(30) #231 Pennsylvania-B (8-12)

317.18 (80)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
61 James Madison** Loss 0-12 0 52 0% Ignored (Why) Feb 23rd Commonwealth Cup 2019
262 Michigan-B Win 13-6 29.09 156 8.4% Counts (Why) Feb 23rd Commonwealth Cup 2019
51 Florida State** Loss 0-9 0 16 0% Ignored (Why) Feb 23rd Commonwealth Cup 2019
135 Princeton** Loss 3-12 0 32 0% Ignored (Why) Feb 23rd Commonwealth Cup 2019
161 Drexel Loss 5-12 -9.31 9 8.06% Counts (Why) Feb 24th Commonwealth Cup 2019
93 Kennesaw State** Loss 1-9 0 7 0% Ignored (Why) Feb 24th Commonwealth Cup 2019
248 Johns Hopkins University Loss 8-9 -31.09 80 10.01% Counts Mar 23rd Jersey Devil 8
256 College of New Jersey Win 7-6 -7.89 206 8.75% Counts Mar 23rd Jersey Devil 8
241 Cornell-B Win 7-6 3.48 114 8.75% Counts Mar 23rd Jersey Devil 8
253 Wellesley-B Win 8-7 -7.54 109 9.4% Counts Mar 23rd Jersey Devil 8
142 Amherst Loss 5-12 -2.16 52 10.15% Counts (Why) Mar 24th Jersey Devil 8
256 College of New Jersey Win 10-6 31.06 206 9.71% Counts (Why) Mar 24th Jersey Devil 8
106 Lehigh** Loss 2-11 0 79 0% Ignored (Why) Mar 24th Jersey Devil 8
253 Wellesley-B Win 5-4 -5.7 109 7.28% Counts Mar 24th Jersey Devil 8
52 Columbia** Loss 0-15 0 33 0% Ignored (Why) Mar 30th West Chester Ram Jam 2019
257 Millersville Win 7-5 10.76 455 8.91% Counts Mar 30th West Chester Ram Jam 2019
31 West Chester** Loss 3-11 0 44 0% Ignored (Why) Mar 30th West Chester Ram Jam 2019
76 Rensselaer Polytech** Loss 1-14 0 290 0% Ignored (Why) Mar 30th West Chester Ram Jam 2019
133 Haverford** Loss 4-10 0 10 0% Ignored (Why) Mar 31st West Chester Ram Jam 2019
257 Millersville Win 9-8 -11.04 455 10.6% Counts Mar 31st West Chester Ram Jam 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.