#162 Fear and Loathing (4-13)

avg: 797.89  •  sd: 59.25  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
110 California Burrito Loss 4-11 467.08 Aug 4th Coconino Classic 2018
62 Long Beach Legacy Loss 7-10 902.13 Aug 4th Coconino Classic 2018
109 Superstition Loss 3-11 472.46 Aug 4th Coconino Classic 2018
200 Rogue Win 11-2 1172.74 Aug 4th Coconino Classic 2018
52 Instant Karma Loss 3-11 745.05 Aug 5th Coconino Classic 2018
170 Spoiler Alert Win 12-9 1103.89 Aug 5th Coconino Classic 2018
43 Flight Club** Loss 5-13 873.13 Ignored Aug 18th Ski Town Classic 2018
120 Mimosas Loss 9-13 604.39 Aug 18th Ski Town Classic 2018
46 The Administrators Loss 6-13 795.8 Aug 18th Ski Town Classic 2018
48 Rubix Loss 5-10 804.94 Aug 18th Ski Town Classic 2018
199 Wasatch Sasquatch Win 13-10 906.49 Aug 19th Ski Town Classic 2018
138 The Strangers Loss 10-13 611.42 Aug 19th Ski Town Classic 2018
52 Instant Karma Loss 2-13 745.05 Sep 8th So Cal Mixed Sectional Championship 2018
170 Spoiler Alert Loss 11-12 633.52 Sep 8th So Cal Mixed Sectional Championship 2018
109 Superstition Win 12-11 1197.46 Sep 8th So Cal Mixed Sectional Championship 2018
47 ROBOS Loss 4-13 787.34 Sep 9th So Cal Mixed Sectional Championship 2018
48 Rubix Loss 3-13 778.83 Sep 9th So Cal 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)