#36 Colorado College (9-15)

avg: 2033.18  •  sd: 57.24  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
13 Ohio State Loss 8-10 2142.26 Feb 3rd Queen City Tune Up 2018 College Women
12 Carleton College Loss 6-13 1821.97 Feb 3rd Queen City Tune Up 2018 College Women
41 Georgia Tech Loss 9-10 1884.42 Feb 3rd Queen City Tune Up 2018 College Women
21 Michigan Loss 8-11 1872.82 Feb 3rd Queen City Tune Up 2018 College Women
79 Chicago Win 13-5 2253.38 Feb 17th Presidents Day Invitational Tournament 2018
105 Chico State Win 13-3 2079.34 Feb 17th Presidents Day Invitational Tournament 2018
55 Iowa State Win 13-4 2446.46 Feb 17th Presidents Day Invitational Tournament 2018
4 Stanford Loss 9-10 2570.52 Feb 17th Presidents Day Invitational Tournament 2018
16 Western Washington Loss 10-12 2106.26 Feb 18th Presidents Day Invitational Tournament 2018
33 UCLA Loss 11-13 1833.85 Feb 18th Presidents Day Invitational Tournament 2018
9 Colorado Loss 6-14 1899.69 Feb 18th Presidents Day Invitational Tournament 2018
61 California-Davis Win 15-0 2417.92 Feb 19th Presidents Day Invitational Tournament 2018
20 Washington Loss 8-11 1874.63 Feb 19th Presidents Day Invitational Tournament 2018
131 Air Force Academy Win 9-5 1814.73 Mar 3rd Air Force Invite 2018
18 Brigham Young Loss 9-11 2037.3 Mar 3rd Air Force Invite 2018
- Colorado School of Mines** Win 13-1 1248.69 Ignored Mar 3rd Air Force Invite 2018
154 Colorado-B Win 7-3 1752.21 Mar 4th Air Force Invite 2018
104 Denver Win 9-4 2081.51 Mar 4th Air Force Invite 2018
2 California-San Diego** Loss 4-13 2132.82 Ignored Mar 24th NW Challenge 2018
17 California-Santa Barbara Loss 7-15 1720.26 Mar 24th NW Challenge 2018
35 Cal Poly-SLO Loss 12-13 1911.55 Mar 24th NW Challenge 2018
38 Victoria Win 11-8 2385.81 Mar 24th NW Challenge 2018
12 Carleton College Loss 5-15 1821.97 Mar 25th NW Challenge 2018
26 California Loss 10-11 2008.23 Mar 25th NW Challenge 2018
**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)