#27 LSU (17-11)

avg: 1777.74  •  sd: 51.59  •  top 16/20: 3.9%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
36 Alabama Win 11-10 1848.14 Jan 26th T Town Throwdown
72 Alabama-Huntsville Win 13-5 2083.99 Jan 26th T Town Throwdown
132 Kentucky Win 10-7 1640.82 Jan 26th T Town Throwdown
37 Illinois Win 13-9 2138.96 Jan 26th T Town Throwdown
48 Kennesaw State Win 15-14 1771.49 Jan 27th T Town Throwdown
24 Auburn Win 11-10 1921.78 Jan 27th T Town Throwdown
160 Vanderbilt** Win 15-4 1724.38 Ignored Jan 27th T Town Throwdown
6 Brigham Young Loss 9-13 1716.17 Feb 8th Florida Warm Up 2019
28 Northeastern Loss 8-9 1650.83 Feb 8th Florida Warm Up 2019
43 Harvard Loss 10-11 1547.28 Feb 8th Florida Warm Up 2019
25 South Carolina Win 15-10 2240.29 Feb 9th Florida Warm Up 2019
12 Texas Loss 7-10 1620.24 Feb 9th Florida Warm Up 2019
13 Wisconsin Win 11-8 2366.58 Feb 9th Florida Warm Up 2019
22 Georgia Loss 8-11 1468.88 Feb 9th Florida Warm Up 2019
43 Harvard Win 15-10 2125.88 Feb 10th Florida Warm Up 2019
20 Tufts Win 12-11 1989.15 Feb 10th Florida Warm Up 2019
36 Alabama Loss 10-13 1394.99 Mar 2nd Mardi Gras XXXII
65 Florida Win 13-10 1863.89 Mar 2nd Mardi Gras XXXII
227 Florida State-B Win 13-6 1515.33 Mar 2nd Mardi Gras XXXII
82 Texas State Loss 11-13 1213.81 Mar 2nd Mardi Gras XXXII
159 Mississippi State** Win 13-2 1725.81 Ignored Mar 3rd Mardi Gras XXXII
103 Georgia State Loss 10-11 1223.38 Mar 3rd Mardi Gras XXXII
19 Colorado State Win 12-11 2024.55 Mar 16th Centex 2019 Men
8 Colorado Loss 8-13 1599.28 Mar 16th Centex 2019 Men
29 Texas-Dallas Win 11-10 1896.91 Mar 16th Centex 2019 Men
67 Oklahoma State Win 15-11 1915.13 Mar 17th Centex 2019 Men
13 Wisconsin Loss 13-15 1786.79 Mar 17th Centex 2019 Men
12 Texas Loss 12-13 1884.9 Mar 17th Centex 2019 Men
**Blowout Eligible

FAQ

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
  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
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)