(14) #67 Virginia Tech (11-10)

1553.29 (99)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
2 Brigham Young** Loss 4-13 0 3 0% Ignored (Why) Feb 3rd Florida Warm Up 2023
88 Central Florida Loss 10-12 -15.41 18 4.13% Counts Feb 3rd Florida Warm Up 2023
34 Michigan Loss 9-13 -7.89 44 4.13% Counts Feb 3rd Florida Warm Up 2023
12 Minnesota Loss 5-13 -3.55 32 4.13% Counts (Why) Feb 4th Florida Warm Up 2023
39 Florida Loss 9-13 -9.94 16 4.13% Counts Feb 4th Florida Warm Up 2023
26 Georgia Tech Loss 11-13 3.72 1 4.13% Counts Feb 4th Florida Warm Up 2023
147 Connecticut Win 11-10 -11.46 8 4.13% Counts Feb 5th Florida Warm Up 2023
201 South Florida Win 13-6 -0.67 24 4.13% Counts (Why) Feb 5th Florida Warm Up 2023
150 George Washington Win 13-5 10.71 2 5.21% Counts (Why) Mar 4th Oak Creek Challenge 2023
248 Drexel** Win 13-3 0 21 0% Ignored (Why) Mar 4th Oak Creek Challenge 2023
157 Yale Loss 7-8 -26.85 12 4.63% Counts Mar 4th Oak Creek Challenge 2023
70 Lehigh Loss 8-13 -28.73 77 5.21% Counts Mar 5th Oak Creek Challenge 2023
124 Towson Win 13-2 17.36 66 5.21% Counts (Why) Mar 5th Oak Creek Challenge 2023
157 Yale Win 13-2 9.45 12 5.21% Counts (Why) Mar 5th Oak Creek Challenge 2023
162 American Win 13-4 10.62 83 6.56% Counts (Why) Apr 1st Atlantic Coast Open 2023
190 MIT Win 13-7 -0.29 27 6.56% Counts (Why) Apr 1st Atlantic Coast Open 2023
77 Temple Win 9-8 3.44 62 6.21% Counts Apr 1st Atlantic Coast Open 2023
33 Duke Loss 8-13 -18.18 34 6.56% Counts Apr 1st Atlantic Coast Open 2023
45 Georgetown Win 15-11 36.85 15 6.56% Counts Apr 2nd Atlantic Coast Open 2023
36 Penn State Win 13-12 24.54 9 6.56% Counts Apr 2nd Atlantic Coast Open 2023
33 Duke Loss 12-13 7.89 34 6.56% Counts Apr 2nd Atlantic Coast Open 2023
**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.