#14 Doublewide (5-8)

avg: 1872.29  •  sd: 87.91  •  top 16/20: 80.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
39 Inception Win 13-6 2014.7 Jul 13th TCT Pro Elite Challenge 2019
15 Rhino Slam! Loss 13-14 1728.54 Jul 13th TCT Pro Elite Challenge 2019
2 Truck Stop Loss 6-13 1569.57 Jul 13th TCT Pro Elite Challenge 2019
8 GOAT Win 14-13 2122.22 Jul 14th TCT Pro Elite Challenge 2019
9 SoCal Condors Win 13-10 2298.53 Jul 14th TCT Pro Elite Challenge 2019
1 Sockeye Loss 5-13 1692.85 Jul 14th TCT Pro Elite Challenge 2019
5 Revolver Win 13-11 2338.47 Jul 14th TCT Pro Elite Challenge 2019
6 Sub Zero Loss 10-15 1609.65 Aug 31st TCT Pro Championships 2019
4 Ring of Fire Loss 11-14 1852.52 Aug 31st TCT Pro Championships 2019
12 Pittsburgh Temper Win 15-6 2489.86 Aug 31st TCT Pro Championships 2019
7 Chicago Machine Loss 9-15 1493.5 Sep 1st TCT Pro Championships 2019
10 DiG Loss 10-13 1638.9 Sep 1st TCT Pro Championships 2019
2 Truck Stop Loss 9-14 1695.7 Sep 1st TCT Pro Championships 2019
**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)