#75 Richmond Floodwall (12-13)

avg: 1165.17  •  sd: 50.86  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
98 Town Hall Stars Loss 10-11 932.04 Jul 20th Stonewalled 2019
- Foggy Bottom Boys Win 11-10 989.4 Jul 20th Stonewalled 2019
96 Magma Bears Win 13-11 1297.04 Jul 21st Stonewalled 2019
111 Fathom Loss 11-13 745.08 Jul 21st Stonewalled 2019
44 Lantern Loss 8-13 883.19 Jul 21st Stonewalled 2019
43 CITYWIDE Special Loss 9-10 1276.95 Aug 10th Chesapeake Open 2019
27 H.I.P Loss 12-13 1423.55 Aug 10th Chesapeake Open 2019
37 Lost Boys Loss 6-13 861.09 Aug 10th Chesapeake Open 2019
26 Blueprint Loss 8-13 1053.91 Aug 10th Chesapeake Open 2019
59 Big Wrench Loss 10-15 817.85 Aug 11th Chesapeake Open 2019
49 El Niño Loss 8-10 1085.32 Aug 11th Chesapeake Open 2019
122 Cockfight Win 12-11 1048.45 Aug 24th FCS Invite 2019
35 Tanasi Loss 7-13 916.1 Aug 24th FCS Invite 2019
82 Black Lung Loss 9-11 877.12 Aug 24th FCS Invite 2019
51 Turbine Loss 7-11 865.8 Aug 24th FCS Invite 2019
104 Charleston Heat Stroke Win 13-8 1521.38 Aug 25th FCS Invite 2019
111 Fathom Win 15-13 1188.1 Aug 25th FCS Invite 2019
79 Bash Bros Win 14-10 1548.42 Aug 25th FCS Invite 2019
111 Fathom Win 13-9 1392.49 Sep 7th Capital Mens Club Sectional Championship 2019
213 Hail Mary** Win 13-5 969.69 Ignored Sep 7th Capital Mens Club Sectional Championship 2019
135 Oakgrove Boys Win 13-7 1424.49 Sep 7th Capital Mens Club Sectional Championship 2019
107 John Doe Win 13-9 1425.51 Sep 8th Capital Mens Club Sectional Championship 2019
107 John Doe Win 13-7 1564.47 Sep 8th Capital Mens Club Sectional Championship 2019
199 Winc City Fog of War Win 13-6 1064.6 Sep 8th Capital Mens Club Sectional Championship 2019
22 Vault Loss 10-13 1337.77 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)