#121 Igneous Ultimate (10-12)

avg: 1020.64  •  sd: 29.8  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
75 Happy Hour Loss 8-9 1132.58 Jul 7th Rose City Rumble 2
174 Breakers Mark Win 12-9 1080.77 Jul 7th Rose City Rumble 2
168 Oh My! Win 13-8 1265.8 Jul 7th Rose City Rumble 2
46 The Administrators Loss 9-12 1050.43 Jul 7th Rose City Rumble 2
80 Garbage Loss 8-10 977.42 Aug 4th Kleinman Eruption 2018
81 Pegasus Win 10-9 1362.29 Aug 4th Kleinman Eruption 2018
168 Oh My! Win 12-7 1290.16 Aug 4th Kleinman Eruption 2018
23 Lights Out Loss 6-13 1014.46 Aug 4th Kleinman Eruption 2018
75 Happy Hour Loss 12-14 1036.62 Aug 5th Kleinman Eruption 2018
143 Bulleit Train Win 13-10 1219.74 Aug 5th Kleinman Eruption 2018
46 The Administrators Loss 11-12 1270.8 Aug 5th Kleinman Eruption 2018
- Natural Twenties** Win 13-4 943.23 Ignored Sep 8th Oregon Mixed Sectional Championship 2018
75 Happy Hour Loss 8-13 761.42 Sep 8th Oregon Mixed Sectional Championship 2018
168 Oh My! Win 12-11 894.64 Sep 8th Oregon Mixed Sectional Championship 2018
- Portland Waldorf Win 13-12 703.13 Sep 8th Oregon Mixed Sectional Championship 2018
174 Breakers Mark Win 13-8 1231.56 Sep 9th Oregon Mixed Sectional Championship 2018
46 The Administrators Loss 9-13 977.23 Sep 9th Oregon Mixed Sectional Championship 2018
13 Birdfruit Loss 6-13 1179.29 Sep 22nd Northwest Mixed Regional Championship 2018
44 Bozos Loss 4-11 860.67 Sep 22nd Northwest Mixed Regional Championship 2018
106 Choco Ghost House Loss 7-13 523.21 Sep 22nd Northwest Mixed Regional Championship 2018
123 Image.Is.Everything. Loss 10-13 685.14 Sep 23rd Northwest Mixed Regional Championship 2018
168 Oh My! Win 13-5 1369.64 Sep 23rd Northwest Mixed Regional 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)