#146 Clemson (12-9)

avg: 1318.35  •  sd: 52.46  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
195 Alabama-Birmingham Loss 10-11 1017.26 Feb 24th Joint Summit 2024
261 Georgia Tech-B Win 11-7 1371.17 Feb 24th Joint Summit 2024
346 Coastal Carolina** Win 12-2 1131.02 Ignored Feb 24th Joint Summit 2024
183 South Florida Win 10-9 1311.53 Feb 24th Joint Summit 2024
195 Alabama-Birmingham Win 13-12 1267.26 Feb 25th Joint Summit 2024
325 South Carolina-B** Win 13-5 1220.93 Ignored Feb 25th Joint Summit 2024
183 South Florida Win 13-8 1682.69 Feb 25th Joint Summit 2024
195 Alabama-Birmingham Win 10-9 1267.26 Mar 16th Tally Classic XVIII
48 Auburn Loss 4-13 1182.29 Mar 16th Tally Classic XVIII
82 Mississippi State Loss 6-13 982.9 Mar 16th Tally Classic XVIII
89 Florida State Loss 7-11 1084.39 Mar 16th Tally Classic XVIII
195 Alabama-Birmingham Win 6-4 1507.87 Mar 17th Tally Classic XVIII
372 North Florida** Win 13-2 955.74 Ignored Mar 17th Tally Classic XVIII
203 Spring Hill Win 13-12 1238.28 Mar 17th Tally Classic XVIII
50 Duke Loss 8-14 1236.48 Apr 13th Carolina D I Mens Conferences 2024
2 North Carolina Loss 10-15 2032.73 Apr 13th Carolina D I Mens Conferences 2024
215 East Carolina Win 9-8 1190.59 Apr 13th Carolina D I Mens Conferences 2024
27 North Carolina-Wilmington** Loss 6-15 1395.28 Ignored Apr 13th Carolina D I Mens Conferences 2024
72 Appalachian State Loss 10-14 1229.95 Apr 14th Carolina D I Mens Conferences 2024
196 Charleston Win 12-9 1478.9 Apr 14th Carolina D I Mens Conferences 2024
42 South Carolina Loss 4-15 1246.77 Apr 14th Carolina D I Mens Conferences 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)