#281 Worcester Polytechnic (8-10)

avg: 763.99  •  sd: 68.73  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
95 Bowdoin** Loss 3-15 880.17 Ignored Mar 22nd PBR State Open
162 Brandeis Loss 2-15 628.22 Mar 22nd PBR State Open
214 MIT Loss 7-13 463.14 Mar 22nd PBR State Open
133 Bates Loss 4-13 725.44 Mar 23rd PBR State Open
348 Bentley Win 12-4 1058.17 Mar 23rd PBR State Open
105 Boston University** Loss 6-15 849.66 Ignored Mar 23rd PBR State Open
312 Amherst Win 9-8 753.94 Mar 29th New England Open 2025
162 Brandeis Loss 5-13 628.22 Mar 29th New England Open 2025
382 Wentworth Win 13-4 839.82 Mar 29th New England Open 2025
362 Western New England Win 9-8 494 Mar 29th New England Open 2025
95 Bowdoin** Loss 6-15 880.17 Ignored Mar 30th New England Open 2025
363 Clark Loss 9-11 119.38 Mar 30th New England Open 2025
215 Northeastern-B Loss 6-15 415.78 Mar 30th New England Open 2025
294 Northeastern-C Win 14-5 1328.13 Mar 30th New England Open 2025
306 Bryant Win 13-4 1266.18 Apr 19th South New England D III Mens Conferences 2025
369 Holy Cross Win 13-2 938.67 Apr 19th South New England D III Mens Conferences 2025
287 Roger Williams Win 11-10 873.81 Apr 19th South New England D III Mens Conferences 2025
76 Williams** Loss 6-15 992.52 Ignored Apr 20th South New England D III 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)