(17) #255 Wake Forest (7-12)

586.48 (9)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
149 Davidson Loss 4-13 -6.97 54 5.03% Counts (Why) Feb 15th 2025 Commonwealth Cup Weekend 1
241 Michigan-B Win 8-7 8.45 180 4.47% Counts Feb 15th 2025 Commonwealth Cup Weekend 1
131 Pittsburgh-B Loss 7-12 0.76 64 5.03% Counts Feb 15th 2025 Commonwealth Cup Weekend 1
256 Illinois-B Win 7-5 13.41 41 3.99% Counts Feb 16th 2025 Commonwealth Cup Weekend 1
187 North Carolina-B Win 9-6 32.56 79 4.47% Counts Feb 16th 2025 Commonwealth Cup Weekend 1
164 Ohio Loss 5-10 -8.58 115 4.47% Counts Feb 16th 2025 Commonwealth Cup Weekend 1
247 George Washington Win 9-6 29.03 38 5.96% Counts Mar 22nd Atlantic Coast Open 2025
113 Lehigh Loss 9-15 7.36 4 6.71% Counts Mar 22nd Atlantic Coast Open 2025
138 RIT Loss 3-15 -6.73 21 6.71% Counts (Why) Mar 22nd Atlantic Coast Open 2025
43 Virginia Tech** Loss 1-15 0 19 0% Ignored (Why) Mar 22nd Atlantic Coast Open 2025
139 Florida State Loss 4-15 -7.39 59 6.71% Counts (Why) Mar 23rd Atlantic Coast Open 2025
159 George Mason Loss 5-15 -13.57 43 6.71% Counts (Why) Mar 23rd Atlantic Coast Open 2025
170 Massachusetts -B Loss 4-10 -14.11 70 5.86% Counts (Why) Mar 23rd Atlantic Coast Open 2025
249 Cedarville Win 10-8 21.48 13 6.92% Counts Mar 29th Needle in a Ho Stack 2025
257 East Tennessee State Loss 11-15 -29.65 335 7.11% Counts Mar 29th Needle in a Ho Stack 2025
344 South Carolina-B Win 7-5 -7.71 190 5.65% Counts Mar 29th Needle in a Ho Stack 2025
94 Tennessee-Chattanooga** Loss 5-13 0 4 0% Ignored (Why) Mar 29th Needle in a Ho Stack 2025
345 Georgia College Win 14-9 0.75 30 7.11% Counts Mar 30th Needle in a Ho Stack 2025
199 North Carolina State-B Loss 8-13 -20.32 404 7.11% Counts Mar 30th Needle in a Ho Stack 2025
**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.