#48 Maryland (13-5)

avg: 1565.66  •  sd: 60.47  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
71 Case Western Reserve Win 13-10 1733.21 Feb 1st Carolina Kickoff mens 2025
97 Duke Win 13-8 1769.58 Feb 1st Carolina Kickoff mens 2025
3 North Carolina** Loss 2-13 1606.12 Ignored Feb 1st Carolina Kickoff mens 2025
49 North Carolina State Win 13-12 1689.8 Feb 2nd Carolina Kickoff mens 2025
27 South Carolina Loss 11-14 1466.26 Feb 2nd Carolina Kickoff mens 2025
32 Virginia Win 15-13 1894.05 Feb 2nd Carolina Kickoff mens 2025
35 Chicago Loss 7-13 1096.8 Feb 15th Queen City Tune Up 2025
17 Tufts Loss 8-13 1400.85 Feb 15th Queen City Tune Up 2025
52 William & Mary Win 13-12 1676.49 Feb 15th Queen City Tune Up 2025
65 Tennessee Win 9-8 1578.54 Feb 16th Queen City Tune Up 2025
101 Yale Win 7-3 1862.48 Feb 16th Queen City Tune Up 2025
75 Carnegie Mellon Win 15-11 1752.41 Mar 29th East Coast Invite 2025
108 Columbia Win 11-10 1344.19 Mar 29th East Coast Invite 2025
56 Cornell Win 11-10 1648.94 Mar 29th East Coast Invite 2025
174 Delaware** Win 14-6 1538.01 Ignored Mar 29th East Coast Invite 2025
75 Carnegie Mellon Win 10-8 1633.92 Mar 30th East Coast Invite 2025
56 Cornell Win 10-8 1786.61 Mar 30th East Coast Invite 2025
83 SUNY-Buffalo Loss 5-8 867.32 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)