#249 Second Wind (5-19)

avg: 422.82  •  sd: 71.3  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
151 Buffalo Lake Effect Loss 3-11 323.09 Jul 6th Motown Throwdown 2019
263 SlipStream Win 11-4 935.55 Jul 6th Motown Throwdown 2019
182 Rocket LawnChair Loss 4-11 169.7 Jul 6th Motown Throwdown 2019
196 Petey's Scallywags Loss 7-8 575.71 Jul 7th Motown Throwdown 2019
182 Rocket LawnChair Loss 6-8 469.2 Jul 7th Motown Throwdown 2019
58 Toast** Loss 5-13 785.08 Ignored Jul 7th Motown Throwdown 2019
175 Moonshine Win 8-7 906.83 Jul 7th Motown Throwdown 2019
140 Crucible Loss 7-13 425.92 Jul 20th Bourbon Bash 2019
193 Hairy Otter Loss 8-13 209.02 Jul 20th Bourbon Bash 2019
175 Moonshine Loss 5-12 181.83 Jul 20th Bourbon Bash 2019
170 Thunderpants the Magic Dragon Loss 6-14 207.18 Jul 20th Bourbon Bash 2019
257 Derby City Thunder Loss 11-13 148.18 Jul 21st Bourbon Bash 2019
266 I-79 Loss 9-12 -29.9 Jul 21st Bourbon Bash 2019
277 Indiana Pterodactyl Attack Loss 0-15 -376.69 Jul 21st Bourbon Bash 2019
73 Petey's Pirates** Loss 3-13 674.68 Ignored Aug 11th CUDA Round Robin 2019
196 Petey's Scallywags Loss 14-15 575.71 Aug 11th CUDA Round Robin 2019
170 Thunderpants the Magic Dragon Loss 8-13 311.02 Aug 11th CUDA Round Robin 2019
257 Derby City Thunder Win 13-6 977.02 Sep 7th East Plains Mixed Club Sectional Championship 2019
155 Goose Lee Loss 10-13 585.07 Sep 7th East Plains Mixed Club Sectional Championship 2019
58 Toast** Loss 5-13 785.08 Ignored Sep 7th East Plains Mixed Club Sectional Championship 2019
251 Mishigami Loss 10-13 88.05 Sep 7th East Plains Mixed Club Sectional Championship 2019
286 Cleveland Rocks Win 15-8 663.18 Sep 8th East Plains Mixed Club Sectional Championship 2019
228 Midwestern Mediocrity Loss 11-14 212.6 Sep 8th East Plains Mixed Club Sectional Championship 2019
251 Mishigami Win 13-6 1016.19 Sep 8th East Plains Mixed 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)