#70 Lehigh (16-8)

avg: 1526.73  •  sd: 61.3  •  top 16/20: 0%

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# Opponent Result Game Rating Status Date Event
168 Johns Hopkins Win 15-9 1602.06 Feb 18th Blue Hen Open
97 Delaware Win 14-13 1544 Feb 18th Blue Hen Open
82 Binghamton Loss 12-13 1336.54 Feb 18th Blue Hen Open
167 Virginia Commonwealth Win 15-11 1471.27 Feb 19th Blue Hen Open
76 Princeton Win 13-6 2083.27 Feb 19th Blue Hen Open
82 Binghamton Win 12-11 1586.54 Feb 19th Blue Hen Open
286 Maryland-Baltimore County** Win 13-1 1145.96 Ignored Mar 4th Oak Creek Challenge 2023
168 Johns Hopkins Win 13-8 1582.74 Mar 4th Oak Creek Challenge 2023
175 Rowan Win 13-5 1648.16 Mar 4th Oak Creek Challenge 2023
67 Virginia Tech Win 13-8 2049.45 Mar 5th Oak Creek Challenge 2023
124 Towson Win 13-8 1765.29 Mar 5th Oak Creek Challenge 2023
157 Yale Win 13-4 1725.16 Mar 5th Oak Creek Challenge 2023
37 McGill Loss 10-13 1445.23 Mar 25th Carousel City Classic
177 Rochester Win 12-4 1640.19 Mar 25th Carousel City Classic
62 Harvard Loss 9-15 1053.42 Mar 25th Carousel City Classic
31 Ottawa Loss 5-15 1229.69 Mar 26th Carousel City Classic
82 Binghamton Loss 11-12 1336.54 Mar 26th Carousel City Classic
62 Harvard Loss 6-11 1022.21 Mar 26th Carousel City Classic
167 Virginia Commonwealth Win 13-9 1508.67 Apr 1st Atlantic Coast Open 2023
147 Connecticut Win 13-5 1762.48 Apr 1st Atlantic Coast Open 2023
63 Rutgers Win 13-7 2126.32 Apr 1st Atlantic Coast Open 2023
106 Liberty Win 15-14 1467.91 Apr 2nd Atlantic Coast Open 2023
33 Duke Loss 8-15 1225.85 Apr 2nd Atlantic Coast Open 2023
45 Georgetown Loss 6-11 1150 Apr 2nd Atlantic Coast Open 2023
**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)