#95 Bowdoin (20-3)

avg: 1480.17  •  sd: 72.18  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
152 Rhode Island Loss 8-9 1143.42 Mar 1st Garden State 2025
210 Penn State-B Win 12-8 1468.69 Mar 1st Garden State 2025
197 Haverford Win 10-5 1652.37 Mar 1st Garden State 2025
262 Brown-B** Win 4-1 1429 Ignored Mar 1st Garden State 2025
247 Connecticut College Win 12-6 1468.87 Mar 2nd Garden State 2025
277 Salisbury** Win 13-4 1379.58 Ignored Mar 2nd Garden State 2025
152 Rhode Island Win 11-6 1815.12 Mar 2nd Garden State 2025
133 Bates Win 10-9 1450.44 Mar 22nd PBR State Open
348 Bentley Win 12-6 1037.48 Mar 22nd PBR State Open
105 Boston University Loss 7-15 849.66 Mar 22nd PBR State Open
281 Worcester Polytechnic** Win 15-3 1363.99 Ignored Mar 22nd PBR State Open
162 Brandeis Win 9-5 1757.28 Mar 23rd PBR State Open
214 MIT Win 13-5 1620.68 Mar 23rd PBR State Open
375 Harvard-B** Win 13-2 867.44 Ignored Mar 29th New England Open 2025
294 Northeastern-C** Win 13-5 1328.13 Ignored Mar 29th New England Open 2025
215 Northeastern-B Win 13-7 1573.31 Mar 29th New England Open 2025
335 Connecticut-B** Win 13-2 1158.9 Ignored Mar 29th New England Open 2025
318 Massachusetts-Lowell** Win 13-5 1212.25 Ignored Mar 30th New England Open 2025
281 Worcester Polytechnic** Win 15-6 1363.99 Ignored Mar 30th New England Open 2025
162 Brandeis Win 15-7 1828.22 Mar 30th New England Open 2025
406 Dartmouth-B** Win 15-2 554.74 Ignored Apr 12th North New England D III Mens Conferences 2025
70 Dartmouth Win 12-10 1856.63 Apr 12th North New England D III Mens Conferences 2025
36 Middlebury Loss 4-15 1218.97 Apr 12th North New England D III 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)