#56 Tennessee (13-5)

avg: 1340.42  •  sd: 108.5  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
195 Georgia Tech-B** Win 11-2 756.73 Ignored Feb 11th 2023 TOTS The Only Tenn I See
179 LSU** Win 11-1 947.6 Ignored Feb 11th 2023 TOTS The Only Tenn I See
114 Union (Tennessee) Win 9-3 1499.39 Feb 11th 2023 TOTS The Only Tenn I See
206 Vanderbilt** Win 11-0 621.72 Ignored Feb 11th 2023 TOTS The Only Tenn I See
54 Georgia Tech Win 10-3 1952.86 Feb 12th 2023 TOTS The Only Tenn I See
77 Tennessee-Chattanooga Win 13-3 1779.39 Feb 12th 2023 TOTS The Only Tenn I See
30 South Carolina Loss 1-15 1060.8 Feb 25th Commonwealth Cup Weekend2 2023
65 Carnegie Mellon Loss 9-14 800.1 Feb 25th Commonwealth Cup Weekend2 2023
26 Notre Dame Loss 4-15 1088.33 Feb 25th Commonwealth Cup Weekend2 2023
47 Florida Loss 8-9 1342.9 Feb 26th Commonwealth Cup Weekend2 2023
129 Maryland Win 12-7 1296.7 Feb 26th Commonwealth Cup Weekend2 2023
95 Temple Loss 6-8 728.62 Feb 26th Commonwealth Cup Weekend2 2023
73 St. Olaf Win 13-6 1826.89 Mar 25th Needle in a Ho Stack2
94 Boston College Win 13-3 1638.5 Mar 25th Needle in a Ho Stack2
114 Union (Tennessee) Win 9-8 1024.39 Mar 25th Needle in a Ho Stack2
201 Wake Forest** Win 13-1 662.67 Ignored Mar 25th Needle in a Ho Stack2
64 Appalachian State Win 12-4 1874.41 Mar 26th Needle in a Ho Stack2
186 Richmond Win 13-6 861.23 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)