(31) #207 Colby (11-9)

795.22 (125)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
120 Army Loss 5-10 -9.49 81 4.35% Counts Feb 24th Bring The Huckus 2024
197 Haverford Win 10-8 15.21 1 4.77% Counts Feb 24th Bring The Huckus 2024
247 SUNY-Geneseo Win 10-9 -1.69 70 4.9% Counts Feb 24th Bring The Huckus 2024
100 Vermont-B Loss 3-13 -8.23 190 4.9% Counts (Why) Feb 24th Bring The Huckus 2024
252 Dickinson Win 15-10 13.85 80 4.9% Counts Feb 25th Bring The Huckus 2024
187 Salisbury Win 15-10 26.9 6 4.9% Counts Feb 25th Bring The Huckus 2024
100 Vermont-B Loss 8-15 -6.41 190 4.9% Counts Feb 25th Bring The Huckus 2024
251 Amherst Win 14-13 -3.17 182 5.19% Counts Mar 2nd Grand Northeast Kickoff
62 Massachusetts -B** Loss 3-15 0 149 0% Ignored (Why) Mar 2nd Grand Northeast Kickoff
138 Tufts-B Loss 9-15 -12.37 69 5.19% Counts Mar 2nd Grand Northeast Kickoff
251 Amherst Win 14-12 2.08 182 5.19% Counts Mar 3rd Grand Northeast Kickoff
269 Western New England Win 15-12 0.96 96 5.19% Counts Mar 3rd Grand Northeast Kickoff
240 Middlebury-B Win 14-10 15.07 69 5.19% Counts Mar 3rd Grand Northeast Kickoff
251 Amherst Win 10-5 24.12 182 5.81% Counts (Why) Mar 30th New England Open 2024 Open Division
86 Bates Loss 4-9 -4.47 87 5.41% Counts (Why) Mar 30th New England Open 2024 Open Division
295 Harvard-B Win 8-6 -7.45 55 5.62% Counts Mar 30th New England Open 2024 Open Division
182 Worcester Polytechnic Institute Loss 2-9 -28.85 194 5.41% Counts (Why) Mar 30th New England Open 2024 Open Division
141 Bryant Loss 5-13 -22.46 141 6.54% Counts (Why) Mar 31st New England Open 2024 Open Division
138 Tufts-B Loss 6-9 -7.96 69 5.81% Counts Mar 31st New England Open 2024 Open Division
181 Northeastern-B Win 8-7 14.06 70 5.81% Counts Mar 31st New England Open 2024 Open Division
**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.