#56 Emory (11-10)

avg: 1447.58  •  sd: 47.45  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
52 Virginia Tech Win 12-10 1713.65 Feb 2nd Florida Warm Up 2024
19 Washington University Loss 5-13 1265.17 Feb 2nd Florida Warm Up 2024
4 Massachusetts Loss 6-13 1634.96 Feb 2nd Florida Warm Up 2024
185 South Florida Win 13-5 1466.3 Feb 3rd Florida Warm Up 2024
42 Michigan Win 12-11 1691.42 Feb 3rd Florida Warm Up 2024
7 Pittsburgh Loss 10-15 1639.54 Feb 3rd Florida Warm Up 2024
21 Tufts Loss 4-15 1228.7 Feb 4th Florida Warm Up 2024
74 Cincinnati Win 13-10 1689.34 Feb 24th Easterns Qualifier 2024
169 Rutgers Win 11-6 1498.33 Feb 24th Easterns Qualifier 2024
28 North Carolina-Wilmington Loss 9-12 1389.14 Feb 24th Easterns Qualifier 2024
68 James Madison Win 10-9 1501.89 Feb 24th Easterns Qualifier 2024
57 Auburn Loss 10-11 1322.19 Feb 25th Easterns Qualifier 2024
27 Georgia Tech Loss 7-15 1140.14 Feb 25th Easterns Qualifier 2024
52 Virginia Tech Win 10-9 1600.52 Feb 25th Easterns Qualifier 2024
60 Temple Loss 8-13 938.87 Feb 25th Easterns Qualifier 2024
85 Carnegie Mellon Win 15-12 1618.82 Mar 30th Atlantic Coast Open 2024
58 Maryland Loss 11-14 1129.63 Mar 30th Atlantic Coast Open 2024
90 SUNY-Buffalo Win 12-11 1400.01 Mar 30th Atlantic Coast Open 2024
126 Lehigh Win 14-10 1544.1 Mar 30th Atlantic Coast Open 2024
61 William & Mary Loss 14-15 1307.01 Mar 31st Atlantic Coast Open 2024
58 Maryland Win 15-12 1743.46 Mar 31st Atlantic Coast Open 2024
**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)