#36 Brigham Young (9-4)

avg: 1567.15  •  sd: 80.93  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
10 California-Santa Barbara Loss 7-13 1484.36 Jan 24th Santa Barbara Invite 2020
39 Cal Poly-SLO Win 9-6 1975.55 Jan 24th Santa Barbara Invite 2020
21 Vermont Loss 5-12 1325.53 Jan 25th Santa Barbara Invite 2020
22 Northwestern Loss 7-13 1232.21 Jan 25th Santa Barbara Invite 2020
58 California-Santa Cruz Win 11-10 1491.65 Jan 25th Santa Barbara Invite 2020
3 Tufts Loss 6-11 1721.84 Feb 8th Queen City Tune Up 2020 Women
38 Duke Win 11-7 2024.55 Feb 8th Queen City Tune Up 2020 Women
83 Clemson Win 11-4 1802.24 Feb 8th Queen City Tune Up 2020 Women
84 Notre Dame Win 7-6 1313.39 Feb 8th Queen City Tune Up 2020 Women
188 Boise State** Win 13-1 1002.66 Ignored Feb 29th Big Sky Brawl 2020
133 Oregon State Win 13-8 1335.56 Feb 29th Big Sky Brawl 2020
136 Montana State University** Win 13-2 1423.08 Ignored Feb 29th Big Sky Brawl 2020
130 Northern Arizona** Win 13-2 1461.82 Ignored Feb 29th 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)