#289 Brigham Young-B (4-10)

avg: 711.02  •  sd: 64.03  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
123 New Mexico Loss 3-11 679.41 Jan 26th New Year Fest 2019
400 Arizona State-C Win 11-4 821.92 Jan 26th New Year Fest 2019
222 Grand Canyon Loss 8-11 554.27 Jan 26th New Year Fest 2019
403 Texas-El Paso Win 11-3 790.26 Jan 26th New Year Fest 2019
273 Colorado State-B Loss 2-11 175.73 Jan 26th New Year Fest 2019
191 Montana State Loss 3-13 424.96 Mar 2nd Big Sky Brawl 2019
202 Northern Arizona Loss 6-8 672.57 Mar 2nd Big Sky Brawl 2019
238 Denver Loss 7-9 618.46 Mar 2nd Big Sky Brawl 2019
280 Idaho Win 11-9 1003.44 Mar 2nd Big Sky Brawl 2019
104 Portland Loss 8-11 973.55 Mar 30th 2019 NW Challenge Tier 2 3
200 Montana Loss 11-13 755.4 Mar 30th 2019 NW Challenge Tier 2 3
162 Washington State Loss 6-11 562.8 Mar 30th 2019 NW Challenge Tier 2 3
280 Idaho Win 11-8 1119.84 Mar 30th 2019 NW Challenge Tier 2 3
241 Washington-B Loss 8-11 522.87 Mar 30th 2019 NW Challenge Tier 2 3
**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)