(11) #157 Drexel (8-13)

1129.41 (57)

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# Opponent Result Effect % of Ranking Status Date Event
87 Case Western Reserve Loss 6-11 -10.59 4.01% Feb 2nd Mid Atlantic Warmup 2019
88 Tennessee-Chattanooga Loss 9-11 1.8 4.24% Feb 2nd Mid Atlantic Warmup 2019
32 William & Mary** Loss 5-13 0 0% Ignored Feb 2nd Mid Atlantic Warmup 2019
39 Vermont Loss 4-13 -1.05 4.24% Feb 2nd Mid Atlantic Warmup 2019
120 James Madison Loss 9-15 -16.03 4.24% Feb 3rd Mid Atlantic Warmup 2019
195 George Washington Win 15-12 7.74 4.24% Feb 3rd Mid Atlantic Warmup 2019
166 Virginia Commonwealth Win 15-13 7.82 4.24% Feb 3rd Mid Atlantic Warmup 2019
137 North Carolina-B Loss 11-15 -12.28 4.24% Feb 3rd Mid Atlantic Warmup 2019
248 Shippensburg Win 13-6 17.88 5.04% Feb 23rd Oak Creek Challenge 2019
142 Princeton Loss 9-10 -2.37 5.04% Feb 23rd Oak Creek Challenge 2019
250 Maryland-Baltimore County Win 13-6 17.3 5.04% Feb 23rd Oak Creek Challenge 2019
299 Towson Win 11-5 7.43 4.63% Feb 23rd Oak Creek Challenge 2019
114 Liberty Loss 10-15 -15.02 5.04% Feb 24th Oak Creek Challenge 2019
174 Cedarville Loss 12-13 -9.92 5.04% Feb 24th Oak Creek Challenge 2019
206 West Chester Win 11-6 19.2 4.77% Feb 24th Oak Creek Challenge 2019
47 Maryland Loss 3-13 -4.66 5.99% Mar 16th Oak Creek Invite 2019
150 Cornell Win 13-10 24.03 5.99% Mar 16th Oak Creek Invite 2019
73 Temple Loss 7-13 -13.14 5.99% Mar 16th Oak Creek Invite 2019
197 George Mason Win 13-11 6.43 5.99% Mar 16th Oak Creek Invite 2019
120 James Madison Loss 12-13 1.81 5.99% Mar 17th Oak Creek Invite 2019
110 Williams Loss 6-15 -26.37 5.99% Mar 17th Oak Creek Invite 2019
**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.