#70 Carnegie Mellon (11-14)

avg: 1279.15  •  sd: 58.78  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
150 Boston College Win 10-7 1082.99 Feb 22nd 2025 Commonwealth Cup Weekend 2
63 Chicago Loss 5-13 744.44 Feb 22nd 2025 Commonwealth Cup Weekend 2
42 Duke Loss 4-9 965.5 Feb 22nd 2025 Commonwealth Cup Weekend 2
34 Cornell Loss 3-13 1041.42 Feb 22nd 2025 Commonwealth Cup Weekend 2
129 Harvard Loss 7-8 708.28 Feb 23rd 2025 Commonwealth Cup Weekend 2
72 Purdue Loss 5-12 660.94 Feb 23rd 2025 Commonwealth Cup Weekend 2
103 Yale Win 10-7 1430.68 Mar 29th East Coast Invite 2025
38 MIT Loss 9-11 1339.61 Mar 29th East Coast Invite 2025
74 Penn State Win 7-5 1587.87 Mar 29th East Coast Invite 2025
76 Columbia Win 9-8 1344.45 Mar 29th East Coast Invite 2025
39 Wesleyan Win 9-6 2005.89 Mar 30th East Coast Invite 2025
24 Minnesota Loss 5-15 1223.12 Mar 30th East Coast Invite 2025
26 Georgetown Loss 5-10 1227.1 Mar 30th East Coast Invite 2025
20 Pennsylvania** Loss 5-13 1312.93 Ignored Apr 12th Pennsylvania D I Womens Conferences 2025
109 Temple Win 8-7 1146.69 Apr 12th Pennsylvania D I Womens Conferences 2025
113 West Chester Win 9-5 1481.03 Apr 12th Pennsylvania D I Womens Conferences 2025
31 Pittsburgh Loss 7-11 1227.32 Apr 13th Pennsylvania D I Womens Conferences 2025
74 Penn State Win 7-6 1384.73 Apr 13th Pennsylvania D I Womens Conferences 2025
122 Cincinnati Win 9-5 1440.62 Apr 26th Ohio Valley D I College Womens Regionals 2025
20 Pennsylvania Loss 5-8 1459.33 Apr 26th Ohio Valley D I College Womens Regionals 2025
109 Temple Win 9-5 1550.75 Apr 26th Ohio Valley D I College Womens Regionals 2025
32 Ohio Loss 6-10 1175.6 Apr 26th Ohio Valley D I College Womens Regionals 2025
22 Ohio State** Loss 3-15 1293.06 Ignored Apr 27th Ohio Valley D I College Womens Regionals 2025
80 Case Western Reserve Loss 7-8 1076.55 Apr 27th Ohio Valley D I College Womens Regionals 2025
122 Cincinnati Win 11-5 1511.56 Apr 27th Ohio Valley D I College Womens Regionals 2025
**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)