#199 Jabba (9-17)

avg: 636.72  •  sd: 43.13  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
26 The Chad Larson Experience** Loss 1-13 1041.97 Ignored Jun 29th Spirit of the Plains 2019
60 Pretty Boys and Handsome Girls Loss 8-13 806.88 Jun 29th Spirit of the Plains 2019
287 Ope!** Win 13-4 623.57 Ignored Jun 29th Spirit of the Plains 2019
107 Shakedown Loss 1-8 492.86 Jun 30th Spirit of the Plains 2019
139 Tequila Mockingbird Loss 7-8 783.67 Jun 30th Spirit of the Plains 2019
256 Robotic Snakes Win 9-4 918.62 Jun 30th Spirit of the Plains 2019
156 EMU Loss 8-9 721 Aug 3rd Heavyweights 2019
175 Prion Loss 10-11 616.33 Aug 3rd Heavyweights 2019
112 Pandamonium Loss 8-13 570.94 Aug 3rd Heavyweights 2019
279 Identity Theft Win 13-7 712.85 Aug 4th Heavyweights 2019
250 Mishigami Loss 9-13 -55.14 Aug 4th Heavyweights 2019
176 Mousetrap Loss 8-13 236.27 Aug 4th Heavyweights 2019
225 Boomtown Pandas Win 11-10 644.51 Aug 17th Cooler Classic 31
137 Mad Udderburn Loss 11-13 698.72 Aug 17th Cooler Classic 31
256 Robotic Snakes Win 13-11 547.46 Aug 17th Cooler Classic 31
182 Rocket LawnChair Loss 11-12 588.72 Aug 17th Cooler Classic 31
168 ELevate Win 7-6 905.15 Aug 18th Cooler Classic 31
156 EMU Loss 5-6 721 Aug 18th Cooler Classic 31
137 Mad Udderburn Loss 8-9 802.56 Aug 18th Cooler Classic 31
156 EMU Loss 8-13 349.84 Sep 7th Central Plains Mixed Club Sectional Championship 2019
23 U54 Ultimate** Loss 1-13 1053.2 Ignored Sep 7th Central Plains Mixed Club Sectional Championship 2019
132 Liquid Hustle Loss 9-13 548.9 Sep 7th Central Plains Mixed Club Sectional Championship 2019
249 Skyhawks Win 12-10 614.86 Sep 7th Central Plains Mixed Club Sectional Championship 2019
156 EMU Loss 13-15 631.82 Sep 8th Central Plains Mixed Club Sectional Championship 2019
217 Stackcats Win 15-10 1022.12 Sep 8th Central Plains Mixed Club Sectional Championship 2019
175 Prion Win 14-13 866.33 Sep 8th Central Plains 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)