(4) #13 Pittsburgh (10-8) OV 2

1994.81 (53)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
6 Georgia Tech Loss 5-9 -22.47 10 5.43% Counts Feb 8th Queen City Tune Up 2020 Women
105 Appalachian State** Win 13-3 0 27 0% Ignored (Why) Feb 8th Queen City Tune Up 2020 Women
2 North Carolina Loss 5-11 -6.67 2 5.8% Counts (Why) Feb 8th Queen City Tune Up 2020 Women
32 William & Mary Win 11-3 15.14 35 5.8% Counts (Why) Feb 8th Queen City Tune Up 2020 Women
33 North Carolina State Win 10-4 14.24 5 5.52% Counts (Why) Feb 9th Queen City Tune Up 2020 Women
21 Vermont Win 12-5 38.43 13 6.75% Counts (Why) Feb 22nd Commonwealth Cup 2020 Weekend 2
25 Georgia Loss 8-13 -54.16 5 7.03% Counts Feb 22nd Commonwealth Cup 2020 Weekend 2
7 Ohio State Win 11-10 17.93 3 7.03% Counts Feb 22nd Commonwealth Cup 2020 Weekend 2
2 North Carolina Loss 9-11 18.35 2 7.03% Counts Feb 22nd Commonwealth Cup 2020 Weekend 2
2 North Carolina Loss 8-15 -5.53 2 7.03% Counts Feb 23rd Commonwealth Cup 2020 Weekend 2
8 Northeastern Win 14-12 25.18 12 7.03% Counts Feb 23rd Commonwealth Cup 2020 Weekend 2
55 Columbia** Win 12-4 0 77 0% Ignored (Why) Feb 23rd Commonwealth Cup 2020 Weekend 2
14 UCLA Loss 4-10 -44.51 73 6.84% Counts (Why) Mar 7th Stanford Invite 2020
4 California-San Diego Loss 5-9 -20.61 34 6.72% Counts Mar 7th Stanford Invite 2020
58 California-Santa Cruz Win 10-6 -10.21 91 7.18% Counts (Why) Mar 7th Stanford Invite 2020
1 Carleton College Loss 6-9 7.59 112 6.95% Counts Mar 7th Stanford Invite 2020
17 British Columbia Win 11-8 27.63 7.83% Counts Mar 8th Stanford Invite 2020
60 Oregon** Win 13-5 0 58 0% Ignored (Why) Mar 8th Stanford Invite 2020
**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.