#71 Carnegie Mellon (11-14)

avg: 1278.34  •  sd: 58.77  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
151 Boston College Win 10-7 1083.05 Feb 22nd 2025 Commonwealth Cup Weekend 2
62 Chicago Loss 5-13 743.7 Feb 22nd 2025 Commonwealth Cup Weekend 2
43 Duke Loss 4-9 964.4 Feb 22nd 2025 Commonwealth Cup Weekend 2
34 Cornell Loss 3-13 1040.76 Feb 22nd 2025 Commonwealth Cup Weekend 2
131 Harvard Loss 7-8 708.3 Feb 23rd 2025 Commonwealth Cup Weekend 2
74 Purdue Loss 5-12 660.76 Feb 23rd 2025 Commonwealth Cup Weekend 2
104 Yale Win 10-7 1430.3 Mar 29th East Coast Invite 2025
38 MIT Loss 9-11 1338.39 Mar 29th East Coast Invite 2025
75 Penn State Win 7-5 1586.79 Mar 29th East Coast Invite 2025
79 Columbia Win 9-8 1343.99 Mar 29th East Coast Invite 2025
39 Wesleyan Win 9-6 2005.4 Mar 30th East Coast Invite 2025
24 Minnesota Loss 5-15 1221.36 Mar 30th East Coast Invite 2025
25 Georgetown Loss 5-10 1225.9 Mar 30th East Coast Invite 2025
20 Pennsylvania** Loss 5-13 1312.4 Ignored Apr 12th Pennsylvania D I Womens Conferences 2025
109 Temple Win 8-7 1146.02 Apr 12th Pennsylvania D I Womens Conferences 2025
115 West Chester Win 9-5 1480.02 Apr 12th Pennsylvania D I Womens Conferences 2025
31 Pittsburgh Loss 7-11 1224.25 Apr 13th Pennsylvania D I Womens Conferences 2025
75 Penn State Win 7-6 1383.65 Apr 13th Pennsylvania D I Womens Conferences 2025
124 Cincinnati Win 9-5 1441.02 Apr 26th Ohio Valley D I College Womens Regionals 2025
20 Pennsylvania Loss 5-8 1458.8 Apr 26th Ohio Valley D I College Womens Regionals 2025
109 Temple Win 9-5 1550.08 Apr 26th Ohio Valley D I College Womens Regionals 2025
32 Ohio Loss 6-10 1174.92 Apr 26th Ohio Valley D I College Womens Regionals 2025
22 Ohio State** Loss 3-15 1291.53 Ignored Apr 27th Ohio Valley D I College Womens Regionals 2025
81 Case Western Reserve Loss 7-8 1075.8 Apr 27th Ohio Valley D I College Womens Regionals 2025
124 Cincinnati Win 11-5 1511.96 Apr 27th Ohio Valley D I College Womens Regionals 2025
**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)