#202 Chili Poppers (8-15)

avg: 692.01  •  sd: 66.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
107 blOKC party Loss 2-11 546.65 Jun 15th Texas Two Finger 2019
26 Public Enemy** Loss 3-11 1098.29 Ignored Jun 15th Texas Two Finger 2019
211 Mud Turtles Loss 3-11 50.27 Jun 15th Texas Two Finger 2019
123 Impact Loss 5-11 477.49 Jun 15th Texas Two Finger 2019
75 Bexar Loss 7-15 673.51 Jul 13th Riverside Classic 2019
276 Alpha Win 13-8 736.73 Jul 13th Riverside Classic 2019
169 Wildstyle Win 13-11 1040.13 Jul 13th Riverside Classic 2019
256 Balloon Win 15-7 977.86 Jul 14th Riverside Classic 2019
104 Moontower Loss 3-15 559.12 Jul 14th Riverside Classic 2019
169 Wildstyle Loss 2-15 211.29 Jul 14th Riverside Classic 2019
107 blOKC party Loss 3-15 546.65 Jul 27th PBJ 2019
256 Balloon Win 15-8 942.66 Jul 27th PBJ 2019
104 Moontower Loss 9-15 643.64 Jul 27th PBJ 2019
100 Risky Business Loss 6-15 569 Jul 28th PBJ 2019
211 Mud Turtles Win 15-10 1103.87 Jul 28th PBJ 2019
227 Discney Loss 11-14 256.85 Jul 28th PBJ 2019
26 Public Enemy** Loss 3-17 1098.29 Ignored Sep 7th Texas Mixed Club Sectional Championship 2019
227 Discney Win 12-10 808.31 Sep 7th Texas Mixed Club Sectional Championship 2019
45 Waterloo** Loss 4-13 893.19 Ignored Sep 7th Texas Mixed Club Sectional Championship 2019
149 Tex Mix Loss 9-11 677.47 Sep 8th Texas Mixed Club Sectional Championship 2019
221 Tlacuaches Win 9-6 1018.62 Sep 8th Texas Mixed Club Sectional Championship 2019
169 Wildstyle Win 9-6 1229.86 Sep 8th Texas Mixed Club Sectional Championship 2019
149 Tex Mix Loss 1-12 326.68 Sep 8th Texas Mixed Club Sectional Championship 2019
**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)