#23 Georgia Tech (17-4)

avg: 1743.96  •  sd: 101.28  •  top 16/20: 24.6%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
94 Kentucky Win 11-5 1962.66 Jan 20th T Town Throwdown XIV Open
431 Alabama-B** Win 13-1 109.63 Ignored Jan 20th T Town Throwdown XIV Open
231 Alabama-Birmingham** Win 13-2 1421.08 Ignored Jan 20th T Town Throwdown XIV Open
155 Vanderbilt** Win 13-5 1712.8 Ignored Jan 20th T Town Throwdown XIV Open
94 Kentucky Win 11-5 1962.66 Jan 21st T Town Throwdown XIV Open
88 Alabama-Huntsville Loss 12-13 1263.31 Jan 21st T Town Throwdown XIV Open
153 Xavier** Win 15-5 1715.49 Ignored Jan 21st T Town Throwdown XIV Open
40 Iowa Win 12-8 2065.96 Feb 17th Easterns Qualifier 2018
12 North Carolina State Win 11-10 2043.86 Feb 17th Easterns Qualifier 2018
133 Case Western Reserve Win 11-7 1642.66 Feb 17th Easterns Qualifier 2018
73 Michigan State Win 12-7 1940.06 Feb 17th Easterns Qualifier 2018
78 Georgetown Win 13-7 1972.6 Feb 17th Easterns Qualifier 2018
48 Dartmouth Win 15-8 2130.24 Feb 18th Easterns Qualifier 2018
33 Maryland Loss 14-16 1475.99 Feb 18th Easterns Qualifier 2018
46 South Carolina Win 13-5 2179.36 Feb 18th Easterns Qualifier 2018
52 Harvard Loss 9-15 1020.53 Mar 10th Tally Classic XIII
231 Alabama-Birmingham Win 13-6 1421.08 Mar 10th Tally Classic XIII
50 Notre Dame Win 13-10 1867.42 Mar 10th Tally Classic XIII
46 South Carolina Win 12-10 1817.49 Mar 10th Tally Classic XIII
81 Florida State Win 13-12 1533.72 Mar 10th Tally Classic XIII
28 Carnegie Mellon Loss 12-13 1593.65 Mar 11th Tally Classic XIII
**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)