(4) #61 James Madison (15-8)

1435.16 (52)

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# Opponent Result Effect % of Ranking Status Date Event
271 Virginia-B** Win 13-0 0 0% Ignored Jan 26th Winta Binta Vinta Fest 2019
82 Georgetown Win 10-6 12.7 3.73% Jan 26th Winta Binta Vinta Fest 2019
40 Michigan Loss 4-8 -14.39 3.23% Jan 26th Winta Binta Vinta Fest 2019
157 Virginia Commonwealth Win 11-7 -5.21 3.96% Jan 26th Winta Binta Vinta Fest 2019
45 Virginia Loss 6-8 -6.87 3.49% Jan 27th Winta Binta Vinta Fest 2019
59 Duke Win 8-6 11.27 3.49% Jan 27th Winta Binta Vinta Fest 2019
231 Pennsylvania-B** Win 12-0 0 0% Ignored Feb 23rd Commonwealth Cup 2019
135 Princeton Win 12-3 5.55 4.92% Feb 23rd Commonwealth Cup 2019
91 Case Western Reserve Win 13-9 10.05 5.13% Feb 23rd Commonwealth Cup 2019
70 Maryland Loss 8-9 -11.82 4.85% Feb 24th Commonwealth Cup 2019
27 Delaware Loss 2-9 -9.75 4.24% Feb 24th Commonwealth Cup 2019
27 Delaware Loss 9-13 -2.52 6.1% Mar 16th Bonanza 2019
56 Pennsylvania Loss 8-10 -13.28 5.93% Mar 16th Bonanza 2019
157 Virginia Commonwealth Win 15-4 0.44 6.1% Mar 16th Bonanza 2019
82 Georgetown Win 13-7 25.24 6.1% Mar 17th Bonanza 2019
27 Delaware Loss 8-12 -3.99 6.1% Mar 17th Bonanza 2019
47 Williams Loss 9-11 -10.25 6.1% Mar 17th Bonanza 2019
157 Virginia Commonwealth Win 13-3 0.5 6.84% Mar 30th Atlantic Coast Open 2019
259 East Carolina** Win 13-5 0 0% Ignored Mar 30th Atlantic Coast Open 2019
130 Connecticut Win 12-2 11.06 6.57% Mar 30th Atlantic Coast Open 2019
182 George Mason** Win 12-3 0 0% Ignored Mar 30th Atlantic Coast Open 2019
157 Virginia Commonwealth Win 11-3 0.45 6.28% Mar 31st Atlantic Coast Open 2019
71 William & Mary Win 13-12 1.21 6.84% Mar 31st Atlantic Coast Open 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.