#2 North Carolina (19-1)

avg: 2138.39  •  sd: 45.76  •  top 16/20: 100%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
40 Duke Win 15-10 1984.19 Jan 27th Carolina Kickoff
53 Appalachian State Win 15-9 1948.62 Jan 28th Carolina Kickoff
55 Georgetown Win 15-8 1975.96 Jan 28th Carolina Kickoff
42 Penn State** Win 15-5 2125.71 Ignored Jan 28th Carolina Kickoff
75 Richmond** Win 15-6 1912 Ignored Jan 29th Carolina Kickoff
17 South Carolina Win 15-6 2373.87 Jan 29th Carolina Kickoff
15 North Carolina State Win 15-8 2370.09 Jan 29th Carolina Kickoff
47 Case Western Reserve Win 15-10 1908.98 Feb 11th Queen City Tune Up1
73 Purdue** Win 15-6 1934.71 Ignored Feb 11th Queen City Tune Up1
24 North Carolina-Charlotte Win 15-11 2081.58 Feb 11th Queen City Tune Up1
61 Harvard Win 15-7 1988.46 Feb 11th Queen City Tune Up1
13 Tufts Win 15-6 2458.18 Feb 12th Queen City Tune Up1
19 Ohio State Win 10-8 2008.53 Feb 12th Queen City Tune Up1
18 Brown Win 13-9 2164.72 Mar 4th Smoky Mountain Invite
58 Auburn Win 13-6 2000.05 Mar 4th Smoky Mountain Invite
12 Carleton College Win 13-8 2359.65 Mar 4th Smoky Mountain Invite
21 Georgia Win 13-11 1965.16 Mar 4th Smoky Mountain Invite
1 Massachusetts Loss 12-15 1919.75 Mar 5th Smoky Mountain Invite
4 Texas Win 15-8 2586.31 Mar 5th Smoky Mountain Invite
6 Colorado Win 15-13 2206.58 Mar 5th Smoky Mountain Invite
**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)