#16 Middlebury (12-0)

avg: 1836.02  •  sd: 67.85  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
91 Colorado College** Win 13-5 1655.26 Ignored Mar 18th Womens Centex1
47 Florida Win 13-11 1696.97 Mar 18th Womens Centex1
75 Boston University Win 13-7 1778.81 Mar 18th Womens Centex1
87 Southern California** Win 13-5 1686.29 Ignored Mar 19th Womens Centex1
47 Florida Win 15-9 1983.61 Mar 19th Womens Centex1
45 Washington University Win 15-4 2079.52 Mar 19th Womens Centex1
23 Texas-Dallas Win 12-9 2085.04 Mar 19th Womens Centex1
116 Cedarville** Win 13-4 1490.83 Ignored Mar 25th Needle in a Ho Stack2
64 Appalachian State Win 13-4 1874.68 Mar 25th Needle in a Ho Stack2
- Berry** Win 13-3 1545.63 Ignored Mar 25th Needle in a Ho Stack2
77 Tennessee-Chattanooga** Win 13-1 1779.69 Ignored Mar 25th Needle in a Ho Stack2
73 St. Olaf Win 9-8 1352.23 Mar 26th Needle in a Ho Stack2
**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)