#100 Risky Business (13-10)

avg: 1169  •  sd: 64.97  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
75 Bexar Win 12-10 1511.64 Jun 15th Texas Two Finger 2019
256 Balloon** Win 15-4 977.86 Ignored Jun 15th Texas Two Finger 2019
49 Boomtown Loss 4-15 863.97 Jun 15th Texas Two Finger 2019
227 Discney Win 15-6 1170.18 Jul 27th PBJ 2019
211 Mud Turtles Win 15-4 1250.27 Jul 27th PBJ 2019
45 Waterloo Loss 6-15 893.19 Jul 27th PBJ 2019
107 blOKC party Loss 6-15 546.65 Jul 28th PBJ 2019
202 Chili Poppers Win 15-6 1292.01 Jul 28th PBJ 2019
104 Moontower Loss 10-15 705.52 Jul 28th PBJ 2019
22 Chalice Loss 4-13 1117.13 Aug 17th Cooler Classic 31
118 Stripes Win 13-10 1422.43 Aug 17th Cooler Classic 31
58 Toast Loss 6-13 785.08 Aug 17th Cooler Classic 31
154 Melt Win 13-1 1513.8 Aug 17th Cooler Classic 31
93 PanIC Loss 6-10 688.53 Aug 18th Cooler Classic 31
42 Woodwork Loss 8-10 1267.15 Aug 18th Cooler Classic 31
118 Stripes Win 11-5 1694.29 Aug 18th Cooler Classic 31
276 Alpha** Win 13-5 840.57 Ignored Sep 7th Texas Mixed Club Sectional Championship 2019
221 Tlacuaches Win 13-5 1200.05 Sep 7th Texas Mixed Club Sectional Championship 2019
104 Moontower Win 11-9 1408.33 Sep 7th Texas Mixed Club Sectional Championship 2019
149 Tex Mix Win 10-7 1316.34 Sep 7th Texas Mixed Club Sectional Championship 2019
75 Bexar Loss 6-9 854.95 Sep 8th Texas Mixed Club Sectional Championship 2019
45 Waterloo Loss 9-11 1243.98 Sep 8th Texas Mixed Club Sectional Championship 2019
104 Moontower Win 10-7 1548.79 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)