#6 Colorado (18-5)

avg: 1992.4  •  sd: 29.25  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
66 Stanford Win 14-8 1908.53 Feb 18th President’s Day Invite
64 California-San Diego Win 15-7 1979.59 Feb 18th President’s Day Invite
31 Oregon State Win 12-11 1756.02 Feb 18th President’s Day Invite
20 Washington Win 13-11 1970.89 Feb 19th President’s Day Invite
38 Emory Win 13-7 2093.35 Feb 19th President’s Day Invite
45 Western Washington Win 15-11 1870.42 Feb 19th President’s Day Invite
9 California-Santa Cruz Win 11-10 2020.46 Feb 19th President’s Day Invite
20 Washington Win 12-10 1980.18 Feb 20th President’s Day Invite
7 Oregon Loss 13-14 1843.08 Feb 20th President’s Day Invite
18 Brown Win 13-12 1871.16 Mar 4th Smoky Mountain Invite
19 Ohio State Win 13-10 2074.01 Mar 4th Smoky Mountain Invite
5 Vermont Loss 10-13 1682.57 Mar 4th Smoky Mountain Invite
21 Georgia Win 13-10 2064.46 Mar 4th Smoky Mountain Invite
11 Pittsburgh Win 13-11 2096.56 Mar 5th Smoky Mountain Invite
2 North Carolina Loss 13-15 1924.21 Mar 5th Smoky Mountain Invite
5 Vermont Loss 12-13 1885.71 Mar 5th Smoky Mountain Invite
3 Brigham Young Loss 11-13 1888.67 Mar 18th Centex 2023
12 Carleton College Win 12-11 1988.49 Mar 18th Centex 2023
62 Northwestern Win 13-6 1987.69 Mar 18th Centex 2023
29 Wisconsin Win 11-6 2213.36 Mar 18th Centex 2023
4 Texas Win 14-13 2146.51 Mar 19th Centex 2023
28 Georgia Tech Win 14-8 2208.82 Mar 19th Centex 2023
13 Tufts Win 15-11 2239.34 Mar 19th Centex 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)