#115 baNC (8-17)

avg: 962.39  •  sd: 69.61  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
106 H.O.G. Ultimate Loss 11-12 882.12 Jun 15th ATL Classic 2019
66 Ironmen Loss 6-13 628.16 Jun 15th ATL Classic 2019
202 War Machine Win 12-7 956.68 Jun 15th ATL Classic 2019
49 El Niño Loss 6-13 747.98 Jun 15th ATL Classic 2019
126 Rougaroux Loss 6-10 408.87 Jun 16th ATL Classic 2019
202 War Machine Win 13-4 1036.17 Jun 16th ATL Classic 2019
120 Rush Hour ATL Loss 7-13 389.79 Jul 20th 2019 Club Terminus
35 Tanasi Loss 10-12 1235.5 Jul 20th 2019 Club Terminus
223 Traffic Win 13-6 862.59 Jul 20th 2019 Club Terminus
126 Rougaroux Win 13-6 1505.03 Jul 20th 2019 Club Terminus
66 Ironmen Win 13-7 1785.69 Jul 21st 2019 Club Terminus
81 Bullet Loss 8-13 630.27 Jul 21st 2019 Club Terminus
86 ATLiens Loss 6-13 514.94 Jul 21st 2019 Club Terminus
111 Fathom Loss 10-12 735.8 Aug 24th FCS Invite 2019
37 Lost Boys Loss 8-13 964.93 Aug 24th FCS Invite 2019
22 Vault** Loss 2-13 1065.92 Ignored Aug 24th FCS Invite 2019
79 Bash Bros Loss 9-13 731.15 Aug 24th FCS Invite 2019
139 Space Cowboys Win 15-14 959.13 Aug 25th FCS Invite 2019
139 Space Cowboys Win 11-7 1301.02 Aug 25th FCS Invite 2019
82 Black Lung Loss 11-12 1001.33 Aug 25th FCS Invite 2019
51 Turbine Win 11-10 1457.69 Sep 7th North Carolina Mens Club Sectional Championship 2019
24 Brickhouse Loss 10-11 1443.2 Sep 7th North Carolina Mens Club Sectional Championship 2019
79 Bash Bros Loss 13-14 1024.72 Sep 7th North Carolina Mens Club Sectional Championship 2019
51 Turbine Loss 8-15 767.88 Sep 8th North Carolina Mens Club Sectional Championship 2019
79 Bash Bros Loss 9-15 634.24 Sep 8th North Carolina Mens 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)