#9 Doublewide (15-6)

avg: 2106.81  •  sd: 84.16  •  top 16/20: 99%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
203 Shrimp Discs** Win 13-2 1252.03 Ignored Jun 24th Texas 2 Finger 2023
218 Supercell** Win 13-0 1132.83 Ignored Jun 24th Texas 2 Finger 2023
68 Brawl** Win 13-3 2018.55 Ignored Jun 24th Texas 2 Finger 2023
48 Alamode Win 11-4 2156.94 Jun 25th Texas 2 Finger 2023
122 Lil Heroes** Win 13-3 1688.43 Ignored Jun 25th Texas 2 Finger 2023
69 Clutch Win 13-9 1828.96 Jun 25th Texas 2 Finger 2023
51 TireBizFriz Win 13-10 1880.64 Jul 15th TCT Pro Elite Challenge East 2023
34 Trident I Win 13-10 1989.95 Jul 15th TCT Pro Elite Challenge East 2023
12 Raleigh-Durham United Win 14-10 2405.33 Jul 15th TCT Pro Elite Challenge East 2023
7 DiG Loss 12-13 2042.51 Jul 16th TCT Pro Elite Challenge East 2023
10 Rhino Slam! Loss 13-14 1960.8 Sep 2nd TCT Pro Championships 2023
6 Ring of Fire Win 15-12 2481.15 Sep 2nd TCT Pro Championships 2023
5 Chicago Machine Loss 10-15 1736.1 Sep 2nd TCT Pro Championships 2023
1 Truck Stop Loss 13-15 2285.05 Sep 3rd TCT Pro Championships 2023
2 PoNY Loss 10-15 1880.33 Sep 3rd TCT Pro Championships 2023
8 Johnny Bravo Loss 11-15 1731.61 Sep 3rd TCT Pro Championships 2023
5 Chicago Machine Win 15-13 2403.89 Sep 4th TCT Pro Championships 2023
48 Alamode Win 15-5 2156.94 Sep 23rd 2023 South Central Mens Regional Championship
125 Cowtown Cannons** Win 15-2 1656.61 Ignored Sep 23rd 2023 South Central Mens Regional Championship
68 Brawl Win 15-7 2018.55 Sep 23rd 2023 South Central Mens Regional Championship
8 Johnny Bravo Win 12-8 2553.93 Sep 24th 2023 South Central Mens Regional Championship
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)