#375 Harvard-B (4-17)

avg: 267.44  •  sd: 63.5  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
230 Harvard** Loss 2-13 357.31 Ignored Mar 9th MIT Invite
214 MIT** Loss 1-13 420.68 Ignored Mar 9th MIT Invite
294 Northeastern-C Loss 5-7 399.99 Mar 9th MIT Invite
364 MIT-B Win 8-6 668.52 Mar 9th MIT Invite
333 Florida-B Loss 4-6 201.05 Mar 15th Tally Classic XIX
278 Jacksonville State Loss 2-11 178.21 Mar 15th Tally Classic XIX
372 Nova Southeastern Loss 8-9 173.19 Mar 15th Tally Classic XIX
397 South Florida-B Win 7-6 227.31 Mar 15th Tally Classic XIX
95 Bowdoin** Loss 2-13 880.17 Ignored Mar 29th New England Open 2025
294 Northeastern-C Loss 8-10 465.47 Mar 29th New England Open 2025
215 Northeastern-B** Loss 2-13 415.78 Ignored Mar 29th New England Open 2025
318 Massachusetts-Lowell Loss 4-8 47.44 Mar 29th New England Open 2025
335 Connecticut-B Loss 3-9 -41.1 Mar 30th New England Open 2025
382 Wentworth Loss 10-12 1.7 Mar 30th New England Open 2025
362 Western New England Win 7-0 969 Mar 30th New England Open 2025
411 Boston University-B Win 11-6 336.61 Apr 12th New England Dev Mens Conferences 2025
262 Brown-B Loss 4-11 229 Apr 12th New England Dev Mens Conferences 2025
215 Northeastern-B** Loss 1-15 415.78 Ignored Apr 12th New England Dev Mens Conferences 2025
111 Vermont-B** Loss 2-15 818.32 Ignored Apr 12th New England Dev Mens Conferences 2025
206 Tufts-B** Loss 4-12 442.31 Ignored Apr 13th New England Dev Mens Conferences 2025
364 MIT-B Loss 6-8 67.53 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)