#59 Portland Ivy (7-9)

avg: 854.64  •  sd: 63.24  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
68 Trash. Win 13-3 1273.17 Jun 22nd Eugene Summer Solstice 2019
49 Korra Loss 8-11 694.49 Jun 22nd Eugene Summer Solstice 2019
35 Seattle Soul Loss 5-9 728.93 Jun 22nd Eugene Summer Solstice 2019
89 Tempo** Win 13-3 814.52 Ignored Jun 22nd Eugene Summer Solstice 2019
56 Venom Win 10-5 1445.67 Jun 23rd Eugene Summer Solstice 2019
74 Koi Win 13-9 999.28 Jun 23rd Eugene Summer Solstice 2019
35 Seattle Soul Loss 4-10 657.99 Jun 23rd Eugene Summer Solstice 2019
23 LOL** Loss 2-11 912.02 Ignored Aug 4th Seattle Round Robin 2019
35 Seattle Soul Loss 2-8 657.99 Aug 4th Seattle Round Robin 2019
83 Sizzle Win 9-3 898.51 Aug 4th Seattle Round Robin 2019
10 Traffic** Loss 2-13 1337.23 Ignored Sep 7th Washington Womens Club Sectional Championship 2019
74 Koi Win 9-8 705.72 Sep 7th Washington Womens Club Sectional Championship 2019
35 Seattle Soul Loss 0-8 657.99 Sep 7th Washington Womens Club Sectional Championship 2019
83 Sizzle Win 12-6 877.82 Sep 7th Washington Womens Club Sectional Championship 2019
18 Underground** Loss 2-13 1096.48 Ignored Sep 8th Washington Womens Club Sectional Championship 2019
25 Sneaky House Hippos** Loss 2-13 862.74 Ignored Sep 8th Washington Womens 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)