#107 Tennessee (5-13)

avg: 1341.72  •  sd: 63.21  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
49 Notre Dame Loss 8-15 1078.45 Feb 11th Queen City Tune Up1
30 Ohio State Loss 6-14 1235.97 Feb 11th Queen City Tune Up1
51 Virginia Loss 8-13 1139.3 Feb 11th Queen City Tune Up1
41 William & Mary Loss 10-14 1320.18 Feb 11th Queen City Tune Up1
134 Carnegie Mellon Loss 7-10 846.65 Feb 12th Queen City Tune Up1
62 Harvard Loss 7-10 1179.24 Feb 12th Queen City Tune Up1
3 Massachusetts** Loss 4-13 1711.41 Ignored Mar 4th Smoky Mountain Invite
4 Texas Loss 9-13 1796.19 Mar 4th Smoky Mountain Invite
20 North Carolina State Loss 7-13 1387.87 Mar 4th Smoky Mountain Invite
8 Pittsburgh Loss 6-13 1555.18 Mar 4th Smoky Mountain Invite
11 Brown Loss 7-15 1474.72 Mar 5th Smoky Mountain Invite
72 Auburn Win 14-13 1622.8 Mar 5th Smoky Mountain Invite
19 Georgia** Loss 6-15 1350.85 Ignored Mar 5th Smoky Mountain Invite
182 Berry Win 11-8 1379.49 Mar 25th Needle in a Ho Stack2
270 Wake Forest Win 13-6 1248.04 Mar 25th Needle in a Ho Stack2
133 Davidson Win 13-9 1656.73 Mar 25th Needle in a Ho Stack2
211 Embry-Riddle Win 13-1 1494.43 Mar 25th Needle in a Ho Stack2
102 Kennesaw State Loss 6-11 811.74 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)