() #133 Holy City Heathens (5-18)

606.4 (29)

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# Opponent Result Effect % of Ranking Status Date Event
140 ScooberDivers Win 13-6 19.82 3.69% Jul 7th Swan Boat 2018
44 El Niño Loss 7-8 17.43 3.28% Jul 7th Swan Boat 2018
128 Vicious Cycle Loss 9-10 -3.2 3.69% Jul 7th Swan Boat 2018
- Shore Break Win 13-7 3.36 3.69% Jul 7th Swan Boat 2018
137 Space Coast Ultimate Loss 11-13 -10.37 3.69% Jul 8th Swan Boat 2018
108 Swamp Horse Loss 8-15 -15.34 3.69% Jul 8th Swan Boat 2018
66 Bullet Loss 8-13 -2.61 4.11% Jul 21st Club Terminus 2018
61 Tanasi Loss 2-13 -4.74 4.11% Jul 21st Club Terminus 2018
97 Rush Hour Loss 5-10 -12.48 3.65% Jul 22nd Club Terminus 2018
165 War Machine Win 11-4 3.81 3.77% Jul 22nd Club Terminus 2018
101 Memphis Belle Loss 7-13 -14.32 4.11% Jul 22nd Club Terminus 2018
55 Ironmen Loss 8-13 2.13 4.11% Jul 22nd Club Terminus 2018
107 BaNC Loss 9-12 -9.99 5.37% Aug 25th Rush Hour Round Robin 2018
98 Southern Hospitality Loss 9-12 -5.82 5.37% Aug 25th Rush Hour Round Robin 2018
34 Lost Boys Loss 6-11 8.35 5.08% Aug 25th Rush Hour Round Robin 2018
97 Rush Hour Loss 5-9 -13.73 4.61% Aug 26th Rush Hour Round Robin 2018
66 Bullet Loss 8-13 -3.46 5.37% Aug 26th Rush Hour Round Robin 2018
102 H.O.G. Ultimate Loss 10-11 5.45 5.37% Aug 26th Rush Hour Round Robin 2018
23 Freaks** Loss 5-13 0 0% Ignored Sep 8th East Coast Mens Sectional Championship 2018
34 Lost Boys Loss 6-13 6.53 5.97% Sep 8th East Coast Mens Sectional Championship 2018
61 Tanasi Win 10-9 39.02 5.97% Sep 8th East Coast Mens Sectional Championship 2018
102 H.O.G. Ultimate Loss 6-12 -22.1 5.81% Sep 8th East Coast Mens Sectional Championship 2018
160 Duel Win 11-2 12.67 5.48% Sep 9th East Coast Mens Sectional Championship 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.