#68 Lehigh (12-6)

avg: 1367.26  •  sd: 66.89  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
151 Johns Hopkins Win 15-9 1473.08 Feb 18th Blue Hen Open
83 Delaware Win 14-13 1397.96 Feb 18th Blue Hen Open
74 Binghamton Loss 12-13 1193.61 Feb 18th Blue Hen Open
143 Virginia Commonwealth Win 15-11 1367.88 Feb 19th Blue Hen Open
65 Princeton Win 13-6 1974.33 Feb 19th Blue Hen Open
74 Binghamton Win 12-11 1443.61 Feb 19th Blue Hen Open
266 Maryland-Baltimore County** Win 13-1 1037.69 Ignored Mar 4th Oak Creek Challenge 2023
151 Johns Hopkins Win 13-8 1453.75 Mar 4th Oak Creek Challenge 2023
162 Rowan Win 13-5 1520.56 Mar 4th Oak Creek Challenge 2023
90 Virginia Tech Win 13-8 1741.91 Mar 5th Oak Creek Challenge 2023
149 Towson Win 13-8 1458.48 Mar 5th Oak Creek Challenge 2023
166 Yale Win 13-4 1496.92 Mar 5th Oak Creek Challenge 2023
34 McGill Loss 10-13 1294.56 Mar 25th Carousel City Classic
119 Rochester Win 12-4 1690.53 Mar 25th Carousel City Classic
61 Harvard Loss 9-15 872.97 Mar 25th Carousel City Classic
23 Ottawa Loss 5-15 1107.65 Mar 26th Carousel City Classic
74 Binghamton Loss 11-12 1193.61 Mar 26th Carousel City Classic
61 Harvard Loss 6-11 841.76 Mar 26th Carousel City Classic
**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)