#336 Pennsylvania Western (6-11)

avg: 556.96  •  sd: 105.37  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
325 Central Connecticut State Loss 7-8 472.71 Mar 1st Garden State 2025
277 Salisbury Loss 6-8 479.09 Mar 1st Garden State 2025
310 Swarthmore Loss 5-10 63.45 Mar 1st Garden State 2025
318 Massachusetts-Lowell Loss 3-6 65.56 Mar 1st Garden State 2025
356 Cornell-B Loss 3-9 -200.62 Mar 2nd Garden State 2025
318 Massachusetts-Lowell Loss 1-15 12.25 Mar 2nd Garden State 2025
383 West Chester-B Win 12-6 805.95 Mar 29th Northeast Classic 2025
417 Siena** Win 13-2 187.6 Ignored Mar 29th Northeast Classic 2025
313 Rowan Win 10-5 1202.66 Mar 29th Northeast Classic 2025
381 SUNY-Binghamton-B Win 10-6 740.81 Mar 29th Northeast Classic 2025
192 Vassar Loss 3-13 493.07 Mar 30th Northeast Classic 2025
328 SUNY-Cortland Win 13-10 909.95 Mar 30th Northeast Classic 2025
213 Vermont-C Loss 8-13 524.64 Mar 30th Northeast Classic 2025
88 Carnegie Mellon Loss 11-15 1125.41 Apr 12th West Penn D I Mens Conferences 2025
22 Penn State** Loss 2-15 1392.96 Ignored Apr 12th West Penn D I Mens Conferences 2025
226 West Virginia Loss 3-15 363.48 Apr 12th West Penn D I Mens Conferences 2025
424 Slippery Rock Win 15-6 600 Ignored Apr 13th West Penn D I Mens Conferences 2025
**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)