#159 Midnight Meat Train (2-15)

avg: 235.84  •  sd: 98.61  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
112 Enigma Loss 7-11 297.54 Jul 7th Motown Throwdown 2018
- COAT Loss 6-11 -274.8 Jul 7th Motown Throwdown 2018
90 Omen Loss 5-11 301.03 Jul 7th Motown Throwdown 2018
127 Dynasty Loss 5-15 51.97 Jul 8th Motown Throwdown 2018
154 Black Market II Loss 9-15 -208.65 Jul 8th Motown Throwdown 2018
124 Wisconsin Hops Loss 4-13 96.35 Aug 4th Heavyweights 2018
73 Greater Gary Goblins Y** Loss 5-13 415.8 Ignored Aug 4th Heavyweights 2018
117 THE BODY Loss 3-13 130.94 Aug 4th Heavyweights 2018
164 Fifty-Fifty Win 11-3 737.74 Aug 5th Heavyweights 2018
120 KC SmokeStack Loss 6-13 111.75 Aug 5th Heavyweights 2018
163 Hippie Mafia Win 13-7 706.05 Aug 5th Heavyweights 2018
112 Enigma Loss 7-11 297.54 Sep 8th East Plains Mens Sectional Championship 2018
51 BroCats** Loss 3-11 589.85 Ignored Sep 8th East Plains Mens Sectional Championship 2018
48 Four Loss 6-11 669.38 Sep 8th East Plains Mens Sectional Championship 2018
139 Kentucky Flying Circus Loss 4-11 -74.5 Sep 8th East Plains Mens Sectional Championship 2018
100 Babe Loss 5-11 233.2 Sep 9th East Plains Mens Sectional Championship 2018
90 Omen** Loss 4-11 301.03 Ignored Sep 9th East Plains Mens 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)