#42 Penn State (10-8)

avg: 1525.71  •  sd: 52.07  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
53 Appalachian State Win 13-12 1558.14 Jan 28th Carolina Kickoff
55 Georgetown Win 14-12 1632.11 Jan 28th Carolina Kickoff
2 North Carolina** Loss 5-15 1538.39 Ignored Jan 28th Carolina Kickoff
40 Duke Win 14-12 1751.54 Jan 28th Carolina Kickoff
55 Georgetown Win 15-11 1792.32 Jan 29th Carolina Kickoff
24 North Carolina-Charlotte Loss 12-15 1399.93 Jan 29th Carolina Kickoff
40 Duke Win 15-11 1911.75 Jan 29th Carolina Kickoff
95 Chicago Win 14-9 1688.57 Feb 11th Queen City Tune Up1
35 Washington University Loss 11-13 1380.45 Feb 11th Queen City Tune Up1
25 North Carolina-Wilmington Loss 12-13 1569.13 Feb 11th Queen City Tune Up1
15 North Carolina State Loss 5-15 1205.28 Feb 11th Queen City Tune Up1
53 Appalachian State Loss 12-13 1308.14 Feb 12th Queen City Tune Up1
73 Purdue Win 8-7 1459.71 Feb 12th Queen City Tune Up1
122 Carnegie Mellon Win 11-5 1682.27 Mar 4th Fish Bowl
25 North Carolina-Wilmington Loss 6-11 1147.43 Mar 4th Fish Bowl
51 James Madison Win 10-8 1699.87 Mar 5th Fish Bowl
46 Rutgers Win 11-9 1710.67 Mar 5th Fish Bowl
25 North Carolina-Wilmington Loss 6-11 1147.43 Mar 5th Fish Bowl
**Blowout Eligible

FAQ

What is the uncertainty of the mean?
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
What's the algorithm again?
  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
Is there a longer explanation of all this?
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)