#143 Bulleit Train (7-13)

avg: 891.6  •  sd: 68.99  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
75 Happy Hour Loss 5-13 657.58 Aug 4th Kleinman Eruption 2018
142 Fable Win 9-8 1016.61 Aug 4th Kleinman Eruption 2018
46 The Administrators Loss 5-10 821.9 Aug 4th Kleinman Eruption 2018
85 Platypi Win 11-10 1315.67 Aug 4th Kleinman Eruption 2018
121 Igneous Ultimate Loss 10-13 692.5 Aug 5th Kleinman Eruption 2018
168 Oh My! Win 14-7 1352.53 Aug 5th Kleinman Eruption 2018
23 Lights Out** Loss 6-15 1014.46 Ignored Aug 5th Kleinman Eruption 2018
199 Wasatch Sasquatch Win 13-4 1178.35 Aug 18th Ski Town Classic 2018
74 Alchemy Loss 2-11 665.2 Aug 18th Ski Town Classic 2018
110 California Burrito Loss 7-11 600.19 Aug 18th Ski Town Classic 2018
47 ROBOS Loss 6-10 891.18 Aug 18th Ski Town Classic 2018
69 Mental Toss Flycoons Loss 7-10 889.82 Aug 19th Ski Town Classic 2018
120 Mimosas Loss 4-10 422.95 Aug 19th Ski Town Classic 2018
- Mola Mola Win 11-4 984.98 Sep 8th Washington Mixed Sectional Championship 2018
80 Garbage Loss 7-11 773.19 Sep 8th Washington Mixed Sectional Championship 2018
123 Image.Is.Everything. Win 9-6 1431.85 Sep 8th Washington Mixed Sectional Championship 2018
23 Lights Out Loss 6-10 1118.3 Sep 8th Washington Mixed Sectional Championship 2018
- RuffSide Win 9-7 863.43 Sep 8th Washington Mixed Sectional Championship 2018
81 Pegasus Loss 7-12 716.78 Sep 9th Washington Mixed Sectional Championship 2018
96 Pheathers and Phurr Loss 6-12 560.65 Sep 9th Washington 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)