#132 Oakgrove Boys (8-15)

avg: 887.78  •  sd: 59.45  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
107 Fathom Loss 4-11 419.53 Jul 20th Stonewalled 2019
35 Blueprint Loss 6-11 930.5 Jul 20th Stonewalled 2019
197 Winc City Fog of War Win 11-5 1077.83 Jul 20th Stonewalled 2019
175 Bomb Squad Win 13-9 1051.42 Jul 21st Stonewalled 2019
- Foggy Bottom Boys Win 11-9 1112.44 Jul 21st Stonewalled 2019
42 Garden State Ultimate Loss 7-13 856.49 Aug 10th Chesapeake Open 2019
29 Brickhouse Loss 7-13 950.72 Aug 10th Chesapeake Open 2019
62 Big Wrench Loss 7-13 719.1 Aug 10th Chesapeake Open 2019
23 Vault Loss 8-13 1127.49 Aug 10th Chesapeake Open 2019
44 Shade Loss 4-13 809.19 Aug 11th Chesapeake Open 2019
52 El Niño Loss 5-15 756.84 Aug 11th Chesapeake Open 2019
197 Winc City Fog of War Win 13-6 1077.83 Sep 7th Capital Mens Club Sectional Championship 2019
91 Richmond Floodwall Loss 7-13 534.48 Sep 7th Capital Mens Club Sectional Championship 2019
101 John Doe Loss 9-13 617.05 Sep 7th Capital Mens Club Sectional Championship 2019
107 Fathom Win 13-11 1248.37 Sep 8th Capital Mens Club Sectional Championship 2019
212 Hail Mary Win 13-4 991.12 Sep 8th Capital Mens Club Sectional Championship 2019
92 Town Hall Stars Loss 4-13 491.11 Sep 8th Capital Mens Club Sectional Championship 2019
42 Garden State Ultimate Loss 7-13 856.49 Sep 21st Mid Atlantic Mens Club Regional Championship 2019
176 Medicine Men Win 13-10 942.38 Sep 21st Mid Atlantic Mens Club Regional Championship 2019
47 CITYWIDE Special Loss 5-15 792.5 Sep 21st Mid Atlantic Mens Club Regional Championship 2019
22 Patrol Loss 6-13 1028.85 Sep 21st Mid Atlantic Mens Club Regional Championship 2019
129 JAWN Loss 10-12 664.58 Sep 22nd Mid Atlantic Mens Club Regional Championship 2019
82 Rumspringa Win 15-13 1340.92 Sep 22nd Mid Atlantic Mens Club Regional 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)