#9 Oregon (23-7)

avg: 2137.14  •  sd: 41.14  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
57 Stanford Win 15-4 2182.25 Jan 28th Santa Barbara Invitational 2023
46 Western Washington Win 11-9 1937.74 Jan 28th Santa Barbara Invitational 2023
54 Northwestern Win 15-3 2216.19 Jan 28th Santa Barbara Invitational 2023
18 California Loss 10-11 1836.57 Jan 28th Santa Barbara Invitational 2023
53 Utah Win 15-8 2184.8 Jan 29th Santa Barbara Invitational 2023
10 California-Santa Cruz Loss 12-13 1964.74 Jan 29th Santa Barbara Invitational 2023
17 Washington Win 12-9 2335.51 Jan 29th Santa Barbara Invitational 2023
44 Victoria Win 10-6 2192.88 Jan 29th Santa Barbara Invitational 2023
61 Emory Win 13-9 1995.55 Feb 18th President’s Day Invite
10 California-Santa Cruz Win 13-9 2508.3 Feb 18th President’s Day Invite
42 Grand Canyon Win 14-8 2241.32 Feb 18th President’s Day Invite
73 California-Santa Barbara** Win 15-4 2091.64 Ignored Feb 19th President’s Day Invite
18 California Win 13-9 2380.13 Feb 19th President’s Day Invite
32 Oregon State Win 11-8 2171.34 Feb 19th President’s Day Invite
15 UCLA Win 10-9 2153.29 Feb 19th President’s Day Invite
6 Colorado Win 14-13 2322.57 Feb 20th President’s Day Invite
7 Cal Poly-SLO Win 12-9 2520.72 Feb 20th President’s Day Invite
29 Utah State Win 13-8 2334.43 Mar 4th Stanford Invite Mens
78 Santa Clara Win 11-7 1941.97 Mar 4th Stanford Invite Mens
44 Victoria Win 13-9 2115.29 Mar 4th Stanford Invite Mens
18 California Win 13-6 2561.57 Mar 5th Stanford Invite Mens
10 California-Santa Cruz Loss 7-11 1622.84 Mar 5th Stanford Invite Mens
17 Washington Loss 10-11 1865.14 Mar 5th Stanford Invite Mens
11 Brown Loss 10-13 1746.58 Apr 1st Easterns 2023
14 Carleton College Win 13-10 2378.02 Apr 1st Easterns 2023
34 Michigan Win 12-11 1913.82 Apr 1st Easterns 2023
27 South Carolina Win 13-10 2176.32 Apr 1st Easterns 2023
3 Massachusetts Loss 13-14 2186.41 Apr 2nd Easterns 2023
12 Minnesota Win 14-13 2195.91 Apr 2nd Easterns 2023
7 Cal Poly-SLO Loss 12-14 1954.39 Apr 2nd Easterns 2023
**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)