#171 Dickinson (7-12)

avg: 953.2  •  sd: 64.76  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
223 Colby Win 13-5 1306.39 Feb 22nd Bring The Huckus 2025
116 West Chester Loss 8-9 1067.17 Feb 22nd Bring The Huckus 2025
218 MIT Win 9-7 1018.64 Feb 22nd Bring The Huckus 2025
174 Delaware Win 13-8 1434.17 Feb 23rd Bring The Huckus 2025
176 Ithaca Win 13-10 1260.2 Feb 23rd Bring The Huckus 2025
116 West Chester Win 15-14 1317.17 Feb 23rd Bring The Huckus 2025
180 American Win 12-8 1346.89 Mar 22nd Atlantic Coast Open 2025
184 East Carolina Loss 8-9 764.71 Mar 22nd Atlantic Coast Open 2025
357 George Washington-B** Win 15-2 628.03 Ignored Mar 22nd Atlantic Coast Open 2025
81 North Carolina-Charlotte Loss 7-11 855.36 Mar 22nd Atlantic Coast Open 2025
96 Appalachian State Loss 11-15 893.26 Mar 23rd Atlantic Coast Open 2025
113 Lehigh Loss 12-14 983.28 Mar 23rd Atlantic Coast Open 2025
115 Vermont-B Loss 12-14 973.76 Mar 23rd Atlantic Coast Open 2025
46 Middlebury** Loss 3-13 997.79 Ignored Mar 29th Easterns 2025
78 Richmond Loss 5-13 748.03 Mar 29th Easterns 2025
45 Elon** Loss 1-13 1005.05 Ignored Mar 29th Easterns 2025
70 Franciscan Loss 2-9 810.69 Mar 29th Easterns 2025
149 Davidson Loss 6-15 454.75 Mar 30th Easterns 2025
163 Messiah Loss 8-15 416.79 Mar 30th Easterns 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)