#318 Swarthmore (5-16)

avg: 655.47  •  sd: 54.43  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
275 Central Connecticut State Loss 3-8 248.66 Feb 24th Bring The Huckus 2024
244 Dickinson Loss 6-7 854.09 Feb 24th Bring The Huckus 2024
331 Rutgers-B Win 6-5 721.28 Feb 24th Bring The Huckus 2024
327 SUNY-Binghamton-B Win 10-8 876.88 Feb 24th Bring The Huckus 2024
319 Edinboro Loss 10-11 529.16 Feb 25th Bring The Huckus 2024
245 Skidmore Loss 7-8 853.07 Feb 25th Bring The Huckus 2024
382 Lehigh-B Win 15-9 803.11 Feb 25th Bring The Huckus 2024
364 Rensselaer Polytech Win 13-8 928.4 Mar 30th Northeast Classic 2024
159 Rhode Island Loss 7-11 821.26 Mar 30th Northeast Classic 2024
327 SUNY-Binghamton-B Loss 8-9 489.21 Mar 30th Northeast Classic 2024
218 Middlebury-B Loss 5-11 454.71 Mar 31st Northeast Classic 2024
315 Vermont-C Loss 5-13 60.56 Mar 31st Northeast Classic 2024
234 Haverford Loss 3-9 399.52 Apr 13th East Penn D III Mens Conferences 2024
171 Scranton Loss 4-15 638.19 Apr 13th East Penn D III Mens Conferences 2024
382 Lehigh-B Win 11-6 834.32 Apr 13th East Penn D III Mens Conferences 2024
86 Cedarville** Loss 4-11 955.52 Ignored Apr 27th Ohio Valley D III College Mens Regionals 2024
123 Oberlin** Loss 1-8 796.72 Ignored Apr 27th Ohio Valley D III College Mens Regionals 2024
171 Scranton Loss 4-13 638.19 Apr 27th Ohio Valley D III College Mens Regionals 2024
173 Xavier Loss 10-11 1108.43 Apr 27th Ohio Valley D III College Mens Regionals 2024
174 Grove City Loss 6-12 645.68 Apr 28th Ohio Valley D III College Mens Regionals 2024
234 Haverford Loss 5-9 470.46 Apr 28th Ohio Valley D III College Mens Regionals 2024
**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)