#46 Ghost Train (15-11)

avg: 1225.83  •  sd: 60.62  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
- Whitefish** Win 13-2 941.91 Ignored Jun 22nd Eugene Summer Solstice 40
- Blackfish Loss 10-11 1155.02 Jun 23rd Eugene Summer Solstice 40
38 Dark Star Loss 11-13 1051.08 Jun 23rd Eugene Summer Solstice 40
99 Red Dawn Win 11-10 968.71 Jun 23rd Eugene Summer Solstice 40
- Blackfish Win 11-8 1645.63 Jun 24th Eugene Summer Solstice 40
6 Furious George Loss 8-13 1372.95 Jun 24th Eugene Summer Solstice 40
78 Rip City Ultimate Win 13-10 1303.94 Aug 25th CBR Memorial 2018
63 Sawtooth Win 9-8 1181.56 Aug 25th CBR Memorial 2018
38 Dark Star Win 11-9 1529.13 Aug 25th CBR Memorial 2018
86 Green River Swordfish Win 13-9 1340.68 Aug 25th CBR Memorial 2018
91 Sprawl Win 13-8 1393.53 Aug 26th CBR Memorial 2018
- DNA Win 13-6 1580.24 Sep 8th Washington Mens Sectional Championship 2018
22 Voodoo Loss 9-13 1085.91 Sep 8th Washington Mens Sectional Championship 2018
- SOUF Win 13-7 1318.16 Sep 8th Washington Mens Sectional Championship 2018
6 Furious George** Loss 4-13 1269.11 Ignored Sep 8th Washington Mens Sectional Championship 2018
- DNA Win 12-10 1218.36 Sep 9th Washington Mens Sectional Championship 2018
- Fight Club Win 13-12 1013.05 Sep 9th Washington Mens Sectional Championship 2018
22 Voodoo Loss 3-13 904.47 Sep 9th Washington Mens Sectional Championship 2018
- SOUF Win 8-7 885.63 Sep 9th Washington Mens Sectional Championship 2018
12 Rhino Slam Loss 7-13 1222.14 Sep 22nd Northwest Mens Regional Championship 2018
63 Sawtooth Win 13-8 1552.72 Sep 22nd Northwest Mens Regional Championship 2018
22 Voodoo Loss 5-12 904.47 Sep 22nd Northwest Mens Regional Championship 2018
6 Furious George Loss 6-12 1289.8 Sep 22nd Northwest Mens Regional Championship 2018
12 Rhino Slam Loss 5-13 1179.67 Sep 23rd Northwest Mens Regional Championship 2018
78 Rip City Ultimate Win 12-8 1416.95 Sep 23rd Northwest Mens Regional Championship 2018
38 Dark Star Loss 10-13 951.78 Sep 23rd Northwest Mens Regional 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)