#196 Thunderpants the Magic Dragon (8-14)

avg: 594.46  •  sd: 86.9  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
125 Hybrid Loss 8-11 642 Jul 7th Motown Throwdown 2018
198 Second Wind Loss 7-11 114.36 Jul 7th Motown Throwdown 2018
137 ELevate Loss 8-9 816.87 Jul 7th Motown Throwdown 2018
186 Jabba Win 11-10 775.2 Jul 7th Motown Throwdown 2018
88 Toast Loss 2-11 576.79 Jul 7th Motown Throwdown 2018
- Sabers Win 11-7 529.73 Jul 8th Motown Throwdown 2018
211 Stackcats Win 15-9 1034.46 Jul 8th Motown Throwdown 2018
155 Liquid Hustle Loss 8-13 345.67 Jul 8th Motown Throwdown 2018
172 Los Heros Win 9-5 1273.84 Aug 25th Indy Invite Club 2018
208 Bonfire Win 9-4 1134.69 Aug 26th Indy Invite Club 2018
84 'Shine** Loss 4-11 621.46 Ignored Aug 26th Indy Invite Club 2018
134 Petey's Pirates Loss 7-9 678.42 Aug 26th Indy Invite Club 2018
125 Hybrid Loss 1-11 407.61 Aug 26th Indy Invite Club 2018
155 Liquid Hustle Loss 5-10 267.93 Aug 26th Indy Invite Club 2018
129 Moonshine Loss 7-13 414.04 Sep 15th East Plains Mixed Sectional Championship 2018
88 Toast Loss 5-13 576.79 Sep 15th East Plains Mixed Sectional Championship 2018
198 Second Wind Loss 6-13 -18.75 Sep 15th East Plains Mixed Sectional Championship 2018
140 Rocket LawnChair Loss 9-13 477.09 Sep 15th East Plains Mixed Sectional Championship 2018
205 Fifth Element Loss 8-13 47.83 Sep 16th East Plains Mixed Sectional Championship 2018
171 North Coast Win 9-8 875.72 Sep 16th East Plains Mixed Sectional Championship 2018
223 Petey's Scallywags Win 12-8 801.85 Sep 16th East Plains Mixed Sectional Championship 2018
208 Bonfire Win 9-5 1063.75 Sep 16th East Plains Mixed 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)