#119 Clemson (8-17)

avg: 1283.55  •  sd: 54.08  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
61 Tennessee Win 13-8 2050.35 Jan 25th Carolina Kickoff 2019
25 South Carolina Loss 6-12 1207.38 Jan 26th Carolina Kickoff 2019
69 Emory Loss 6-12 929.15 Jan 26th Carolina Kickoff 2019
52 Notre Dame Loss 6-9 1208.1 Jan 26th Carolina Kickoff 2019
62 Duke Loss 8-15 986.2 Jan 27th Carolina Kickoff 2019
66 Penn State Loss 9-11 1286.04 Feb 9th Queen City Tune Up 2019 Men
79 Tulane Win 11-10 1581.42 Feb 9th Queen City Tune Up 2019 Men
47 Maryland Loss 10-12 1418.21 Feb 9th Queen City Tune Up 2019 Men
9 Massachusetts** Loss 3-13 1465.5 Ignored Feb 9th Queen City Tune Up 2019 Men
24 Auburn Loss 6-15 1196.78 Feb 10th Queen City Tune Up 2019 Men
52 Notre Dame Loss 8-14 1090.63 Feb 10th Queen City Tune Up 2019 Men
79 Tulane Loss 6-7 1331.42 Feb 10th Queen City Tune Up 2019 Men
53 Indiana Loss 5-9 1097.56 Feb 16th Easterns Qualifier 2019
197 George Mason Win 12-10 1239.52 Feb 16th Easterns Qualifier 2019
81 Georgia Tech Loss 9-13 1028.75 Feb 16th Easterns Qualifier 2019
64 Ohio Loss 7-13 981.87 Feb 16th Easterns Qualifier 2019
139 Pennsylvania Win 15-12 1530.16 Feb 17th Easterns Qualifier 2019
126 New Hampshire Win 12-10 1513.54 Feb 17th Easterns Qualifier 2019
101 Connecticut Win 13-12 1481.24 Feb 17th Easterns Qualifier 2019
103 Georgia State Loss 6-11 801.68 Mar 16th Tally Classic XIV
43 Harvard Loss 6-12 1092.97 Mar 16th Tally Classic XIV
79 Tulane Win 10-9 1581.42 Mar 16th Tally Classic XIV
52 Notre Dame Loss 14-15 1501.67 Mar 16th Tally Classic XIV
159 Mississippi State Win 15-11 1506.97 Mar 17th Tally Classic XIV
88 Tennessee-Chattanooga Loss 12-15 1118.69 Mar 17th Tally Classic XIV
**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)