#217 Haverford (11-8)

avg: 741.57  •  sd: 73.36  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
174 Delaware Win 9-8 1063.01 Feb 22nd Bring The Huckus 2025
176 Ithaca Loss 5-12 332.06 Feb 22nd Bring The Huckus 2025
328 Hofstra Win 13-3 840.55 Feb 22nd Bring The Huckus 2025
218 MIT Win 10-8 1001.97 Feb 23rd Bring The Huckus 2025
116 West Chester Loss 8-12 751.02 Feb 23rd Bring The Huckus 2025
176 Ithaca Win 9-5 1461.12 Feb 23rd Bring The Huckus 2025
112 Bowdoin Loss 5-10 630.68 Mar 1st Garden State 2025
279 Brown-B Win 10-7 855.84 Mar 1st Garden State 2025
234 Penn State-B Win 8-7 781.34 Mar 1st Garden State 2025
151 Rhode Island Loss 4-9 451.19 Mar 1st Garden State 2025
237 Connecticut College Win 8-7 774.5 Mar 2nd Garden State 2025
231 Salisbury Loss 8-10 421.96 Mar 2nd Garden State 2025
347 Army Win 11-6 664.99 Mar 29th Northeast Classic 2025
235 College of New Jersey Loss 9-11 406.78 Mar 29th Northeast Classic 2025
336 SUNY-Cortland Win 13-6 791.65 Mar 29th Northeast Classic 2025
234 Penn State-B Loss 8-10 393.68 Mar 29th Northeast Classic 2025
235 College of New Jersey Win 13-5 1255.99 Mar 30th Northeast Classic 2025
176 Ithaca Loss 7-13 374.53 Mar 30th Northeast Classic 2025
275 SUNY-Geneseo Win 12-7 1001.54 Mar 30th Northeast Classic 2025
**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)