#142 Ithaca (8-8)

avg: 920.19  •  sd: 84.89  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
192 Connecticut College Win 6-4 916.66 Mar 2nd SouthHill Slam
244 Cornell-B** Win 9-0 317.22 Ignored Mar 2nd SouthHill Slam
239 SUNY-Albany** Win 9-0 584.99 Ignored Mar 2nd SouthHill Slam
192 Connecticut College Win 9-5 1080.11 Mar 3rd SouthHill Slam
244 Cornell-B** Win 13-1 317.22 Ignored Mar 3rd SouthHill Slam
122 Boston College Loss 7-8 950.76 Mar 24th King of New York 2024
94 Lehigh Loss 4-6 910.09 Mar 24th King of New York 2024
193 SUNY-Geneseo Loss 4-5 413.01 Mar 24th King of New York 2024
157 Hamilton Loss 6-7 712.7 Apr 20th Western NY D III Womens Conferences 2024
82 Rochester Loss 5-8 890.88 Apr 20th Western NY D III Womens Conferences 2024
193 SUNY-Geneseo Win 9-1 1138.01 Apr 20th Western NY D III Womens Conferences 2024
157 Hamilton Win 7-6 962.7 Apr 27th Metro East D III College Womens Regionals 2024
82 Rochester Loss 8-11 978.87 Apr 27th Metro East D III College Womens Regionals 2024
193 SUNY-Geneseo Win 15-1 1138.01 Apr 27th Metro East D III College Womens Regionals 2024
144 Skidmore Loss 7-8 787.28 Apr 28th Metro East D III College Womens Regionals 2024
81 Wesleyan Loss 5-8 899.71 Apr 28th Metro East D III College Womens 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)