#64 Overcast (11-6)

avg: 1048.22  •  sd: 73.81  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
113 Club M - Magma Win 14-8 1300.27 Jun 23rd Boston Invite 2018
- BUDA Win 13-9 1145.45 Jun 23rd Boston Invite 2018
94 Red Tide Win 15-11 1262.69 Jun 23rd Boston Invite 2018
105 Bruises Win 14-9 1263.83 Jun 24th Boston Invite 2018
158 Shades** Win 15-3 858.19 Ignored Jun 24th Boston Invite 2018
96 Shrike Win 15-7 1461.82 Jun 24th Boston Invite 2018
142 Genny Lite Win 13-4 1101.22 Aug 26th Sectional Sanction Upstate NY 2018
14 GOAT Loss 7-13 1157.57 Aug 26th Sectional Sanction Upstate NY 2018
45 Mockingbird Loss 7-13 681.25 Aug 26th Sectional Sanction Upstate NY 2018
28 Phoenix Loss 11-12 1254.92 Aug 26th Sectional Sanction Upstate NY 2018
- ESF Mighty Oaks Win 12-6 747.63 Sep 8th Upstate New York Mens Sectional Championship 2018
96 Shrike Win 10-9 986.82 Sep 8th Upstate New York Mens Sectional Championship 2018
- Maverick Win 12-7 1263.37 Sep 8th Upstate New York Mens Sectional Championship 2018
28 Phoenix Loss 6-15 779.92 Sep 8th Upstate New York Mens Sectional Championship 2018
96 Shrike Loss 9-10 736.82 Sep 9th Upstate New York Mens Sectional Championship 2018
142 Genny Lite Win 15-5 1101.22 Sep 9th Upstate New York Mens Sectional Championship 2018
14 GOAT** Loss 6-15 1115.11 Ignored Sep 9th Upstate New York Mens Sectional Championship 2018
**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)