#316 Massachusetts-Lowell (7-11)

avg: 619.5  •  sd: 95.04  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
322 Central Connecticut State Win 7-6 720.07 Mar 1st Garden State 2025
337 Pennsylvania Western Win 6-3 1097.8 Mar 1st Garden State 2025
277 Salisbury Loss 6-9 350.95 Mar 1st Garden State 2025
311 Swarthmore Loss 6-11 86.02 Mar 1st Garden State 2025
337 Pennsylvania Western Win 15-1 1151.1 Mar 2nd Garden State 2025
389 Stevens Tech Loss 5-9 -343.04 Mar 2nd Garden State 2025
329 Connecticut-B Win 10-7 964.67 Mar 29th New England Open 2025
374 Harvard-B Win 8-4 852.01 Mar 29th New England Open 2025
185 Northeastern-B Loss 3-13 516.27 Mar 29th New England Open 2025
284 Northeastern-C Loss 8-9 632.13 Mar 29th New England Open 2025
90 Bowdoin** Loss 5-13 878.93 Ignored Mar 30th New England Open 2025
351 Clark Win 13-12 546.7 Mar 30th New England Open 2025
370 Wentworth Win 15-7 909.43 Mar 30th New England Open 2025
84 Boston College** Loss 3-14 907.56 Ignored Apr 12th Metro Boston D I Mens Conferences 2025
229 Harvard Loss 7-10 549.37 Apr 12th Metro Boston D I Mens Conferences 2025
20 Tufts** Loss 4-15 1395.17 Ignored Apr 12th Metro Boston D I Mens Conferences 2025
116 Boston University Loss 8-15 798.81 Apr 13th Metro Boston D I Mens Conferences 2025
222 MIT Loss 7-15 376.13 Apr 13th Metro Boston D I 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)