#18 Phoenix (21-9)

avg: 1697.67  •  sd: 73.15  •  top 16/20: 98.9%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
63 Taco Truck** Win 13-3 1166.83 Ignored Jun 16th Cackalacky Challenge 2018
- Warhawks Win 13-7 1151.93 Jun 16th Cackalacky Challenge 2018
29 Virginia Rebellion Win 13-7 1913.98 Jun 17th Cackalacky Challenge 2018
- Ripe Win 11-10 1715.91 Jun 17th Cackalacky Challenge 2018
- Ripe Win 11-9 1840.12 Jun 17th Cackalacky Challenge 2018
12 Traffic Win 13-8 2265.23 Jul 7th TCT Pro Elite Challenge 2018
9 Schwa Win 13-11 2066.81 Jul 7th TCT Pro Elite Challenge 2018
19 Pop Win 13-8 2175.48 Jul 7th TCT Pro Elite Challenge 2018
16 Heist Win 10-9 1847.08 Jul 8th TCT Pro Elite Challenge 2018
4 Seattle Riot Loss 7-13 1706.24 Jul 8th TCT Pro Elite Challenge 2018
5 Scandal Loss 7-13 1545.57 Jul 8th TCT Pro Elite Challenge 2018
15 Wildfire Win 9-8 1848.35 Aug 18th TCT Elite Select Challenge 2018
19 Pop Win 13-12 1804.32 Aug 18th TCT Elite Select Challenge 2018
25 Colorado Small Batch Win 10-9 1572.1 Aug 18th TCT Elite Select Challenge 2018
11 Rival Win 13-11 2033.02 Aug 19th TCT Elite Select Challenge 2018
10 Nemesis Win 13-11 2053.32 Aug 19th TCT Elite Select Challenge 2018
63 Taco Truck** Win 13-3 1166.83 Ignored Sep 8th North Carolina Womens Sectional Championship 2018
37 Fiasco Win 15-9 1612.06 Sep 22nd Southeast Womens Regional Championship 2018
63 Taco Truck** Win 15-2 1166.83 Ignored Sep 22nd Southeast Womens Regional Championship 2018
40 Steel** Win 15-3 1641 Ignored Sep 22nd Southeast Womens Regional Championship 2018
7 Ozone Loss 7-15 1336.53 Sep 23rd Southeast Womens Regional Championship 2018
27 Tabby Rosa Win 14-10 1780.25 Sep 23rd Southeast Womens Regional Championship 2018
27 Tabby Rosa Win 15-11 1762.71 Sep 23rd Southeast Womens Regional Championship 2018
12 Traffic Loss 9-15 1253.59 Oct 18th USA Ultimate National Championships 2018
2 Fury Loss 9-15 1845.23 Oct 18th USA Ultimate National Championships 2018
6 6ixers Loss 8-15 1451.54 Oct 18th USA Ultimate National Championships 2018
16 Heist Win 11-9 1971.29 Oct 19th USA Ultimate National Championships 2018
10 Nemesis Loss 11-15 1443.32 Oct 19th USA Ultimate National Championships 2018
9 Schwa Loss 9-12 1492.6 Oct 19th USA Ultimate National Championships 2018
11 Rival Loss 13-15 1590.01 Oct 20th USA Ultimate National Championships 2018
**Blowout Eligible

FAQ

The uncertainty of the mean is equal to the standard deviation of the set of game ratings, divided by the square root of the number of games. We treated a team’s ranking as a normally distributed random variable, with the USAU ranking as the mean and the uncertainty of the ranking as the standard deviation
  1. Calculate uncertainy for USAU ranking averge
  2. Model ranking as a normal distribution around USAU averge with standard deviation equal to uncertainty
  3. Simulate seasons by drawing a rank for each team from their distribution. Note the teams in the top 16 (club) or top 20 (college)
  4. Sum the fractions for each region for how often each of it's teams appeared in the top 16 (club) or top 20 (college)
  5. Subtract one from each fraction for "autobids"
  6. Award remainings bids to the regions with the highest remaining fraction, subtracting one from the fraction each time a bid is awarded
There is an article on Ulitworld written by Scott Dunham and I that gives a little more context (though it probably was the thing that linked you here)