#19 Washington University (16-4)

avg: 1865.17  •  sd: 48.04  •  top 16/20: 69.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
56 Emory Win 13-5 2047.58 Feb 2nd Florida Warm Up 2024
7 Pittsburgh Loss 12-13 1968.14 Feb 2nd Florida Warm Up 2024
8 Vermont Loss 11-13 1809.76 Feb 2nd Florida Warm Up 2024
10 Carleton College Loss 7-13 1452.8 Feb 3rd Florida Warm Up 2024
185 South Florida** Win 13-3 1466.3 Ignored Feb 3rd Florida Warm Up 2024
101 Cornell Win 12-11 1349.57 Feb 4th Florida Warm Up 2024
27 Georgia Tech Win 14-13 1865.14 Feb 4th Florida Warm Up 2024
151 Cal Poly-SLO-B** Win 12-5 1633.94 Ignored Mar 2nd Stanford Invite 2024
65 Stanford Win 11-7 1871.83 Mar 2nd Stanford Invite 2024
63 Western Washington Win 13-7 1979.76 Mar 2nd Stanford Invite 2024
35 California-Santa Cruz Win 10-9 1762.21 Mar 3rd Stanford Invite 2024
6 Oregon Loss 7-12 1588.75 Mar 3rd Stanford Invite 2024
44 Tulane Win 12-8 1982.83 Mar 3rd Stanford Invite 2024
50 Alabama Win 12-7 2022.08 Mar 30th Huck Finn 2024
76 Purdue Win 12-6 1936.53 Mar 30th Huck Finn 2024
49 St Olaf Win 12-9 1848.53 Mar 30th Huck Finn 2024
66 Virginia Win 11-8 1759.78 Mar 30th Huck Finn 2024
67 Chicago Win 11-5 1987.02 Mar 31st Huck Finn 2024
49 St Olaf Win 13-7 2060.7 Mar 31st Huck Finn 2024
65 Stanford Win 13-6 2004.93 Mar 31st Huck Finn 2024
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)