#157 Winc City Fog of War (4-14)

avg: 293.22  •  sd: 93.04  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
33 Richmond Floodwall** Loss 3-11 743.56 Ignored Jul 28th 2018 Richmond Stonewalled
148 Bomb Squad Loss 7-8 245.44 Jul 28th 2018 Richmond Stonewalled
126 Watchdogs Win 9-8 796.4 Jul 28th 2018 Richmond Stonewalled
76 Slag Dump Loss 4-9 390.89 Jul 28th 2018 Richmond Stonewalled
169 Bearfest Win 10-8 297.58 Jul 29th 2018 Richmond Stonewalled
148 Bomb Squad Win 11-9 619.64 Jul 29th 2018 Richmond Stonewalled
57 Shade** Loss 2-13 500.17 Ignored Aug 11th Nuccis Cup 2018
- Tune-UP Loss 6-13 -28.34 Aug 11th Nuccis Cup 2018
126 Watchdogs Loss 7-13 113.86 Aug 11th Nuccis Cup 2018
125 Town Hall Stars Loss 9-13 254.94 Aug 11th Nuccis Cup 2018
- Bearproof Loss 8-13 -110.71 Aug 12th Nuccis Cup 2018
135 Helots Loss 10-13 258.19 Aug 12th Nuccis Cup 2018
148 Bomb Squad Loss 8-11 4.83 Sep 8th Capital Mens Sectional Championship 2018
126 Watchdogs Loss 11-13 442.56 Sep 8th Capital Mens Sectional Championship 2018
- Mr. Scott and the Tots Win 11-7 602.46 Sep 8th Capital Mens Sectional Championship 2018
68 John Doe** Loss 2-11 439.2 Ignored Sep 8th Capital Mens Sectional Championship 2018
25 Medicine Men** Loss 1-11 805.58 Ignored Sep 8th Capital Mens Sectional Championship 2018
125 Town Hall Stars Loss 8-11 307.9 Sep 9th Capital 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)