#238 Denver (8-9)

avg: 897.8  •  sd: 69.08  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
382 Air Force-B Win 13-4 906.13 Jan 26th New Year Fest 2019
272 Arizona State-B Win 13-8 1272.63 Jan 26th New Year Fest 2019
388 Arizona-B Win 13-7 838.33 Jan 26th New Year Fest 2019
202 Northern Arizona Loss 8-13 476.91 Jan 26th New Year Fest 2019
273 Colorado State-B Win 13-11 1004.58 Jan 27th New Year Fest 2019
202 Northern Arizona Loss 11-12 848.07 Jan 27th New Year Fest 2019
222 Grand Canyon Loss 8-12 478.73 Jan 27th New Year Fest 2019
125 Colorado School of Mines Loss 3-13 678.32 Feb 23rd Denver Round Robin 2019
273 Colorado State-B Loss 11-12 650.73 Feb 23rd Denver Round Robin 2019
170 Colorado-Denver Loss 3-13 483.91 Feb 23rd Denver Round Robin 2019
191 Montana State Loss 7-10 635.29 Mar 2nd Big Sky Brawl 2019
289 Brigham Young-B Win 9-7 990.36 Mar 2nd Big Sky Brawl 2019
280 Idaho Win 11-7 1221.12 Mar 2nd Big Sky Brawl 2019
202 Northern Arizona Loss 6-7 848.07 Mar 2nd Big Sky Brawl 2019
305 Boise State Win 15-1 1242.33 Mar 3rd Big Sky Brawl 2019
76 Utah Loss 10-13 1145.58 Mar 3rd Big Sky Brawl 2019
133 Utah State Win 12-11 1370.27 Mar 3rd Big Sky Brawl 2019
**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)