#215 Northeastern-B (15-6)

avg: 1015.78  •  sd: 61.13  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
133 Bates Loss 5-8 871.84 Mar 8th Grand Northeast Kickoff 2025
262 Brown-B Win 7-4 1325.16 Mar 8th Grand Northeast Kickoff 2025
399 Middlebury-B** Win 11-0 686 Ignored Mar 8th Grand Northeast Kickoff 2025
385 New Hampshire** Win 10-1 802.59 Ignored Mar 8th Grand Northeast Kickoff 2025
312 Amherst Win 8-4 1193.74 Mar 9th Grand Northeast Kickoff 2025
133 Bates Loss 10-15 871.84 Mar 9th Grand Northeast Kickoff 2025
223 Colby Win 8-7 1107.72 Mar 9th Grand Northeast Kickoff 2025
95 Bowdoin Loss 7-13 922.64 Mar 29th New England Open 2025
335 Connecticut-B Win 13-3 1158.9 Mar 29th New England Open 2025
375 Harvard-B** Win 13-2 867.44 Ignored Mar 29th New England Open 2025
318 Massachusetts-Lowell Win 13-3 1212.25 Mar 29th New England Open 2025
294 Northeastern-C Win 11-7 1195.03 Mar 29th New England Open 2025
312 Amherst Win 12-9 974.3 Mar 30th New England Open 2025
162 Brandeis Loss 7-15 628.22 Mar 30th New England Open 2025
281 Worcester Polytechnic Win 15-6 1363.99 Mar 30th New England Open 2025
411 Boston University-B** Win 12-3 389.91 Ignored Apr 12th New England Dev Mens Conferences 2025
262 Brown-B Win 10-7 1218.66 Apr 12th New England Dev Mens Conferences 2025
375 Harvard-B** Win 15-1 867.44 Ignored Apr 12th New England Dev Mens Conferences 2025
111 Vermont-B Loss 7-11 951.42 Apr 12th New England Dev Mens Conferences 2025
262 Brown-B Win 11-9 1078.2 Apr 13th New England Dev Mens Conferences 2025
294 Northeastern-C Loss 7-10 338.47 Apr 13th New England Dev 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)