#238 Strictly Bidness (3-16)

avg: 187.41  •  sd: 73.57  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
122 Huntsville Outlaws** Loss 2-13 416.72 Ignored Jul 7th Huckfest 2018
84 'Shine** Loss 2-15 621.46 Ignored Jul 7th Huckfest 2018
197 Magic City Mayhem Loss 7-11 118.38 Jul 7th Huckfest 2018
240 Memphis Hustle & Flow Win 12-8 585.64 Jul 7th Huckfest 2018
212 Mixed Results Loss 5-13 -85.95 Jul 8th Huckfest 2018
197 Magic City Mayhem Loss 6-13 -14.73 Jul 8th Huckfest 2018
226 Baywatch Loss 9-13 -72.45 Jul 8th Huckfest 2018
129 Moonshine Loss 5-10 397.67 Jul 21st Bourbon Bash 2018
- Pocket City Approach Loss 8-9 140.94 Jul 21st Bourbon Bash 2018
223 Petey's Scallywags Loss 8-10 98.03 Jul 21st Bourbon Bash 2018
235 Skyhawks Loss 6-9 -174.06 Jul 21st Bourbon Bash 2018
198 Second Wind Loss 8-11 215.64 Jul 21st Bourbon Bash 2018
223 Petey's Scallywags Loss 6-8 60.2 Jul 22nd Bourbon Bash 2018
246 Taco Cat Win 12-10 141.95 Jul 22nd Bourbon Bash 2018
- Spidermonkeys Win 12-9 114.42 Jul 22nd Bourbon Bash 2018
212 Mixed Results Loss 9-12 168.69 Sep 8th East Coast Mixed Sectional Championship 2018
56 Murmur Loss 7-13 763.64 Sep 8th East Coast Mixed Sectional Championship 2018
188 Hairy Otter Loss 8-12 200.1 Sep 8th East Coast Mixed Sectional Championship 2018
153 APEX** Loss 5-13 253.35 Ignored Sep 8th East 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)