#131 Slag Dump (8-10)

avg: 892.66  •  sd: 67.57  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
107 John Doe Loss 8-11 641.33 Jul 20th Stonewalled 2019
44 Lantern Loss 7-11 912.46 Jul 20th Stonewalled 2019
178 Bomb Squad Loss 9-11 373.41 Jul 20th Stonewalled 2019
213 Hail Mary Win 13-6 969.69 Jul 21st Stonewalled 2019
199 Winc City Fog of War Win 11-7 931.5 Jul 21st Stonewalled 2019
96 Magma Bears Loss 9-13 649.63 Aug 10th Nuccis Cup 2019
207 Sky Hook Win 13-10 747.77 Aug 10th Nuccis Cup 2019
107 John Doe Loss 7-13 449.41 Aug 10th Nuccis Cup 2019
211 Bearproof Win 13-2 991.47 Aug 10th Nuccis Cup 2019
132 JAWN Loss 10-15 432.96 Aug 11th Nuccis Cup 2019
43 CITYWIDE Special Loss 4-13 801.95 Sep 7th Founders Mens Club Sectional Championship 2019
- Axial Tilt** Win 13-5 600 Ignored Sep 7th Founders Mens Club Sectional Championship 2019
180 Not A Sport Win 13-9 1001.27 Sep 7th Founders Mens Club Sectional Championship 2019
132 JAWN Win 13-10 1214.71 Sep 7th Founders Mens Club Sectional Championship 2019
38 Garden State Ultimate Loss 7-13 897.49 Sep 8th Founders Mens Club Sectional Championship 2019
58 Rumspringa Loss 12-13 1152.07 Sep 8th Founders Mens Club Sectional Championship 2019
18 Patrol Loss 6-13 1138.32 Sep 8th Founders Mens Club Sectional Championship 2019
132 JAWN Win 13-7 1444.1 Sep 8th Founders 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)