#389 Stevens Tech (7-13)

avg: 186.02  •  sd: 83.37  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
355 Army Loss 2-15 -186.15 Mar 1st Garden State 2025
246 Connecticut College** Loss 5-15 285.45 Ignored Mar 1st Garden State 2025
359 Cornell-B Loss 3-15 -202.22 Mar 1st Garden State 2025
322 Central Connecticut State Loss 2-8 -4.93 Mar 2nd Garden State 2025
316 Massachusetts-Lowell Win 9-5 1148.56 Mar 2nd Garden State 2025
311 Swarthmore Loss 7-11 165.82 Mar 2nd Garden State 2025
359 Cornell-B Loss 5-10 -176.12 Mar 29th Northeast Classic 2025
331 Hofstra Win 7-6 695.89 Mar 29th Northeast Classic 2025
211 Vermont-C** Loss 4-13 415.81 Ignored Mar 29th Northeast Classic 2025
418 SUNY-Albany-B** Win 13-2 98.08 Ignored Mar 29th Northeast Classic 2025
416 Siena Win 11-5 186.18 Mar 30th Northeast Classic 2025
380 SUNY-Binghamton-B Loss 6-10 -251.11 Mar 30th Northeast Classic 2025
384 West Chester-B Win 12-9 569.91 Mar 30th Northeast Classic 2025
243 College of New Jersey** Loss 4-15 293.37 Ignored Apr 13th Metro NY D III Mens Conferences 2025
- Manhattan Win 13-9 186.18 Apr 13th Metro NY D III Mens Conferences 2025
243 College of New Jersey** Loss 2-12 293.37 Ignored Apr 26th Metro East D III College Mens Regionals 2025
176 Hamilton** Loss 5-13 557.41 Ignored Apr 26th Metro East D III College Mens Regionals 2025
81 Rochester** Loss 1-13 938.5 Ignored Apr 26th Metro East D III College Mens Regionals 2025
267 SUNY-Geneseo** Loss 1-13 199.71 Ignored Apr 26th Metro East D III College Mens Regionals 2025
415 New Haven Win 9-5 186.16 Apr 27th Metro East D III College Mens 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)