#102 Charleston Heat Stroke (11-15)

avg: 1034.45  •  sd: 71.9  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
108 H.O.G. Ultimate Win 13-10 1341.14 Jul 20th 2019 Club Terminus
143 Space Cowboys Loss 10-13 499.79 Jul 20th 2019 Club Terminus
127 Rougaroux Loss 10-12 667.85 Jul 20th 2019 Club Terminus
117 Rush Hour ATL Win 13-6 1568.19 Jul 20th 2019 Club Terminus
86 Bullet Loss 8-12 665.54 Jul 21st 2019 Club Terminus
67 Ironmen Loss 9-12 892.79 Jul 21st 2019 Club Terminus
126 Cockfight Win 13-7 1469.75 Jul 21st 2019 Club Terminus
84 Black Lung Win 13-10 1453.7 Aug 24th FCS Invite 2019
37 Tanasi Loss 9-13 1056.68 Aug 24th FCS Invite 2019
63 Turbine Loss 7-13 695 Aug 24th FCS Invite 2019
126 Cockfight Win 13-9 1330.78 Aug 24th FCS Invite 2019
107 Fathom Loss 8-15 454.72 Aug 25th FCS Invite 2019
91 Richmond Floodwall Loss 8-13 595.85 Aug 25th FCS Invite 2019
99 Bash Bros Loss 12-14 821.76 Aug 25th FCS Invite 2019
38 Lost Boys Loss 8-13 946.84 Sep 7th East Coast Mens Club Sectional Championship 2019
108 H.O.G. Ultimate Loss 12-13 887.99 Sep 7th East Coast Mens Club Sectional Championship 2019
86 Bullet Win 11-10 1231.7 Sep 7th East Coast Mens Club Sectional Championship 2019
143 Space Cowboys Win 13-9 1246.5 Sep 7th East Coast Mens Club Sectional Championship 2019
37 Tanasi Loss 5-13 875.25 Sep 8th East Coast Mens Club Sectional Championship 2019
117 Rush Hour ATL Win 12-11 1093.19 Sep 8th East Coast Mens Club Sectional Championship 2019
143 Space Cowboys Win 14-7 1410.82 Sep 8th East Coast Mens Club Sectional Championship 2019
36 Freaks Loss 6-13 875.4 Sep 21st Southeast Club Mens Regional Championship 2019
29 Brickhouse Loss 5-13 908.25 Sep 21st Southeast Club Mens Regional Championship 2019
50 UpRoar Loss 7-13 802.94 Sep 21st Southeast Club Mens Regional Championship 2019
99 Bash Bros Win 13-9 1461.28 Sep 21st Southeast Club Mens Regional Championship 2019
117 Rush Hour ATL Win 13-8 1464.35 Sep 22nd Southeast Club Mens Regional 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)