#240 Memphis Hustle & Flow (2-15)

avg: 144.49  •  sd: 131.74  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
213 Heartbreakers Loss 4-8 -65.82 Jul 7th Huckfest 2018
122 Huntsville Outlaws** Loss 5-13 416.72 Ignored Jul 7th Huckfest 2018
84 'Shine** Loss 1-13 621.46 Ignored Jul 7th Huckfest 2018
238 Strictly Bidness Loss 8-12 -253.74 Jul 7th Huckfest 2018
226 Baywatch Loss 3-13 -253.88 Jul 8th Huckfest 2018
159 Hellbenders Loss 5-11 210.74 Aug 11th Hootie on the Hill 2018
128 Boomtown** Loss 2-11 377.74 Ignored Aug 11th Hootie on the Hill 2018
115 STAX** Loss 2-13 437.43 Ignored Aug 11th Hootie on the Hill 2018
234 rubber duck ultimate. Loss 10-13 -72 Aug 11th Hootie on the Hill 2018
248 Mixed on the Rock Win 15-14 -81.09 Aug 12th Hootie on the Hill 2018
215 Free Ride Loss 7-15 -107.99 Aug 12th Hootie on the Hill 2018
122 Huntsville Outlaws Loss 8-13 520.56 Sep 8th Gulf Coast Mixed Sectional Championship 2018
197 Magic City Mayhem Loss 5-10 11.37 Sep 8th Gulf Coast Mixed Sectional Championship 2018
115 STAX** Loss 5-13 437.43 Ignored Sep 8th Gulf Coast Mixed Sectional Championship 2018
201 Mississippi Blues Loss 7-12 49.31 Sep 8th Gulf Coast Mixed Sectional Championship 2018
82 Method** Loss 3-13 632.62 Ignored Sep 9th Gulf Coast Mixed Sectional Championship 2018
201 Mississippi Blues Win 12-7 1090.33 Sep 9th Gulf Coast 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)