#178 Bomb Squad (7-12)

avg: 622.61  •  sd: 58.35  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
131 Slag Dump Win 11-9 1141.86 Jul 20th Stonewalled 2019
107 John Doe Loss 4-11 406.94 Jul 20th Stonewalled 2019
44 Lantern** Loss 3-11 779.35 Ignored Jul 20th Stonewalled 2019
152 Watchdogs Loss 11-13 534.06 Jul 21st Stonewalled 2019
135 Oakgrove Boys Loss 9-13 448.39 Jul 21st Stonewalled 2019
241 defunCT** Win 13-0 436.29 Ignored Aug 24th The Incident 2019 Age of Ultimatron
112 Genny The Boys Loss 8-13 475.42 Aug 24th The Incident 2019 Age of Ultimatron
44 Lantern** Loss 4-13 779.35 Ignored Aug 24th The Incident 2019 Age of Ultimatron
159 Ender's Outcasts Win 11-9 985.73 Aug 24th The Incident 2019 Age of Ultimatron
200 NEO Win 11-7 930.38 Aug 25th The Incident 2019 Age of Ultimatron
148 Overcast Loss 5-11 177.22 Aug 25th The Incident 2019 Age of Ultimatron
- Fathom II** Win 11-3 600 Ignored Sep 7th Capital Mens Club Sectional Championship 2019
235 HB Woodlawn Win 11-2 637.73 Sep 7th Capital Mens Club Sectional Championship 2019
152 Watchdogs Loss 9-11 513.69 Sep 7th Capital Mens Club Sectional Championship 2019
98 Town Hall Stars Loss 6-11 510.34 Sep 7th Capital Mens Club Sectional Championship 2019
173 Medicine Men Loss 11-12 527.84 Sep 8th Capital Mens Club Sectional Championship 2019
111 Fathom Loss 8-13 477.76 Sep 8th Capital Mens Club Sectional Championship 2019
213 Hail Mary Win 13-7 927.22 Sep 8th Capital Mens Club Sectional Championship 2019
22 Vault** Loss 1-11 1065.92 Ignored Sep 8th Capital 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)