#87 Tennessee-Chattanooga (10-8)

avg: 1309.98  •  sd: 74.64  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
264 Jacksonville State** Win 11-3 1141.75 Ignored Feb 10th Golden Triangle Invitational
222 Mississippi State -B Win 11-3 1336.33 Feb 10th Golden Triangle Invitational
76 Purdue Loss 6-11 810.52 Feb 10th Golden Triangle Invitational
117 Vanderbilt Win 13-9 1598.54 Feb 10th Golden Triangle Invitational
50 Alabama Win 13-12 1626.57 Feb 11th Golden Triangle Invitational
40 Illinois Loss 11-13 1350.84 Feb 11th Golden Triangle Invitational
110 Arizona State Win 9-8 1317.59 Feb 24th Mardi Gras XXXVI college
105 Mississippi State Win 13-4 1810.79 Feb 24th Mardi Gras XXXVI college
333 LSU-B** Win 13-0 751.44 Ignored Feb 24th Mardi Gras XXXVI college
132 Arkansas Win 10-8 1374.52 Feb 25th Mardi Gras XXXVI college
91 Indiana Win 13-4 1870.81 Feb 25th Mardi Gras XXXVI college
44 Tulane Loss 9-11 1292.47 Feb 25th Mardi Gras XXXVI college
84 Appalachian State Loss 12-13 1201.8 Mar 30th Atlantic Coast Open 2024
144 Pittsburgh-B Win 13-10 1390.16 Mar 30th Atlantic Coast Open 2024
73 Richmond Loss 12-13 1239.26 Mar 30th Atlantic Coast Open 2024
61 William & Mary Loss 9-15 916.53 Mar 30th Atlantic Coast Open 2024
97 Florida State Loss 7-11 780.87 Mar 31st Atlantic Coast Open 2024
52 Virginia Tech Loss 13-14 1350.52 Mar 31st Atlantic Coast Open 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)