#38 Purdue (14-6)

avg: 1707.04  •  sd: 51.78  •  top 16/20: 0.1%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
120 James Madison Win 13-7 1840.33 Feb 16th Easterns Qualifier 2019
139 Pennsylvania Win 13-11 1458.51 Feb 16th Easterns Qualifier 2019
39 Vermont Loss 7-13 1148.24 Feb 16th Easterns Qualifier 2019
165 Georgia Southern** Win 13-3 1691.91 Ignored Feb 16th Easterns Qualifier 2019
33 Johns Hopkins Loss 13-15 1516.99 Feb 17th Easterns Qualifier 2019
61 Tennessee Win 13-10 1882.33 Feb 17th Easterns Qualifier 2019
39 Vermont Loss 14-15 1580.77 Feb 17th Easterns Qualifier 2019
135 University of Pittsburgh-B Win 13-4 1843.04 Mar 23rd CWRUL Memorial 2019
160 Vanderbilt Win 13-7 1681.91 Mar 23rd CWRUL Memorial 2019
64 Ohio Win 13-11 1768.24 Mar 23rd CWRUL Memorial 2019
183 Oberlin Win 15-8 1606.77 Mar 24th CWRUL Memorial 2019
132 Kentucky Win 15-8 1815.97 Mar 24th CWRUL Memorial 2019
64 Ohio Loss 10-13 1211.26 Mar 24th CWRUL Memorial 2019
87 Case Western Reserve Win 15-8 1987.37 Mar 24th CWRUL Memorial 2019
92 John Brown Win 11-9 1626.88 Mar 30th Huck Finn XXIII
152 Arkansas Win 11-2 1753.2 Mar 30th Huck Finn XXIII
46 Iowa State Win 9-7 1938.57 Mar 31st Huck Finn XXIII
31 Texas A&M Win 11-7 2215.3 Mar 31st Huck Finn XXIII
18 Michigan Loss 8-10 1646.1 Mar 31st Huck Finn XXIII
23 Texas Tech Loss 9-10 1706.13 Mar 31st Huck Finn XXIII
**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)