#117 Vanderbilt (5-12)

avg: 1179.97  •  sd: 62.06  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
57 Auburn Loss 9-11 1197.99 Feb 10th Golden Triangle Invitational
192 Harding Loss 9-11 601.9 Feb 10th Golden Triangle Invitational
40 Illinois Loss 7-11 1112.79 Feb 10th Golden Triangle Invitational
87 Tennessee-Chattanooga Loss 9-13 891.41 Feb 10th Golden Triangle Invitational
222 Mississippi State -B Win 13-6 1336.33 Feb 11th Golden Triangle Invitational
54 California-Santa Barbara Loss 5-12 869.64 Mar 2nd Stanford Invite 2024
35 California-Santa Cruz Loss 7-12 1116.7 Mar 2nd Stanford Invite 2024
160 Santa Clara Win 11-9 1242.24 Mar 2nd Stanford Invite 2024
63 Western Washington Win 9-8 1547.23 Mar 2nd Stanford Invite 2024
40 Illinois Loss 9-10 1454.68 Mar 3rd Stanford Invite 2024
6 Oregon** Loss 2-13 1509.26 Ignored Mar 3rd Stanford Invite 2024
65 Stanford Loss 8-11 1039.33 Mar 3rd Stanford Invite 2024
128 Colorado College Loss 6-7 1011 Mar 30th Huck Finn 2024
83 Northwestern Loss 8-9 1210.48 Mar 30th Huck Finn 2024
108 Wisconsin-Milwaukee Loss 8-9 1074.7 Mar 30th Huck Finn 2024
132 Arkansas Win 10-7 1501.52 Mar 31st Huck Finn 2024
82 Central Florida Win 9-8 1462.27 Mar 31st Huck Finn 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)