#29 Georgia Tech (14-5)

avg: 2058.72  •  sd: 112.55  •  top 16/20: 4.5%

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# Opponent Result Game Rating Status Date Event
163 Florida State** Win 12-1 1447.3 Ignored Jan 25th Florida Winter Classic 2025
233 Florida-B** Win 13-0 835.72 Ignored Jan 25th Florida Winter Classic 2025
168 Miami (Florida)** Win 13-1 1410.09 Ignored Jan 25th Florida Winter Classic 2025
71 Central Florida Win 10-6 2053.48 Jan 26th Florida Winter Classic 2025
67 Florida Win 10-5 2176.52 Jan 26th Florida Winter Classic 2025
184 Georgia Southern** Win 13-0 1290.69 Ignored Jan 26th Florida Winter Classic 2025
37 American Loss 10-11 1771.84 Feb 22nd 2025 Commonwealth Cup Weekend 2
6 Vermont** Loss 5-14 2071.2 Ignored Feb 22nd 2025 Commonwealth Cup Weekend 2
21 Ohio State Win 10-9 2391.62 Feb 22nd 2025 Commonwealth Cup Weekend 2
36 MIT Win 9-8 2024.22 Feb 23rd 2025 Commonwealth Cup Weekend 2
20 Virginia Loss 8-10 2006.26 Feb 23rd 2025 Commonwealth Cup Weekend 2
34 Ohio Loss 8-10 1695.9 Feb 23rd 2025 Commonwealth Cup Weekend 2
19 Notre Dame Loss 10-11 2161.09 Feb 23rd 2025 Commonwealth Cup Weekend 2
114 Cedarville** Win 13-4 1811.01 Ignored Mar 29th Needle in a Ho Stack 2025
107 Virginia Tech** Win 13-5 1853.9 Ignored Mar 29th Needle in a Ho Stack 2025
215 South Carolina-B** Win 13-0 1049.8 Ignored Mar 29th Needle in a Ho Stack 2025
55 Appalachian State Win 13-8 2195.54 Mar 30th Needle in a Ho Stack 2025
141 Georgia College** Win 15-0 1612.61 Ignored Mar 30th Needle in a Ho Stack 2025
79 Tennessee Win 15-1 2078.92 Mar 30th Needle in a Ho Stack 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)