss 3-13 -21.85 5.69% Sep 10th 2017 Northwest 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.