#26 Carleton College-Eclipse (15-6)

avg: 1552.11  •  sd: 160.12  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
118 California-San Diego-B Win 9-5 1304.62 Feb 4th Stanford Open
83 Nevada-Reno Win 10-2 1603.35 Feb 4th Stanford Open
61 Cal Poly-SLO Win 6-4 1571.88 Feb 4th Stanford Open
47 Santa Clara Win 8-6 1668.65 Feb 5th Stanford Open
172 Chico State** Win 12-1 790.14 Ignored Feb 5th Stanford Open
61 Cal Poly-SLO Win 10-5 1780.16 Feb 5th Stanford Open
8 Stanford Loss 4-13 1460.45 Feb 18th President’s Day Invite
18 Colorado State Win 10-9 1787.46 Feb 18th President’s Day Invite
11 Oregon Loss 7-12 1440.95 Feb 18th President’s Day Invite
35 UCLA Win 9-7 1735.83 Feb 18th President’s Day Invite
6 Colorado Loss 8-13 1693.38 Feb 19th President’s Day Invite
58 Texas Win 13-7 1847.46 Feb 19th President’s Day Invite
11 Oregon Loss 5-10 1387.56 Feb 19th President’s Day Invite
19 California-San Diego Loss 8-10 1390.46 Feb 20th President’s Day Invite
37 Duke Loss 7-10 1058.2 Feb 20th President’s Day Invite
203 Georgia-B** Win 13-0 -430.51 Ignored Mar 18th College Southerns XXI
133 Emory** Win 13-2 1199.63 Ignored Mar 18th College Southerns XXI
- Georgia Southern University** Win 13-0 -190.07 Ignored Mar 18th College Southerns XXI
202 Emory-B** Win 15-0 -181.4 Ignored Mar 19th College Southerns XXI
187 North Carolina-Wilmington** Win 15-0 525.37 Ignored Mar 19th College Southerns XXI
121 Charleston** Win 15-0 1364.36 Ignored Mar 19th College Southerns XXI
**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)