#339 Delaware-B (8-8)

avg: 531.99  •  sd: 72.25  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
267 SUNY-Geneseo Loss 7-8 674.71 Feb 22nd Bring The Huckus 2025
235 Skidmore Loss 6-9 496.63 Feb 22nd Bring The Huckus 2025
314 Rowan Loss 5-13 23.62 Feb 22nd Bring The Huckus 2025
356 Lehigh-B Win 13-3 1011.44 Feb 22nd Bring The Huckus 2025
331 Hofstra Loss 7-9 291.56 Feb 23rd Bring The Huckus 2025
413 American-B** Win 13-2 285.62 Ignored Apr 12th Colonial Dev Mens Conferences 2025
404 Georgetown-B Win 12-5 580.28 Apr 12th Colonial Dev Mens Conferences 2025
396 Maryland-B Win 13-4 707.67 Apr 12th Colonial Dev Mens Conferences 2025
401 George Washington-B Win 12-5 613.1 Apr 13th Colonial Dev Mens Conferences 2025
396 Maryland-B Win 11-6 654.36 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
343 Virginia-B Win 11-7 969.74 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
205 North Carolina State-B Loss 5-8 586.9 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
334 South Carolina-B Loss 5-11 -39.55 Apr 26th Atlantic Coast Dev College Mens Regionals 2025
264 Virginia Tech-B Loss 6-13 206.34 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
205 North Carolina State-B Loss 7-13 482.97 Apr 27th Atlantic Coast Dev College Mens Regionals 2025
334 South Carolina-B Win 8-7 685.45 Apr 27th Atlantic Coast Dev College Mens Regionals 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)