#82 Binghamton (11-8)

avg: 1461.54  •  sd: 49.41  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
163 Boston University Win 9-8 1226.13 Jan 28th Mid Atlantic Warmup
56 James Madison Loss 7-9 1320.3 Jan 28th Mid Atlantic Warmup
83 RIT Loss 8-11 1084.75 Jan 28th Mid Atlantic Warmup
248 Drexel Win 10-8 1007.21 Jan 28th Mid Atlantic Warmup
56 James Madison Loss 10-14 1200.94 Jan 29th Mid Atlantic Warmup
83 RIT Win 13-11 1679.2 Jan 29th Mid Atlantic Warmup
167 Virginia Commonwealth Win 14-10 1488.81 Jan 29th Mid Atlantic Warmup
168 Johns Hopkins Win 15-9 1602.06 Feb 18th Blue Hen Open
70 Lehigh Win 13-12 1651.73 Feb 18th Blue Hen Open
97 Delaware Win 12-11 1544 Feb 18th Blue Hen Open
70 Lehigh Loss 11-12 1401.73 Feb 19th Blue Hen Open
97 Delaware Win 12-9 1764.37 Feb 19th Blue Hen Open
285 Villanova** Win 14-4 1149.69 Ignored Feb 19th Blue Hen Open
176 Syracuse Win 15-4 1647.79 Mar 25th Carousel City Classic
31 Ottawa Loss 8-12 1388.54 Mar 25th Carousel City Classic
63 Rutgers Loss 11-12 1443.79 Mar 25th Carousel City Classic
50 Case Western Reserve Loss 13-14 1515.01 Mar 26th Carousel City Classic
70 Lehigh Win 12-11 1651.73 Mar 26th Carousel City Classic
71 Cornell Loss 10-11 1378.6 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)