#194 Freetail (10-9)

avg: 607.61  •  sd: 54.25  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
116 Moontower Loss 8-15 471.24 Aug 4th PBJ 2018
216 Mud Turtles Win 12-8 926.34 Aug 4th PBJ 2018
221 Chili Poppers Win 14-8 932.69 Aug 4th PBJ 2018
204 Spring Creek Ascension Loss 9-11 297.32 Aug 5th PBJ 2018
221 Chili Poppers Win 13-12 521.65 Aug 5th PBJ 2018
178 Balloon Win 13-12 813.3 Aug 5th PBJ 2018
227 Mixfits Win 14-11 646.77 Aug 18th Riverside Classic 2018
97 tHUMP Loss 3-15 539.88 Aug 18th Riverside Classic 2018
204 Spring Creek Ascension Win 11-10 671.53 Aug 18th Riverside Classic 2018
178 Balloon Win 12-11 813.3 Aug 19th Riverside Classic 2018
64 Sellout** Loss 1-15 688.24 Ignored Aug 19th Riverside Classic 2018
97 tHUMP Loss 4-15 539.88 Aug 19th Riverside Classic 2018
227 Mixfits Win 7-6 458.44 Sep 8th Texas Mixed Sectional Championship 2018
49 Cosa Nostra** Loss 3-10 771.79 Ignored Sep 8th Texas Mixed Sectional Championship 2018
97 tHUMP Loss 5-9 610.82 Sep 8th Texas Mixed Sectional Championship 2018
216 Mud Turtles Win 11-4 1085.18 Sep 9th Texas Mixed Sectional Championship 2018
216 Mud Turtles Win 10-9 610.18 Sep 9th Texas Mixed Sectional Championship 2018
178 Balloon Loss 8-11 322.69 Sep 9th Texas Mixed Sectional Championship 2018
204 Spring Creek Ascension Loss 5-8 92.93 Sep 9th Texas Mixed Sectional Championship 2018
**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)