#188 Thunder Boys (3-15)

avg: 534.21  •  sd: 87.64  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
94 Log Jam Loss 3-15 477.67 Jun 22nd Boston Invite 2019
154 BUDA U20B Loss 8-15 187.79 Jun 22nd Boston Invite 2019
157 Ender's Outcasts Loss 9-15 227.17 Jun 22nd Boston Invite 2019
112 Somerville BAG Loss 8-13 497.22 Jun 22nd Boston Invite 2019
204 Spring Break '93 Loss 8-13 -63.87 Jun 23rd Boston Invite 2019
186 Watch City Loss 1-13 -61.67 Jun 23rd Boston Invite 2019
198 Madhouse Win 11-7 943.98 Jul 20th Vacationland 2019
95 Red Tide Loss 8-9 952.07 Jul 20th Vacationland 2019
112 Somerville BAG Loss 9-11 744.18 Jul 20th Vacationland 2019
163 One Night Win 11-6 1257.83 Jul 20th Vacationland 2019
104 Burly Loss 3-13 425.93 Jul 21st Vacationland 2019
157 Ender's Outcasts Loss 6-11 195.96 Jul 21st Vacationland 2019
165 Rising Tide U20B Loss 3-9 105.51 Jul 21st Vacationland 2019
51 Lantern** Loss 2-11 758.82 Ignored Sep 7th East New England Mens Club Sectional Championship 2019
198 Madhouse Win 11-10 602.09 Sep 7th East New England Mens Club Sectional Championship 2019
66 Deathsquad Loss 6-11 695.62 Sep 7th East New England Mens Club Sectional Championship 2019
163 One Night Loss 6-9 292.57 Sep 7th East New England Mens Club Sectional Championship 2019
95 Red Tide Loss 10-11 952.07 Sep 7th East New England 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)