#66 Tennessee (11-6)

avg: 1434.85  •  sd: 80.09  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
191 Elon** Win 13-0 947.39 Ignored Feb 17th Commonwealth Cup Weekend 1 2024
151 George Washington Win 13-6 1391.23 Feb 17th Commonwealth Cup Weekend 1 2024
181 Virginia-B** Win 13-2 1061.64 Ignored Feb 17th Commonwealth Cup Weekend 1 2024
53 American Loss 6-10 1088.64 Feb 18th Commonwealth Cup Weekend 1 2024
151 George Washington Win 6-3 1337.93 Feb 18th Commonwealth Cup Weekend 1 2024
100 Davenport Loss 7-9 914.63 Feb 18th Commonwealth Cup Weekend 1 2024
43 Alabama-Huntsville Loss 7-8 1575.69 Feb 24th The Only Tenn I See Memorial Tournament
174 Vanderbilt** Win 13-1 1126.74 Ignored Feb 24th The Only Tenn I See Memorial Tournament
147 Kentucky Win 13-1 1441.73 Feb 24th The Only Tenn I See Memorial Tournament
43 Alabama-Huntsville Win 14-10 2099.39 Feb 25th The Only Tenn I See Memorial Tournament
122 Illinois Win 14-3 1587.6 Feb 25th The Only Tenn I See Memorial Tournament
40 Union (Tennessee) Win 10-9 1843.54 Feb 25th The Only Tenn I See Memorial Tournament
128 Cedarville Win 13-7 1504.5 Mar 23rd Needle in a Ho Stack 2024
50 Davidson Loss 5-9 1084.87 Mar 23rd Needle in a Ho Stack 2024
43 Alabama-Huntsville Loss 4-13 1100.69 Mar 24th Needle in a Ho Stack 2024
97 Appalachian State Win 10-6 1716.5 Mar 24th Needle in a Ho Stack 2024
50 Davidson Loss 7-9 1334.59 Mar 24th Needle in a Ho Stack 2024
**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)