#172 Los Heros (13-13)

avg: 744.78  •  sd: 67.42  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
38 Columbus Cocktails** Loss 3-11 900.3 Ignored Jul 7th Motown Throwdown 2018
171 North Coast Win 9-7 1030.05 Jul 7th Motown Throwdown 2018
134 Petey's Pirates Loss 6-11 411.06 Jul 7th Motown Throwdown 2018
211 Stackcats Win 9-8 643.98 Jul 7th Motown Throwdown 2018
129 Moonshine Loss 10-15 517.96 Jul 8th Motown Throwdown 2018
171 North Coast Win 13-10 1078.86 Jul 8th Motown Throwdown 2018
198 Second Wind Win 15-6 1181.25 Jul 8th Motown Throwdown 2018
145 Pandamonium Win 11-6 1432.08 Aug 4th Heavyweights 2018
111 panIC Loss 10-13 738.35 Aug 4th Heavyweights 2018
230 EDM Win 13-1 904.08 Aug 4th Heavyweights 2018
146 Prion Win 11-8 1250.63 Aug 5th Heavyweights 2018
45 Northern Comfort** Loss 4-13 835.86 Ignored Aug 5th Heavyweights 2018
97 tHUMP Loss 4-13 539.88 Aug 5th Heavyweights 2018
196 Thunderpants the Magic Dragon Loss 5-9 65.4 Aug 25th Indy Invite Club 2018
125 Hybrid Loss 4-6 642 Aug 25th Indy Invite Club 2018
212 Mixed Results Win 8-6 814.54 Aug 26th Indy Invite Club 2018
84 'Shine Loss 4-9 621.46 Aug 26th Indy Invite Club 2018
155 Liquid Hustle Win 9-8 966.83 Aug 26th Indy Invite Club 2018
186 Jabba Loss 10-11 525.2 Sep 8th Central Plains Mixed Sectional Championship 2018
155 Liquid Hustle Loss 6-11 295.13 Sep 8th Central Plains Mixed Sectional Championship 2018
104 Shakedown Loss 6-10 604.41 Sep 8th Central Plains Mixed Sectional Championship 2018
246 Taco Cat** Win 11-2 503.83 Ignored Sep 8th Central Plains Mixed Sectional Championship 2018
235 Skyhawks Win 11-5 844.51 Sep 8th Central Plains Mixed Sectional Championship 2018
155 Liquid Hustle Loss 10-14 443.12 Sep 9th Central Plains Mixed Sectional Championship 2018
211 Stackcats Win 12-10 757.1 Sep 9th Central Plains Mixed Sectional Championship 2018
137 ELevate Win 13-12 1066.87 Sep 9th Central 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)