#17 SoCal Condors (16-6)

avg: 1681.02  •  sd: 111.42  •  top 16/20: 64.2%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
12 Rhino Slam Loss 8-13 1283.51 Jul 7th TCT Pro Elite Challenge 2018
11 DiG Loss 8-13 1301.09 Jul 7th TCT Pro Elite Challenge 2018
13 Johnny Bravo Loss 9-13 1357.89 Jul 7th TCT Pro Elite Challenge 2018
5 Truck Stop Win 13-9 2355.43 Jul 8th TCT Pro Elite Challenge 2018
16 Madison Club Loss 11-13 1463.67 Jul 8th TCT Pro Elite Challenge 2018
25 Medicine Men Win 10-9 1530.58 Jul 8th TCT Pro Elite Challenge 2018
27 Turbine Win 14-12 1613.14 Aug 18th TCT Elite Select Challenge 2018
18 Pittsburgh Temper Win 13-8 2167.56 Aug 18th TCT Elite Select Challenge 2018
20 Patrol Win 13-11 1769.54 Aug 18th TCT Elite Select Challenge 2018
14 GOAT Win 13-8 2211.26 Aug 19th TCT Elite Select Challenge 2018
2 Sockeye Loss 6-13 1435.16 Aug 19th TCT Elite Select Challenge 2018
74 DOGGPOUND Win 11-5 1597.3 Sep 8th So Cal Mens Sectional Championship 2018
81 Sundowners Win 11-5 1547.72 Sep 8th So Cal Mens Sectional Championship 2018
40 Streetgang Win 11-7 1741.99 Sep 8th So Cal Mens Sectional Championship 2018
40 Streetgang Win 13-8 1771.26 Sep 9th So Cal Mens Sectional Championship 2018
91 Sprawl Win 11-7 1364.26 Sep 9th So Cal Mens Sectional Championship 2018
144 Gridlock** Win 11-2 1068.25 Ignored Sep 9th So Cal Mens Sectional Championship 2018
74 DOGGPOUND Win 15-7 1597.3 Sep 22nd Southwest Mens Regional Championship 2018
86 Green River Swordfish** Win 15-5 1522.11 Ignored Sep 22nd Southwest Mens Regional Championship 2018
40 Streetgang Win 15-11 1656.26 Sep 22nd Southwest Mens Regional Championship 2018
1 Revolver Loss 11-15 1698.48 Sep 23rd Southwest Mens Regional Championship 2018
19 Guerrilla Win 15-11 1929.06 Sep 23rd Southwest Mens Regional Championship 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)