#236 RnB (3-15)

avg: 433.03  •  sd: 79.02  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
136 Crucible Loss 6-13 331.51 Jun 22nd Summer Glazed Daze 2019
233 Stormborn Win 13-7 1007.89 Jun 22nd Summer Glazed Daze 2019
74 Petey's Pirates** Loss 5-13 629.88 Ignored Jun 22nd Summer Glazed Daze 2019
193 Heavy Flow Loss 5-13 61.14 Jun 23rd Summer Glazed Daze 2019
221 District Cocktails Loss 7-12 23.22 Jun 23rd Summer Glazed Daze 2019
165 Possum Loss 4-13 205.52 Jun 23rd Summer Glazed Daze 2019
259 ThunderCats Win 13-3 904.02 Jun 23rd Summer Glazed Daze 2019
100 NC Galaxy** Loss 3-13 516.4 Ignored Jul 13th Hometown Mix Up 2019
160 APEX Loss 9-12 483.25 Jul 13th Hometown Mix Up 2019
18 Superlame** Loss 2-13 1105.27 Ignored Jul 13th Hometown Mix Up 2019
149 Rowdy Loss 3-13 270.54 Jul 13th Hometown Mix Up 2019
165 Possum Loss 7-13 247.99 Jul 14th Hometown Mix Up 2019
273 Rampage Loss 11-13 3.18 Jul 14th Hometown Mix Up 2019
267 Baltimore BENCH Win 13-7 809.07 Sep 7th Capital Mixed Club Sectional Championship 2019
87 Fleet Loss 6-13 563.71 Sep 7th Capital Mixed Club Sectional Championship 2019
27 Rally** Loss 2-13 1036.96 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
110 Rat City** Loss 3-13 474.3 Ignored Sep 7th Capital Mixed Club Sectional Championship 2019
221 District Cocktails Loss 12-13 418.74 Sep 8th Capital 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)