#116 West Chester (14-5)

avg: 1192.17  •  sd: 71.33  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
223 Colby Win 9-5 1235.45 Feb 22nd Bring The Huckus 2025
171 Dickinson Win 9-8 1078.2 Feb 22nd Bring The Huckus 2025
218 MIT Win 8-7 864.3 Feb 22nd Bring The Huckus 2025
171 Dickinson Loss 14-15 828.2 Feb 23rd Bring The Huckus 2025
217 Haverford Win 12-8 1182.73 Feb 23rd Bring The Huckus 2025
246 Skidmore Win 15-9 1145.94 Feb 23rd Bring The Huckus 2025
56 Cornell Loss 7-11 1057.05 Mar 1st Oak Creek Challenge 2025
105 Liberty Win 7-2 1832.91 Mar 1st Oak Creek Challenge 2025
226 SUNY-Albany Win 12-3 1297.07 Mar 1st Oak Creek Challenge 2025
157 Johns Hopkins Loss 8-11 640.23 Mar 2nd Oak Creek Challenge 2025
113 Lehigh Win 9-7 1483.58 Mar 2nd Oak Creek Challenge 2025
138 RIT Win 11-10 1217.92 Mar 2nd Oak Creek Challenge 2025
157 Johns Hopkins Win 11-8 1371.45 Mar 29th East Coast Invite 2025
179 Pennsylvania Win 14-5 1511.9 Mar 29th East Coast Invite 2025
83 SUNY-Buffalo Loss 7-13 763.39 Mar 29th East Coast Invite 2025
102 Syracuse Loss 10-15 806.78 Mar 29th East Coast Invite 2025
98 Boston College Win 11-10 1396.7 Mar 30th East Coast Invite 2025
131 Pittsburgh-B Win 13-11 1350.14 Mar 30th East Coast Invite 2025
128 SUNY-Binghamton Win 9-5 1657.13 Mar 30th East Coast Invite 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)