#20 Washington (9-12)

avg: 2240.23  •  sd: 68.09  •  top 16/20: 41.7%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
26 California Win 11-8 2498.84 Feb 17th Presidents Day Invitational Tournament 2018
43 Southern California Win 14-5 2590.28 Feb 17th Presidents Day Invitational Tournament 2018
9 Colorado Loss 7-13 1942.16 Feb 17th Presidents Day Invitational Tournament 2018
11 Texas Loss 7-11 2004.85 Feb 18th Presidents Day Invitational Tournament 2018
4 Stanford Loss 6-11 2148.82 Feb 18th Presidents Day Invitational Tournament 2018
43 Southern California Loss 6-9 1571.72 Feb 18th Presidents Day Invitational Tournament 2018
37 Northwestern Win 9-7 2307.51 Feb 19th Presidents Day Invitational Tournament 2018
36 Colorado College Win 11-8 2398.79 Feb 19th Presidents Day Invitational Tournament 2018
2 California-San Diego Loss 7-13 2175.29 Mar 3rd Stanford Invite 2018
12 Carleton College Loss 9-11 2172.76 Mar 3rd Stanford Invite 2018
43 Southern California Win 11-7 2457.18 Mar 3rd Stanford Invite 2018
33 UCLA Win 13-10 2390.84 Mar 4th Stanford Invite 2018
5 Oregon Loss 9-13 2191.96 Mar 4th Stanford Invite 2018
9 Colorado Loss 11-12 2374.69 Mar 4th Stanford Invite 2018
14 Whitman Win 11-8 2751.74 Mar 23rd NW Challenge 2018
5 Oregon Loss 13-15 2396.34 Mar 23rd NW Challenge 2018
18 Brigham Young Loss 7-15 1686.51 Mar 24th NW Challenge 2018
1 Dartmouth** Loss 6-15 2297.25 Ignored Mar 24th NW Challenge 2018
21 Michigan Loss 6-15 1638.43 Mar 24th NW Challenge 2018
69 Boston College Win 15-3 2350.35 Mar 25th NW Challenge 2018
35 Cal Poly-SLO Win 15-6 2636.55 Mar 25th NW Challenge 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)