#75 Carnegie Mellon (10-8)

avg: 1371.25  •  sd: 55.87  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
180 American Win 12-6 1485.05 Jan 25th Mid Atlantic Warm Up 2025
184 East Carolina Win 9-7 1169.04 Jan 25th Mid Atlantic Warm Up 2025
101 Yale Win 12-9 1607.85 Jan 25th Mid Atlantic Warm Up 2025
64 James Madison Loss 9-11 1208.17 Jan 25th Mid Atlantic Warm Up 2025
66 Dartmouth Win 14-13 1577.25 Jan 26th Mid Atlantic Warm Up 2025
52 William & Mary Loss 9-15 1036.01 Jan 26th Mid Atlantic Warm Up 2025
104 Alabama Win 13-9 1657.53 Feb 15th Queen City Tune Up 2025
37 North Carolina-Wilmington Loss 9-10 1510.07 Feb 15th Queen City Tune Up 2025
27 South Carolina Loss 6-13 1179.6 Feb 15th Queen City Tune Up 2025
69 Auburn Win 7-6 1553.39 Feb 16th Queen City Tune Up 2025
51 Purdue Loss 7-10 1166.19 Feb 16th Queen City Tune Up 2025
48 Maryland Loss 11-15 1184.5 Mar 29th East Coast Invite 2025
128 SUNY-Binghamton Win 10-9 1253.07 Mar 29th East Coast Invite 2025
87 Temple Win 9-8 1435.92 Mar 29th East Coast Invite 2025
101 Yale Win 12-11 1387.48 Mar 29th East Coast Invite 2025
48 Maryland Loss 8-10 1303 Mar 30th East Coast Invite 2025
52 William & Mary Win 11-8 1917.1 Mar 30th East Coast Invite 2025
87 Temple Loss 5-7 982.78 Mar 30th East Coast Invite 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)