#125 Town Hall Stars (9-13)

avg: 673.51  •  sd: 96.69  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
148 Bomb Squad Win 11-6 917.13 Jul 28th 2018 Richmond Stonewalled
126 Watchdogs Win 10-6 1167.56 Jul 28th 2018 Richmond Stonewalled
76 Slag Dump Loss 9-10 865.89 Jul 28th 2018 Richmond Stonewalled
- Foggy Bottom Boys Loss 5-8 437.53 Jul 28th 2018 Richmond Stonewalled
114 Cockfight Win 7-3 1363.48 Jul 29th 2018 Richmond Stonewalled
136 Pipeline Loss 12-13 455.82 Jul 29th 2018 Richmond Stonewalled
57 Shade Loss 7-13 542.64 Aug 11th Nuccis Cup 2018
169 Bearfest Win 13-7 592.45 Aug 11th Nuccis Cup 2018
- Tune-UP Loss 8-9 446.66 Aug 11th Nuccis Cup 2018
157 Winc City Fog of War Win 13-9 711.78 Aug 11th Nuccis Cup 2018
126 Watchdogs Loss 5-13 71.4 Aug 12th Nuccis Cup 2018
109 JAWN Loss 8-9 644.86 Aug 12th Nuccis Cup 2018
33 Richmond Floodwall Loss 8-11 977.95 Sep 8th Capital Mens Sectional Championship 2018
169 Bearfest** Win 11-3 634.92 Ignored Sep 8th Capital Mens Sectional Championship 2018
- BLUD Win 11-2 696.45 Sep 8th Capital Mens Sectional Championship 2018
52 Oakgrove Boys Loss 2-11 586.93 Sep 8th Capital Mens Sectional Championship 2018
148 Bomb Squad Win 11-4 970.44 Sep 9th Capital Mens Sectional Championship 2018
157 Winc City Fog of War Win 11-8 658.82 Sep 9th Capital Mens Sectional Championship 2018
33 Richmond Floodwall Loss 7-13 786.03 Sep 22nd Mid Atlantic Mens Regional Championship 2018
30 Garden State Ultimate** Loss 5-13 750.55 Ignored Sep 22nd Mid Atlantic Mens Regional Championship 2018
25 Medicine Men** Loss 4-13 805.58 Ignored Sep 22nd Mid Atlantic Mens Regional Championship 2018
126 Watchdogs Loss 10-15 217.79 Sep 23rd Mid Atlantic Mens Regional 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)