#133 Oregon State (6-7)

avg: 839.4  •  sd: 60.26  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
60 Oregon Loss 6-15 746.76 Jan 25th Pacific Confrontational Invite 2020
44 Whitman** Loss 6-15 926.67 Ignored Jan 25th Pacific Confrontational Invite 2020
176 Portland State Win 10-6 985.38 Jan 25th Pacific Confrontational Invite 2020
60 Oregon Loss 5-11 746.76 Jan 26th Pacific Confrontational Invite 2020
44 Whitman** Loss 5-12 926.67 Ignored Jan 26th Pacific Confrontational Invite 2020
206 Idaho** Win 12-3 813.69 Ignored Feb 29th Big Sky Brawl 2020
36 Brigham Young Loss 8-13 1070.99 Feb 29th Big Sky Brawl 2020
136 Montana State University Loss 10-13 494.93 Feb 29th Big Sky Brawl 2020
130 Northern Arizona Win 9-8 986.82 Feb 29th Big Sky Brawl 2020
188 Boise State Win 8-4 967.47 Mar 1st Big Sky Brawl 2020
197 Montana Win 11-3 899.52 Mar 1st Big Sky Brawl 2020
144 Nevada-Reno Win 7-5 1104.6 Mar 1st Big Sky Brawl 2020
130 Northern Arizona Loss 3-6 315.12 Mar 1st Big Sky Brawl 2020
**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)