(5) #100 Charleston Heat Stroke (9-11)

876.95 (12)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
162 Scoop** Win 11-2 0 2 0% Ignored (Why) Jul 23rd Filling the Void
54 Brickhouse Loss 7-11 -6.97 8 4.1% Counts Jul 23rd Filling the Void
154 Queen City Kings Win 11-0 2.58 9 3.87% Counts (Why) Jul 23rd Filling the Void
110 Tennessee Folklore Win 11-7 16.72 12 4.1% Counts Jul 23rd Filling the Void
75 Rush Hour ATL Win 9-7 17.29 11 3.87% Counts Jul 24th Filling the Void
60 baNC Loss 9-10 6.17 10 4.21% Counts Jul 24th Filling the Void
96 Dyno Win 9-8 5.43 13 3.99% Counts Jul 24th Filling the Void
103 Space Cowboys Loss 11-13 -15.57 14 5.5% Counts Aug 27th FCS Invite 2022
19 Raleigh-Durham United Loss 7-13 12.43 7 5.5% Counts Aug 27th FCS Invite 2022
48 Oakgrove Boys Loss 8-13 -8.5 3 5.5% Counts Aug 27th FCS Invite 2022
103 Space Cowboys Win 13-6 32.69 14 5.5% Counts (Why) Aug 28th FCS Invite 2022
105 Black Lung Win 13-8 26.3 53 5.5% Counts Aug 28th FCS Invite 2022
38 Redwolves Loss 12-13 17.75 3 5.5% Counts Aug 28th FCS Invite 2022
63 Delirium Win 15-12 35.83 11 6.12% Counts Sep 10th 2022 East Coast Mens Sectional Championship
123 Atlanta Arson Loss 12-14 -24.06 11 6.12% Counts Sep 10th 2022 East Coast Mens Sectional Championship
144 Nashville Mudcats Win 15-4 15.87 8 6.12% Counts (Why) Sep 10th 2022 East Coast Mens Sectional Championship
80 Hooch Loss 10-14 -18.84 11 6.12% Counts Sep 10th 2022 East Coast Mens Sectional Championship
103 Space Cowboys Loss 8-13 -34.87 14 6.12% Counts Sep 11th 2022 East Coast Mens Sectional Championship
110 Tennessee Folklore Loss 10-15 -34.54 12 6.12% Counts Sep 11th 2022 East Coast Mens Sectional Championship
144 Nashville Mudcats Loss 8-11 -47.09 8 6.12% Counts Sep 11th 2022 East Coast Mens Sectional Championship
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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.