#122 Boston University (11-7)

avg: 1167.78  •  sd: 76.93  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
78 Richmond Loss 8-13 851.87 Jan 25th Mid Atlantic Warm Up 2025
138 RIT Loss 7-11 626.02 Jan 25th Mid Atlantic Warm Up 2025
272 Virginia Commonwealth** Win 11-4 1111.33 Ignored Jan 25th Mid Atlantic Warm Up 2025
60 Michigan State Loss 5-12 886.35 Jan 25th Mid Atlantic Warm Up 2025
157 Johns Hopkins Win 15-4 1605.84 Jan 26th Mid Atlantic Warm Up 2025
184 East Carolina Win 13-10 1217.85 Jan 26th Mid Atlantic Warm Up 2025
179 Pennsylvania Win 15-4 1511.9 Jan 26th Mid Atlantic Warm Up 2025
170 Massachusetts -B Win 9-6 1378.42 Mar 1st UMass Invite 2025
108 Columbia Loss 7-10 829.53 Mar 1st UMass Invite 2025
126 Maine Loss 7-9 858.75 Mar 1st UMass Invite 2025
73 Williams Win 8-7 1510.1 Mar 1st UMass Invite 2025
68 Wesleyan Loss 8-11 1065.7 Mar 2nd UMass Invite 2025
334 Bentley** Win 15-3 794.03 Ignored Mar 22nd PBR State Open
218 MIT Win 12-6 1318.61 Mar 22nd PBR State Open
112 Bowdoin Win 15-7 1804.58 Mar 22nd PBR State Open
144 Bates Loss 7-9 780.22 Mar 23rd PBR State Open
290 Worcester Polytechnic** Win 15-6 1013.7 Ignored Mar 23rd PBR State Open
166 Brandeis Win 11-10 1097.11 Mar 23rd PBR State Open
**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)