#146 Igneous Ultimate (8-16)

avg: 884.28  •  sd: 47.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
244 Natural Twenties Win 15-7 1007.71 Jun 29th Rose City Rumble 2019
125 Hive Loss 11-12 895.76 Jun 29th Rose City Rumble 2019
157 Choco Ghost House Loss 10-15 389.77 Jun 29th Rose City Rumble 2019
67 The Administrators Loss 9-11 1005.98 Jun 29th Rose City Rumble 2019
125 Hive Loss 10-14 622.05 Aug 3rd Kleinman Eruption 2019
37 Garage Sale** Loss 6-15 921.16 Ignored Aug 3rd Kleinman Eruption 2019
151 Fable Win 13-10 1190 Aug 3rd Kleinman Eruption 2019
239 Midnight Whiskey Win 15-8 994.59 Aug 3rd Kleinman Eruption 2019
161 Breakers Mark Win 10-8 1090.2 Aug 4th Kleinman Eruption 2019
95 Garbage Loss 8-13 627.09 Aug 4th Kleinman Eruption 2019
127 Platypi Loss 9-10 879.27 Aug 4th Kleinman Eruption 2019
82 Happy Hour Loss 8-11 825.53 Sep 7th Oregon Mixed Club Sectional Championship 2019
161 Breakers Mark Loss 8-10 564.86 Sep 7th Oregon Mixed Club Sectional Championship 2019
37 Garage Sale Loss 5-10 947.27 Sep 7th Oregon Mixed Club Sectional Championship 2019
223 Eugene Skyfall Win 13-3 1136.22 Sep 7th Oregon Mixed Club Sectional Championship 2019
125 Hive Loss 10-12 782.63 Sep 8th Oregon Mixed Club Sectional Championship 2019
223 Eugene Skyfall Win 16-14 744.51 Sep 8th Oregon Mixed Club Sectional Championship 2019
276 SkyLab** Win 15-2 788.46 Ignored Sep 8th Oregon Mixed Club Sectional Championship 2019
25 Lights Out Loss 6-13 1043.79 Sep 21st Northwest Club Mixed Regional Championship
11 Lochsa** Loss 5-13 1198.08 Ignored Sep 21st Northwest Club Mixed Regional Championship
67 The Administrators Loss 10-13 927.04 Sep 21st Northwest Club Mixed Regional Championship
119 Bulleit Train Loss 10-12 815.65 Sep 22nd Northwest Club Mixed Regional Championship
157 Choco Ghost House Win 15-7 1443.38 Sep 22nd Northwest Club Mixed Regional Championship
108 Surge Loss 8-15 519.17 Sep 22nd Northwest Club Mixed Regional Championship
**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)