#93 Cincinnati (6-13)

avg: 1363.42  •  sd: 60.28  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
30 Auburn Loss 6-12 1129.95 Feb 16th Warm Up A Florida Affair 2018
52 Harvard Loss 11-13 1307.17 Feb 16th Warm Up A Florida Affair 2018
168 South Florida Win 13-11 1292.83 Feb 16th Warm Up A Florida Affair 2018
18 Brigham Young Loss 8-13 1357.23 Feb 16th Warm Up A Florida Affair 2018
4 Minnesota** Loss 5-12 1469.92 Ignored Feb 17th Warm Up A Florida Affair 2018
2 Carleton College Loss 9-13 1809.63 Feb 17th Warm Up A Florida Affair 2018
45 Illinois State Loss 9-15 1070.67 Feb 18th Warm Up A Florida Affair 2018
42 Connecticut Win 15-11 1976.72 Feb 18th Warm Up A Florida Affair 2018
180 Pittsburgh-B Win 9-6 1430.45 Mar 24th CWRUL Memorial 2018
94 Kentucky Loss 9-10 1237.66 Mar 24th CWRUL Memorial 2018
106 RIT Win 13-8 1811.91 Mar 24th CWRUL Memorial 2018
144 Dayton Win 11-10 1278.53 Mar 25th CWRUL Memorial 2018
94 Kentucky Loss 8-11 997.05 Mar 25th CWRUL Memorial 2018
50 Notre Dame Loss 4-12 939.28 Mar 25th CWRUL Memorial 2018
240 Tennessee Tech Win 15-4 1389.41 Mar 25th CWRUL Memorial 2018
30 Auburn Loss 12-15 1408.77 Mar 31st Easterns 2018
6 Brown Loss 9-15 1531.23 Mar 31st Easterns 2018
20 Cal Poly-SLO Loss 9-15 1327.64 Mar 31st Easterns 2018
10 Virginia Tech Loss 7-15 1323.3 Mar 31st Easterns 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)