(1) #51 Ohio State (16-10)

1537.69 (4)

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# Opponent Result Effect % of Ranking Status Date Event
234 Haverford Win 13-7 -5.73 3.21% Feb 3rd Mid Atlantic Warmup 2018
177 Virginia Commonwealth Win 13-4 2.8 3.21% Feb 3rd Mid Atlantic Warmup 2018
161 Boston University Win 13-2 4.98 3.21% Feb 3rd Mid Atlantic Warmup 2018
102 Richmond Loss 11-13 -14.58 3.21% Feb 3rd Mid Atlantic Warmup 2018
48 Dartmouth Loss 11-14 -9.47 3.21% Feb 4th Mid Atlantic Warmup 2018
115 Villanova Win 14-11 1.74 3.21% Feb 4th Mid Atlantic Warmup 2018
102 Richmond Win 10-9 -2.85 3.21% Feb 4th Mid Atlantic Warmup 2018
33 Maryland Loss 11-12 0.81 3.6% Feb 17th Easterns Qualifier 2018
46 South Carolina Loss 10-11 -3.12 3.6% Feb 17th Easterns Qualifier 2018
62 Vermont Win 13-9 12.96 3.6% Feb 17th Easterns Qualifier 2018
84 Virginia Win 13-11 3.49 3.6% Feb 17th Easterns Qualifier 2018
75 Tennessee-Chattanooga Loss 8-13 -23.11 3.6% Feb 17th Easterns Qualifier 2018
40 Iowa Loss 12-13 -1.42 3.6% Feb 18th Easterns Qualifier 2018
98 Clemson Win 13-11 1.09 3.6% Feb 18th Easterns Qualifier 2018
78 Georgetown Win 11-9 4.73 3.6% Feb 18th Easterns Qualifier 2018
45 Illinois State Loss 8-15 -21.77 4.04% Mar 3rd Midwest Throwdown 2018
164 St John's Win 15-6 5.72 4.04% Mar 3rd Midwest Throwdown 2018
69 Carleton College-GoP Win 15-13 5.31 4.04% Mar 3rd Midwest Throwdown 2018
47 Iowa State Win 11-9 11.79 4.04% Mar 4th Midwest Throwdown 2018
170 Kansas State Win 15-5 5.14 4.04% Mar 4th Midwest Throwdown 2018
49 Marquette Win 15-7 25.74 4.04% Mar 4th Midwest Throwdown 2018
74 Washington University Win 15-3 20.27 4.04% Mar 4th Midwest Throwdown 2018
44 Illinois Win 12-8 26.45 5.1% Mar 31st Huck Finn 2018
45 Illinois State Loss 10-15 -21.76 5.1% Mar 31st Huck Finn 2018
29 Texas Loss 8-13 -17.33 5.1% Mar 31st Huck Finn 2018
39 Northwestern Loss 11-14 -11.94 5.1% Mar 31st Huck Finn 2018
**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.