(20) #336 Texas-Dallas-B (8-18)

424.3 (15)

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# Opponent Result Effect % of Ranking Status Date Event
170 Kansas State** Loss 3-13 0 0% Ignored Feb 3rd Big D in Little d Open 2018
82 Oklahoma State** Loss 2-13 0 0% Ignored Feb 3rd Big D in Little d Open 2018
305 Oklahoma-B Win 12-3 27.11 3.55% Feb 3rd Big D in Little d Open 2018
287 Central Arkansas Loss 5-13 -14.71 3.7% Feb 3rd Big D in Little d Open 2018
27 Texas State** Loss 3-13 0 0% Ignored Feb 3rd Big D in Little d Open 2018
344 Dallas Loss 4-9 -19.91 3.06% Feb 4th Big D in Little d Open 2018
305 Oklahoma-B Win 15-10 22.68 3.7% Feb 4th Big D in Little d Open 2018
387 North Texas-B Win 15-5 13.8 3.7% Feb 4th Big D in Little d Open 2018
373 Creighton Win 6-4 7.68 3.19% Feb 24th Dust Bowl 2018
387 North Texas-B Win 8-3 12.73 3.42% Feb 24th Dust Bowl 2018
287 Central Arkansas Loss 10-12 -0.97 4.4% Feb 24th Dust Bowl 2018
128 Colorado School of Mines** Loss 1-11 0 0% Ignored Feb 24th Dust Bowl 2018
199 Stephen F Austin Loss 3-11 -3.78 4.04% Feb 24th Dust Bowl 2018
274 Arkansas State Loss 1-12 -14.23 4.22% Feb 25th Dust Bowl 2018
264 LSU-B Loss 4-13 -15.03 4.94% Mar 10th Mens Centex 2018
187 Texas A&M-B Loss 2-13 -2.22 4.94% Mar 10th Mens Centex 2018
258 Texas A&M-C Loss 6-12 -12.54 4.8% Mar 10th Mens Centex 2018
217 Texas Christian Loss 7-12 -2.93 4.94% Mar 11th Mens Centex 2018
297 Trinity University Win 11-10 15.28 4.94% Mar 11th Mens Centex 2018
284 Tulsa Loss 7-10 -9.26 5.24% Mar 24th Greatest Crusade IV
258 Texas A&M-C Loss 1-13 -15.78 5.54% Mar 24th Greatest Crusade IV
217 Texas Christian Loss 5-13 -7.98 5.54% Mar 24th Greatest Crusade IV
351 Texas-Arlington Loss 9-11 -18.19 5.54% Mar 24th Greatest Crusade IV
344 Dallas Win 13-7 30.89 5.54% Mar 25th Greatest Crusade IV
338 Abilene Christian University Loss 10-11 -8.09 5.54% Mar 25th Greatest Crusade IV
379 Southern Methodist Win 12-8 14.93 5.54% Mar 25th Greatest Crusade IV
**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.