#3 Colorado (20-1)

avg: 2467.86  •  sd: 65.32  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
53 Cal Poly-SLO** Win 15-2 1980.02 Ignored Feb 18th President’s Day Invite
31 California Win 13-7 2215.49 Feb 18th President’s Day Invite
25 California-Davis** Win 10-4 2319.95 Ignored Feb 18th President’s Day Invite
74 Utah** Win 14-3 1824.4 Ignored Feb 18th President’s Day Invite
24 Carleton College-Eclipse Win 13-8 2228.99 Feb 19th President’s Day Invite
48 Texas Win 10-5 2033.85 Feb 19th President’s Day Invite
17 California-San Diego** Win 14-3 2424.58 Ignored Feb 19th President’s Day Invite
8 Stanford Win 12-8 2674.48 Feb 20th President’s Day Invite
11 Oregon Win 12-10 2334.94 Feb 20th President’s Day Invite
39 Santa Clara** Win 13-3 2139.36 Ignored Mar 11th Stanford Invite Womens
17 California-San Diego** Win 12-5 2424.58 Ignored Mar 11th Stanford Invite Womens
11 Oregon Win 10-7 2486.48 Mar 11th Stanford Invite Womens
31 California** Win 11-4 2257.96 Ignored Mar 12th Stanford Invite Womens
9 Washington Win 13-12 2308.52 Mar 12th Stanford Invite Womens
1 North Carolina Loss 3-13 2337.91 Mar 12th Stanford Invite Womens
8 Stanford Win 13-9 2651.89 Mar 25th Northwest Challenge1
74 Utah** Win 13-0 1824.4 Ignored Mar 25th Northwest Challenge1
15 Victoria** Win 13-2 2452.64 Ignored Mar 25th Northwest Challenge1
7 Carleton College Win 13-8 2774.51 Mar 26th Northwest Challenge1
9 Washington Win 13-10 2511.67 Mar 26th Northwest Challenge1
2 British Columbia Win 13-11 2777.14 Mar 26th Northwest Challenge1
**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)