#58 Penn State (9-9)

avg: 1451.04  •  sd: 57.95  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
25 Clemson Loss 0-13 1272.28 Feb 9th Queen City Tune Up 2019 Women
38 Florida Win 9-7 1890.45 Feb 9th Queen City Tune Up 2019 Women
11 Pittsburgh** Loss 2-12 1483.27 Ignored Feb 9th Queen City Tune Up 2019 Women
41 Harvard Loss 7-10 1177.99 Feb 9th Queen City Tune Up 2019 Women
57 Cornell Win 10-8 1723.28 Feb 10th Queen City Tune Up 2019 Women
40 Michigan Loss 12-14 1348.48 Feb 10th Queen City Tune Up 2019 Women
1 North Carolina** Loss 1-13 1930.07 Ignored Feb 23rd Commonwealth Cup 2019
28 North Carolina State Loss 7-13 1216.13 Feb 23rd Commonwealth Cup 2019
22 Tufts Loss 4-13 1334.61 Feb 23rd Commonwealth Cup 2019
44 Brown Win 12-11 1679.41 Feb 24th Commonwealth Cup 2019
31 West Chester Loss 10-13 1385.88 Feb 24th Commonwealth Cup 2019
201 Indiana** Win 12-5 1138.64 Ignored Mar 23rd CWRUL Memorial 2019
79 Ball State Loss 9-10 1148.29 Mar 23rd CWRUL Memorial 2019
104 Boston College Win 10-7 1484.64 Mar 23rd CWRUL Memorial 2019
91 Case Western Reserve Win 13-12 1327.67 Mar 23rd CWRUL Memorial 2019
111 Michigan State Win 12-8 1499.4 Mar 24th CWRUL Memorial 2019
85 Dayton Win 10-5 1817.21 Mar 24th CWRUL Memorial 2019
94 Carnegie Mellon Win 12-9 1530.08 Mar 24th CWRUL Memorial 2019
**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)