#144 Skidmore (11-12)

avg: 912.28  •  sd: 73.8  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
82 Rochester Loss 3-9 744.48 Feb 24th Bring The Huckus 2024
168 Swarthmore Loss 1-5 177.22 Feb 24th Bring The Huckus 2024
220 Dickinson Loss 4-5 148.22 Feb 24th Bring The Huckus 2024
191 Syracuse Win 8-4 1117.35 Feb 24th Bring The Huckus 2024
108 West Chester Loss 3-9 579.47 Feb 25th Bring The Huckus 2024
191 Syracuse Win 8-4 1117.35 Feb 25th Bring The Huckus 2024
181 Vermont-C Win 9-3 1210.94 Mar 30th Northeast Classic 2024
150 RIT Loss 5-8 414.45 Mar 30th Northeast Classic 2024
180 SUNY-Buffalo Win 10-3 1220.02 Mar 30th Northeast Classic 2024
192 Connecticut College Win 8-4 1115.86 Mar 31st Northeast Classic 2024
68 Vermont-B Loss 6-8 1136.94 Mar 31st Northeast Classic 2024
111 NYU Loss 3-4 1016.12 Mar 31st Northeast Classic 2024
185 Bowdoin Win 7-1 1185.58 Mar 31st Northeast Classic 2024
95 McGill Loss 5-9 726.88 Mar 31st Northeast Classic 2024
215 Vassar Loss 7-8 190.55 Apr 14th Eastern Metro East D III Womens Conferences 2024
192 Connecticut College Win 10-5 1124.95 Apr 14th Eastern Metro East D III Womens Conferences 2024
228 Rensselaer Polytech** Win 13-3 781.36 Ignored Apr 14th Eastern Metro East D III Womens Conferences 2024
81 Wesleyan Loss 8-10 1090.65 Apr 14th Eastern Metro East D III Womens Conferences 2024
193 SUNY-Geneseo Win 9-3 1138.01 Apr 27th Metro East D III College Womens Regionals 2024
81 Wesleyan Loss 7-11 886.42 Apr 27th Metro East D III College Womens Regionals 2024
157 Hamilton Win 7-4 1333.86 Apr 27th Metro East D III College Womens Regionals 2024
82 Rochester Loss 5-14 744.48 Apr 28th Metro East D III College Womens Regionals 2024
142 Ithaca Win 8-7 1045.19 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)