#116 Liberty (12-6)

avg: 1182.96  •  sd: 57.65  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
85 Carnegie Mellon Loss 9-12 972.96 Jan 27th Mid Atlantic Warm Up
156 Johns Hopkins Win 9-8 1144.03 Jan 27th Mid Atlantic Warm Up
73 Richmond Loss 7-12 843.75 Jan 27th Mid Atlantic Warm Up
165 RIT Win 13-9 1383.86 Jan 27th Mid Atlantic Warm Up
96 Connecticut Loss 10-12 1011.28 Jan 28th Mid Atlantic Warm Up
123 Pennsylvania Win 11-8 1513.09 Jan 28th Mid Atlantic Warm Up
298 Mary Washington Win 12-9 709.15 Jan 28th Mid Atlantic Warm Up
102 Davenport Win 12-8 1658.42 Feb 17th Commonwealth Cup Weekend 1 2024
238 Wake Forest Win 13-2 1275.13 Feb 17th Commonwealth Cup Weekend 1 2024
99 Elon Loss 9-11 993.3 Feb 18th Commonwealth Cup Weekend 1 2024
199 Messiah Win 13-7 1389.77 Feb 18th Commonwealth Cup Weekend 1 2024
144 Pittsburgh-B Win 11-9 1311.23 Feb 18th Commonwealth Cup Weekend 1 2024
271 High Point** Win 13-0 1111.1 Ignored Mar 23rd Needle in a Ho Stack 2024
158 Kennesaw State Win 10-9 1135.72 Mar 23rd Needle in a Ho Stack 2024
125 Davidson Loss 9-10 1021.57 Mar 24th Needle in a Ho Stack 2024
189 East Carolina Win 12-2 1462.04 Mar 24th Needle in a Ho Stack 2024
64 Georgia State Loss 7-10 1022.15 Mar 24th Needle in a Ho Stack 2024
296 South Carolina-B** Win 11-1 969.12 Ignored Mar 24th Needle in a Ho Stack 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)