(7) #142 ScooberDivers (10-10)

827.39 (63)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
140 Space Coast Ultimate Win 11-9 10.47 14 3.94% Counts Jul 13th Swan Boat 2019
133 Vicious Cycle Loss 7-11 -16.43 5 3.83% Counts Jul 13th Swan Boat 2019
203 Scootlyfe Win 11-10 -10.93 58 3.94% Counts Jul 13th Swan Boat 2019
217 Tyranny Win 11-7 -1.48 158 3.83% Counts Jul 13th Swan Boat 2019
124 Swamp Horse Loss 9-15 -17.53 8 3.94% Counts Jul 14th Swan Boat 2019
113 Omen Loss 7-8 0.52 72 3.5% Counts Jul 14th Swan Boat 2019
133 Vicious Cycle Loss 13-15 -6.54 5 3.94% Counts Jul 14th Swan Boat 2019
168 Barefoot Win 13-6 24.17 146 5.14% Counts (Why) Aug 17th Mudbowl 2019
187 Rampage Win 13-4 16.57 132 5.14% Counts (Why) Aug 17th Mudbowl 2019
192 Trent's Team Win 13-9 5.96 33 5.14% Counts Aug 17th Mudbowl 2019
29 Clutch Loss 8-13 11.65 42 5.14% Counts Aug 18th Mudbowl 2019
126 Rougaroux Loss 6-13 -28.31 36 5.14% Counts (Why) Aug 18th Mudbowl 2019
124 Swamp Horse Loss 9-13 -17.92 8 5.14% Counts Aug 18th Mudbowl 2019
133 Vicious Cycle Loss 9-13 -23.37 5 6.03% Counts Sep 7th Florida Mens Club Sectional Championship 2019
67 UpRoar Loss 9-13 -2.16 76 6.03% Counts Sep 7th Florida Mens Club Sectional Championship 2019
203 Scootlyfe Win 13-6 13.38 58 6.03% Counts (Why) Sep 7th Florida Mens Club Sectional Championship 2019
124 Swamp Horse Win 12-11 13.68 8 6.03% Counts Sep 7th Florida Mens Club Sectional Championship 2019
190 UpRoar Claws Win 15-10 9.97 6.03% Counts Sep 8th Florida Mens Club Sectional Championship 2019
113 Omen Win 14-10 34.55 72 6.03% Counts Sep 8th Florida Mens Club Sectional Championship 2019
124 Swamp Horse Loss 10-13 -15.42 8 6.03% Counts Sep 8th Florida Mens Club Sectional Championship 2019
**Blowout Eligible. Learn more about how this works here.

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.