#227 Midwestern Mediocrity (7-13)

avg: 472.03  •  sd: 47.72  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
225 Boomtown Pandas Win 13-12 644.51 Aug 3rd Heavyweights 2019
147 Los Heros Loss 7-13 315.69 Aug 3rd Heavyweights 2019
137 Mad Udderburn Loss 8-13 431.4 Aug 3rd Heavyweights 2019
156 EMU Loss 5-13 246 Aug 4th Heavyweights 2019
211 Mastodon Loss 7-12 68.15 Aug 4th Heavyweights 2019
112 Pandamonium Loss 10-13 738.96 Aug 4th Heavyweights 2019
240 Duloofda Loss 13-14 294.57 Aug 17th Cooler Classic 31
168 ELevate Loss 8-13 283.99 Aug 17th Cooler Classic 31
152 Melt Loss 7-13 303.79 Aug 17th Cooler Classic 31
217 Stackcats Win 12-11 693.52 Aug 17th Cooler Classic 31
219 Great Minnesota Get Together Loss 7-8 431.41 Aug 18th Cooler Classic 31
295 Fox Valley Forge** Win 11-3 255.54 Ignored Aug 18th Cooler Classic 31
290 Taco Cat Win 10-3 511.82 Aug 18th Cooler Classic 31
254 Derby City Thunder Win 15-9 844.82 Sep 7th East Plains Mixed Club Sectional Championship 2019
74 Petey's Pirates** Loss 5-13 629.88 Ignored Sep 7th East Plains Mixed Club Sectional Championship 2019
166 Moonshine Loss 10-13 475.52 Sep 7th East Plains Mixed Club Sectional Championship 2019
250 Mishigami Win 13-9 781.99 Sep 7th East Plains Mixed Club Sectional Championship 2019
185 Pixel Loss 10-12 450.08 Sep 8th East Plains Mixed Club Sectional Championship 2019
248 Second Wind Win 14-11 690.56 Sep 8th East Plains Mixed Club Sectional Championship 2019
182 Rocket LawnChair Loss 5-11 113.72 Sep 8th East 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)