#152 Watchdogs (13-14)

avg: 762.9  •  sd: 50.27  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
96 Magma Bears Loss 9-11 818.99 Jul 20th Stonewalled 2019
213 Hail Mary Win 11-5 969.69 Jul 20th Stonewalled 2019
22 Vault** Loss 4-11 1065.92 Ignored Jul 20th Stonewalled 2019
- Foggy Bottom Boys Loss 9-12 519.04 Jul 21st Stonewalled 2019
178 Bomb Squad Win 13-11 851.45 Jul 21st Stonewalled 2019
50 Colt Loss 6-13 744.87 Aug 3rd Philly Open 2019
172 Hazard Loss 11-13 427.44 Aug 3rd Philly Open 2019
137 Babe Loss 11-12 716.9 Aug 3rd Philly Open 2019
211 Bearproof Win 13-11 620.31 Aug 3rd Philly Open 2019
230 Hot Tamales Win 13-7 752.28 Aug 4th Philly Open 2019
200 NEO Win 15-11 844.65 Aug 4th Philly Open 2019
132 JAWN Loss 9-10 761.57 Aug 10th Nuccis Cup 2019
171 Adelphos Loss 7-13 99.27 Aug 10th Nuccis Cup 2019
199 Winc City Fog of War Win 13-9 883.17 Aug 10th Nuccis Cup 2019
98 Town Hall Stars Loss 5-13 457.04 Aug 10th Nuccis Cup 2019
207 Sky Hook Win 15-13 633.8 Aug 11th Nuccis Cup 2019
132 JAWN Loss 11-15 505.4 Aug 11th Nuccis Cup 2019
107 John Doe Loss 12-13 881.94 Aug 11th Nuccis Cup 2019
98 Town Hall Stars Win 15-13 1271.22 Aug 11th Nuccis Cup 2019
- Fathom II** Win 11-2 600 Ignored Sep 7th Capital Mens Club Sectional Championship 2019
178 Bomb Squad Win 11-9 871.82 Sep 7th Capital Mens Club Sectional Championship 2019
22 Vault** Loss 3-11 1065.92 Ignored Sep 7th Capital Mens Club Sectional Championship 2019
98 Town Hall Stars Win 11-9 1306.25 Sep 7th Capital Mens Club Sectional Championship 2019
173 Medicine Men Win 11-7 1119.73 Sep 8th Capital Mens Club Sectional Championship 2019
235 HB Woodlawn** Win 11-4 637.73 Ignored Sep 8th Capital Mens Club Sectional Championship 2019
107 John Doe Loss 10-13 678.8 Sep 8th Capital Mens Club Sectional Championship 2019
98 Town Hall Stars Loss 9-13 638.47 Sep 8th Capital 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)