#93 Brawl (11-2)

avg: 1031.28  •  sd: 78.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
124 BARNSTORM Win 12-11 905.71 Jun 28th Texas 2 FingerOpen
127 NOx Win 11-6 1288.13 Jun 28th Texas 2 FingerOpen
175 Supercell** Win 13-3 784.45 Ignored Jun 28th Texas 2 FingerOpen
51 Alamode Loss 7-15 884.3 Jun 29th Texas 2 FingerOpen
99 Texas Tea-A Win 15-9 1490.49 Jun 29th Texas 2 FingerOpen
77 Cowtown Cannons Win 14-11 1456.47 Jun 29th Texas 2 FingerOpen
154 Bonzaiiiii!! Win 13-9 927.83 Jul 12th Riverside Classic 2025
155 Texas United Win 6-3 1049.06 Jul 12th Riverside Classic 2025
125 Riverside Win 10-9 896.07 Jul 12th Riverside Classic 2025
160 Forge** Win 10-3 1026.97 Ignored Jul 12th Riverside Classic 2025
173 Dallas Delinquents** Win 15-2 812.19 Ignored Jul 13th Riverside Classic 2025
77 Cowtown Cannons Loss 7-15 543.13 Jul 13th Riverside Classic 2025
125 Riverside Win 2-1 896.07 Jul 13th Riverside Classic 2025
**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)