(60) #187 College of New Jersey (13-6)

1163.42 (19)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
359 Bentley** Win 9-1 0 172 0% Ignored (Why) Mar 2nd Philly Special 2024
259 Brandeis Win 7-2 13.06 185 3.58% Counts (Why) Mar 2nd Philly Special 2024
240 SUNY-Albany Win 3-1 9.84 222 2.27% Counts (Why) Mar 2nd Philly Special 2024
115 Bowdoin Win 11-9 27.16 221 4.94% Counts Mar 3rd Philly Special 2024
188 Brown-B Win 9-8 6.12 97 4.67% Counts Mar 3rd Philly Special 2024
272 Rowan Win 12-9 2.01 345 4.94% Counts Mar 3rd Philly Special 2024
130 Penn State-B Loss 9-11 -1.73 13 4.94% Counts Mar 3rd Philly Special 2024
213 Ithaca Win 8-6 12 59 5.34% Counts Mar 30th Northeast Classic 2024
181 SUNY-Cortland Loss 5-8 -23 145 5.15% Counts Mar 30th Northeast Classic 2024
159 Rhode Island Win 9-8 15.62 262 5.89% Counts Mar 31st Northeast Classic 2024
136 Wesleyan Loss 8-9 5.03 383 5.89% Counts Mar 31st Northeast Classic 2024
108 Vermont-B Win 11-9 37.21 239 6.22% Counts Mar 31st Northeast Classic 2024
- Manhattan** Win 15-0 0 0% Ignored (Why) Apr 13th Metro NY D III Mens Conferences 2024
310 Stevens Tech Win 15-5 8.67 181 6.98% Counts (Why) Apr 13th Metro NY D III Mens Conferences 2024
252 Hamilton Win 15-10 18.8 7.84% Counts Apr 27th Metro East D III College Mens Regionals 2024
364 Rensselaer Polytech Win 14-7 -12.61 415 7.84% Counts (Why) Apr 27th Metro East D III College Mens Regionals 2024
199 Connecticut College Loss 11-12 -13.84 237 7.84% Counts Apr 27th Metro East D III College Mens Regionals 2024
245 Skidmore Loss 8-15 -63.81 274 7.84% Counts Apr 27th Metro East D III College Mens Regionals 2024
267 SUNY-Geneseo Loss 12-14 -43.63 234 7.84% Counts Apr 28th Metro East D III College Mens Regionals 2024
**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.