#38 MIT (12-10)

avg: 1588.82  •  sd: 49.9  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
57 James Madison Win 8-7 1531.04 Feb 22nd 2025 Commonwealth Cup Weekend 2
72 Purdue Win 9-8 1385.94 Feb 22nd 2025 Commonwealth Cup Weekend 2
109 Temple Win 11-3 1621.69 Feb 22nd 2025 Commonwealth Cup Weekend 2
62 Brown Win 9-8 1476.28 Feb 23rd 2025 Commonwealth Cup Weekend 2
34 Cornell Loss 7-11 1174.53 Feb 23rd 2025 Commonwealth Cup Weekend 2
33 Georgia Tech Loss 8-9 1526.61 Feb 23rd 2025 Commonwealth Cup Weekend 2
45 American Win 12-7 2062.92 Mar 29th East Coast Invite 2025
70 Carnegie Mellon Win 11-9 1528.35 Mar 29th East Coast Invite 2025
42 Duke Loss 8-9 1440.5 Mar 29th East Coast Invite 2025
74 Penn State Win 10-6 1755.89 Mar 29th East Coast Invite 2025
42 Duke Loss 4-5 1440.5 Mar 30th East Coast Invite 2025
3 Tufts Loss 9-15 1973.28 Mar 30th East Coast Invite 2025
35 Wisconsin Loss 6-8 1333.31 Mar 30th East Coast Invite 2025
150 Boston College** Win 15-1 1293.33 Ignored Apr 13th Metro Boston D I Womens Conferences 2025
129 Harvard** Win 11-2 1433.28 Ignored Apr 13th Metro Boston D I Womens Conferences 2025
25 Northeastern Loss 6-12 1223.22 Apr 13th Metro Boston D I Womens Conferences 2025
25 Northeastern Loss 9-10 1677.53 Apr 13th Metro Boston D I Womens Conferences 2025
62 Brown Win 11-6 1897.97 Apr 26th New England D I College Womens Regionals 2025
119 Brown-B** Win 12-4 1537.46 Ignored Apr 26th New England D I College Womens Regionals 2025
3 Tufts** Loss 4-15 1888.77 Ignored Apr 26th New England D I College Womens Regionals 2025
93 Rhode Island Win 14-7 1684.95 Apr 27th New England D I College Womens Regionals 2025
25 Northeastern Loss 6-8 1502.04 Apr 27th New England D I College Womens Regionals 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)