#130 Penn State-B (16-4)

avg: 1379.42  •  sd: 93.27  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
359 Bentley Win 9-4 1053.96 Mar 2nd Philly Special 2024
115 Bowdoin Win 9-8 1561.94 Mar 2nd Philly Special 2024
259 Brandeis Win 13-2 1514.93 Mar 3rd Philly Special 2024
187 College of New Jersey Win 11-9 1412.63 Mar 3rd Philly Special 2024
310 Stevens Tech** Win 13-3 1278.83 Ignored Mar 3rd Philly Special 2024
240 SUNY-Albany Win 13-7 1545.31 Mar 3rd Philly Special 2024
139 Army Loss 9-11 1099.14 Mar 16th Free Tournament
364 Rensselaer Polytech** Win 13-5 1032.24 Ignored Mar 16th Free Tournament
126 Towson Win 13-7 1946.62 Mar 16th Free Tournament
171 Scranton Win 13-7 1795.72 Mar 16th Free Tournament
139 Army Win 15-6 1948.35 Mar 17th Free Tournament
367 Dartmouth-B** Win 15-5 1017.54 Ignored Mar 17th Free Tournament
126 Towson Win 12-8 1830.24 Mar 17th Free Tournament
402 Case Western Reserve-B** Win 13-1 638.41 Ignored Apr 20th Ohio Valley Dev Mens Conferences 2024
127 Pittsburgh-B Loss 10-13 1060.59 Apr 20th Ohio Valley Dev Mens Conferences 2024
407 West Chester-B** Win 13-1 467.56 Ignored Apr 20th Ohio Valley Dev Mens Conferences 2024
127 Pittsburgh-B Win 15-14 1513.73 Apr 21st Ohio Valley Dev Mens Conferences 2024
292 Kent State Win 14-11 1060.96 May 4th Ohio Valley D I College Mens Regionals 2024
97 Lehigh Loss 9-15 1010.86 May 4th Ohio Valley D I College Mens Regionals 2024
92 Pennsylvania Loss 3-15 939.36 May 4th Ohio Valley D I College Mens Regionals 2024
**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)