#206 Varsity (3-13)

avg: 542.7  •  sd: 56.28  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
156 Heavy Flow Loss 5-10 265.66 Aug 11th Philly Open 2018
232 Baltimore BENCH Win 9-4 889.24 Aug 11th Philly Open 2018
83 Birds Loss 7-10 835.88 Aug 11th Philly Open 2018
224 Stormborn Win 7-3 957.45 Aug 11th Philly Open 2018
99 Legion Loss 11-12 990.26 Aug 12th Philly Open 2018
158 Philly Twist Loss 7-8 690.1 Aug 12th Philly Open 2018
141 Powermove Loss 6-11 346.82 Aug 12th Philly Open 2018
139 Nautilus Loss 7-13 358.36 Aug 18th Chowdafest 2018
180 HAOS Win 10-9 804.94 Aug 18th Chowdafest 2018
53 Darkwing** Loss 3-13 734.27 Ignored Aug 18th Chowdafest 2018
181 RIMIX Loss 9-10 547.36 Aug 19th Chowdafest 2018
133 Townies Loss 7-11 494.26 Aug 19th Chowdafest 2018
150 Scarecrow Loss 6-10 371.24 Aug 19th Chowdafest 2018
181 RIMIX Loss 7-10 282.7 Aug 19th Chowdafest 2018
127 Funk Loss 7-13 423.35 Sep 8th Metro New York Mixed Sectional Championship 2018
- TBD Loss 9-12 157.89 Sep 8th Metro New York Mixed Sectional 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)