#31 Georgia Tech (9-6)

avg: 1566.94  •  sd: 73.85  •  top 16/20: 1.9%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
14 Minnesota Loss 11-13 1583.35 Feb 2nd Florida Warm Up 2024
19 Pittsburgh Loss 10-13 1414.58 Feb 2nd Florida Warm Up 2024
45 Texas A&M Win 12-5 2030.98 Feb 2nd Florida Warm Up 2024
46 Florida Win 15-11 1811.02 Feb 3rd Florida Warm Up 2024
86 Florida State Win 13-2 1728.57 Feb 3rd Florida Warm Up 2024
9 Brown Loss 8-13 1390.01 Feb 3rd Florida Warm Up 2024
30 Washington University Loss 13-14 1468.67 Feb 4th Florida Warm Up 2024
58 Virginia Win 13-7 1888.1 Feb 24th Easterns Qualifier 2024
42 North Carolina-Charlotte Loss 8-11 1101.63 Feb 24th Easterns Qualifier 2024
88 Notre Dame Loss 10-11 987.7 Feb 24th Easterns Qualifier 2024
114 Harvard** Win 13-5 1566.79 Ignored Feb 24th Easterns Qualifier 2024
66 Emory Win 15-7 1855.29 Feb 25th Easterns Qualifier 2024
122 Lehigh Win 13-8 1438.08 Feb 25th Easterns Qualifier 2024
77 William & Mary Win 11-9 1454.27 Feb 25th Easterns Qualifier 2024
54 Alabama Win 15-9 1873.59 Feb 25th Easterns Qualifier 2024
**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)