(3) #62 Central Florida (18-6)

1798.88 (437)

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# Opponent Result Effect % of Ranking Status Date Event
180 South Florida** Win 11-0 0 0% Ignored Jan 13th Florida Winter Classic 2018
141 North Georgia Win 8-2 1.75 3.85% Jan 13th Florida Winter Classic 2018
174 Florida-B** Win 12-0 0 0% Ignored Jan 13th Florida Winter Classic 2018
48 Georgia Loss 5-9 -16.53 4.25% Jan 13th Florida Winter Classic 2018
54 Florida State Loss 8-9 -3.33 4.68% Jan 14th Florida Winter Classic 2018
89 Iowa Win 6-4 5.11 3.59% Jan 14th Florida Winter Classic 2018
134 Tennessee Win 8-3 3.09 3.85% Jan 14th Florida Winter Classic 2018
135 William & Mary Win 10-7 -9.61 6.62% Feb 24th Commonwealth Cup 2018
148 Virginia Tech Win 11-6 -4.44 6.62% Feb 24th Commonwealth Cup 2018
59 South Carolina Loss 3-13 -43 7% Feb 24th Commonwealth Cup 2018
7 Tufts** Loss 1-13 0 0% Ignored Feb 25th Commonwealth Cup 2018
88 Georgetown Win 10-9 -7.17 7% Feb 25th Commonwealth Cup 2018
31 Penn State Loss 4-9 -19.23 5.79% Feb 25th Commonwealth Cup 2018
170 North Carolina-Asheville** Win 13-0 0 0% Ignored Mar 3rd Cola Classic 2018
39 Clemson Loss 6-9 -14 6.59% Mar 3rd Cola Classic 2018
141 North Georgia Win 9-2 2.86 6.14% Mar 3rd Cola Classic 2018
90 Georgia College Win 10-6 18.97 6.81% Mar 3rd Cola Classic 2018
226 North Carolina-B** Win 12-4 0 0% Ignored Mar 4th Cola Classic 2018
59 South Carolina Win 5-3 22.64 4.81% Mar 4th Cola Classic 2018
124 Carleton College-Eclipse Win 12-4 13.35 7.99% Mar 17th College Southerns 2018
271 Charleston** Win 13-0 0 0% Ignored Mar 17th College Southerns 2018
174 Florida-B** Win 13-0 0 0% Ignored Mar 17th College Southerns 2018
108 Wisconsin-Eau Claire Win 13-3 22.55 8.33% Mar 18th College Southerns 2018
54 Florida State Win 6-4 27.19 6.04% Mar 18th College Southerns 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.