#75 Tennessee-Chattanooga (16-9)

avg: 1415.67  •  sd: 79.02  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
244 Berry Win 11-9 1032.85 Jan 27th Clutch Classic 2018
418 Kennesaw State-B** Win 13-0 445.2 Ignored Jan 27th Clutch Classic 2018
224 Georgia Southern Win 12-5 1461.24 Jan 27th Clutch Classic 2018
376 Tulane-B** Win 13-1 878 Ignored Jan 27th Clutch Classic 2018
140 Florida Tech Loss 5-9 638.41 Jan 28th Clutch Classic 2018
282 Wingate** Win 15-5 1262.96 Ignored Jan 28th Clutch Classic 2018
33 Maryland Loss 8-13 1188.12 Feb 17th Easterns Qualifier 2018
51 Ohio State Win 13-8 2033.85 Feb 17th Easterns Qualifier 2018
46 South Carolina Loss 9-13 1160.8 Feb 17th Easterns Qualifier 2018
62 Vermont Loss 9-10 1340.83 Feb 17th Easterns Qualifier 2018
84 Virginia Win 11-10 1527.14 Feb 17th Easterns Qualifier 2018
61 James Madison Loss 14-15 1347.52 Feb 18th Easterns Qualifier 2018
64 North Carolina-Charlotte Loss 10-12 1224.38 Feb 18th Easterns Qualifier 2018
78 Georgetown Win 13-11 1643.91 Feb 18th Easterns Qualifier 2018
150 North Carolina-Asheville Win 12-10 1369.2 Mar 17th College Southerns 2018
248 North Georgia Win 13-8 1270.49 Mar 17th College Southerns 2018
125 Georgia College Win 13-7 1773.34 Mar 17th College Southerns 2018
69 Carleton College-GoP Win 12-11 1574.46 Mar 17th College Southerns 2018
207 Florida-B Win 13-5 1520.75 Mar 18th College Southerns 2018
125 Georgia College Loss 9-10 1090.81 Mar 18th College Southerns 2018
69 Carleton College-GoP Loss 5-13 849.46 Mar 18th College Southerns 2018
89 John Brown Loss 12-15 1081.81 Mar 31st Huck Finn 2018
95 Purdue Win 13-10 1681.08 Mar 31st Huck Finn 2018
58 Kansas Win 13-10 1829.01 Mar 31st Huck Finn 2018
76 Chicago Win 15-8 1980.12 Mar 31st Huck Finn 2018
**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)