#344 South Carolina-B (2-13)

avg: 129.6  •  sd: 70.71  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
105 Liberty** Loss 0-11 632.91 Ignored Feb 15th 2025 Commonwealth Cup Weekend 1
199 North Carolina State-B** Loss 2-7 217.07 Ignored Feb 16th 2025 Commonwealth Cup Weekend 1
230 West Virginia Loss 2-8 85.38 Feb 16th 2025 Commonwealth Cup Weekend 1
119 Central Florida** Loss 6-15 581.39 Ignored Mar 1st Joint Summit 2025
127 Clemson** Loss 1-13 534.14 Ignored Mar 1st Joint Summit 2025
198 Georgia State** Loss 5-13 235.3 Ignored Mar 1st Joint Summit 2025
187 North Carolina-B** Loss 4-11 264.39 Ignored Mar 1st Joint Summit 2025
350 Clemson-B Win 12-9 455.77 Mar 2nd Joint Summit 2025
257 East Tennessee State Loss 10-15 126.64 Mar 2nd Joint Summit 2025
249 Cedarville Loss 8-13 116.64 Mar 29th Needle in a Ho Stack 2025
94 Tennessee-Chattanooga** Loss 3-13 679.56 Ignored Mar 29th Needle in a Ho Stack 2025
255 Wake Forest Loss 5-7 258.34 Mar 29th Needle in a Ho Stack 2025
249 Cedarville Loss 2-11 12.8 Mar 30th Needle in a Ho Stack 2025
252 Embry-Riddle Loss 4-15 -9.57 Mar 30th Needle in a Ho Stack 2025
370 Morehouse Win 9-8 50.06 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)