#204 Spring Creek Ascension (6-12)

avg: 546.53  •  sd: 70.35  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
167 Wildstyle Loss 9-15 267.81 Aug 4th PBJ 2018
118 Risky Business Loss 10-15 577.8 Aug 4th PBJ 2018
178 Balloon Win 14-12 909.26 Aug 4th PBJ 2018
167 Wildstyle Loss 10-14 384.59 Aug 5th PBJ 2018
194 Freetail Win 11-9 856.81 Aug 5th PBJ 2018
118 Risky Business Loss 10-15 577.8 Aug 5th PBJ 2018
227 Mixfits Win 9-8 458.44 Aug 18th Riverside Classic 2018
194 Freetail Loss 10-11 482.61 Aug 18th Riverside Classic 2018
97 tHUMP Loss 5-15 539.88 Aug 18th Riverside Classic 2018
116 Moontower Loss 3-15 436.05 Aug 19th Riverside Classic 2018
216 Mud Turtles Loss 7-11 18.29 Aug 19th Riverside Classic 2018
216 Mud Turtles Win 7-4 981.34 Sep 8th Texas Mixed Sectional Championship 2018
94 Tex Mix Loss 5-10 579.14 Sep 8th Texas Mixed Sectional Championship 2018
64 Sellout Loss 5-10 714.35 Sep 8th Texas Mixed Sectional Championship 2018
194 Freetail Win 8-5 1061.21 Sep 9th Texas Mixed Sectional Championship 2018
- Tlacuaches Loss 5-9 361.84 Sep 9th Texas Mixed Sectional Championship 2018
221 Chili Poppers Win 8-7 521.65 Sep 9th Texas Mixed Sectional Championship 2018
178 Balloon Loss 7-11 221.41 Sep 9th Texas 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)