#141 Boston University (8-14)

avg: 1342.31  •  sd: 55.96  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
226 American Win 11-8 1398.73 Jan 27th Mid Atlantic Warm Up
70 James Madison Loss 7-11 1166.3 Jan 27th Mid Atlantic Warm Up
65 Richmond Win 9-8 1799.99 Jan 27th Mid Atlantic Warm Up
148 Johns Hopkins Win 9-8 1440.12 Jan 27th Mid Atlantic Warm Up
103 SUNY-Binghamton Win 11-8 1857.25 Jan 28th Mid Atlantic Warm Up
79 Case Western Reserve Loss 5-13 995.69 Jan 28th Mid Atlantic Warm Up
59 William & Mary Loss 6-13 1127.3 Jan 28th Mid Atlantic Warm Up
120 Syracuse Loss 8-10 1140.6 Mar 2nd No Sleep till Brooklyn 2024
102 Connecticut Loss 8-10 1232.46 Mar 2nd No Sleep till Brooklyn 2024
93 Princeton Loss 8-9 1413.03 Mar 2nd No Sleep till Brooklyn 2024
191 NYU Win 13-2 1756.8 Mar 3rd No Sleep till Brooklyn 2024
120 Syracuse Loss 8-13 907.1 Mar 3rd No Sleep till Brooklyn 2024
25 Middlebury** Loss 3-13 1404.07 Ignored Mar 3rd No Sleep till Brooklyn 2024
18 Northeastern Loss 8-15 1543.24 Apr 13th Metro Boston D I Mens Conferences 2024
152 Harvard Loss 9-10 1186.24 Apr 13th Metro Boston D I Mens Conferences 2024
112 Boston College Loss 12-13 1330.9 Apr 14th Metro Boston D I Mens Conferences 2024
297 Massachusetts-Lowell** Win 15-4 1329.5 Ignored Apr 14th Metro Boston D I Mens Conferences 2024
201 MIT Win 15-3 1716.71 Apr 14th Metro Boston D I Mens Conferences 2024
112 Boston College Loss 11-13 1227.06 May 4th New England D I College Mens Regionals 2024
9 Vermont** Loss 4-13 1647.89 Ignored May 4th New England D I College Mens Regionals 2024
159 Rhode Island Loss 9-11 1038.94 May 4th New England D I College Mens Regionals 2024
210 Northeastern-B Win 13-10 1408.8 May 5th New England D I College Mens Regionals 2024
**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)