#219 Memphis Hustle & Flow (6-14)

avg: 611.21  •  sd: 69.45  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
105 Auburn HeyDay Loss 6-13 558.12 Jul 6th Huntsville Huckfest 2019
174 Magic City Mayhem Win 13-8 1282.33 Jul 6th Huntsville Huckfest 2019
167 Possum Win 13-10 1164.24 Jul 6th Huntsville Huckfest 2019
113 sKNO cone Loss 6-13 511.67 Jul 6th Huntsville Huckfest 2019
162 OutKast Win 11-10 997.91 Jul 7th Huntsville Huckfest 2019
34 'Shine** Loss 5-13 988.45 Ignored Jul 7th Huntsville Huckfest 2019
83 Old #7** Loss 5-15 637.85 Jul 7th Huntsville Huckfest 2019
186 Be Reasonable Loss 5-13 145.44 Aug 17th Hootie on the Hill 2019
107 blOKC party Loss 9-13 728.08 Aug 17th Hootie on the Hill 2019
65 7 Sins** Loss 4-13 733.62 Ignored Aug 17th Hootie on the Hill 2019
149 Tex Mix Loss 3-13 326.68 Aug 17th Hootie on the Hill 2019
297 NWA White Tails Win 15-8 159.78 Aug 18th Hootie on the Hill 2019
243 rubber duck ultimate. Win 15-10 916.25 Aug 18th Hootie on the Hill 2019
105 Auburn HeyDay Loss 4-12 558.12 Sep 7th Gulf Coast Mixed Club Sectional Championship 2019
174 Magic City Mayhem Loss 9-12 440.8 Sep 7th Gulf Coast Mixed Club Sectional Championship 2019
47 Huntsville Outlaws** Loss 4-11 873.42 Ignored Sep 7th Gulf Coast Mixed Club Sectional Championship 2019
235 Mississippi Blues Loss 8-9 360.91 Sep 7th Gulf Coast Mixed Club Sectional Championship 2019
105 Auburn HeyDay Loss 4-10 558.12 Sep 8th Gulf Coast Mixed Club Sectional Championship 2019
70 Memphis STAX** Loss 4-13 701.52 Ignored Sep 8th Gulf Coast Mixed Club Sectional Championship 2019
235 Mississippi Blues Win 10-7 875.58 Sep 8th Gulf Coast 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)