#233 Skidmore (8-5)

avg: 704.52  •  sd: 88.33  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
281 Edinboro Win 9-3 1050.84 Feb 24th Bring The Huckus 2024
187 Salisbury Loss 8-9 738.68 Feb 24th Bring The Huckus 2024
344 Lehigh-B** Win 13-3 686.14 Ignored Feb 24th Bring The Huckus 2024
277 Stevens Tech Loss 5-9 -31.61 Feb 24th Bring The Huckus 2024
219 Central Connecticut State Loss 6-15 155.54 Feb 25th Bring The Huckus 2024
321 SUNY-Binghamton-B Win 13-8 751.85 Feb 25th Bring The Huckus 2024
306 Swarthmore Win 8-7 449.08 Feb 25th Bring The Huckus 2024
282 Hofstra Win 10-8 712.13 Mar 30th Northeast Classic 2024
350 SUNY-Buffalo-B** Win 12-5 625.44 Ignored Mar 30th Northeast Classic 2024
213 SUNY-Albany Win 10-7 1155.81 Mar 30th Northeast Classic 2024
157 Ithaca Loss 7-9 737.27 Mar 31st Northeast Classic 2024
247 SUNY-Geneseo Win 9-8 762.5 Mar 31st Northeast Classic 2024
100 Vermont-B Loss 8-10 972.88 Mar 31st Northeast Classic 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)