#36 Alabama (16-10)

avg: 1723.14  •  sd: 54.87  •  top 16/20: 0.4%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
24 Auburn Loss 8-9 1671.78 Jan 26th T Town Throwdown
48 Kennesaw State Win 10-8 1909.15 Jan 26th T Town Throwdown
106 Illinois State Win 13-8 1823.5 Jan 26th T Town Throwdown
27 LSU Loss 10-11 1652.74 Jan 26th T Town Throwdown
48 Kennesaw State Loss 12-14 1425.53 Jan 27th T Town Throwdown
160 Vanderbilt Win 14-8 1660.41 Jan 27th T Town Throwdown
72 Alabama-Huntsville Win 15-10 1937.59 Jan 27th T Town Throwdown
52 Notre Dame Win 9-7 1906.01 Feb 9th Queen City Tune Up 2019 Men
108 North Carolina-Charlotte Win 12-7 1845.58 Feb 9th Queen City Tune Up 2019 Men
57 Carnegie Mellon Win 10-6 2083.54 Feb 9th Queen City Tune Up 2019 Men
11 North Carolina State Loss 7-11 1560.68 Feb 9th Queen City Tune Up 2019 Men
1 North Carolina Loss 7-15 1631.92 Feb 10th Queen City Tune Up 2019 Men
47 Maryland Win 15-12 1956.82 Feb 10th Queen City Tune Up 2019 Men
14 Ohio State Loss 11-13 1763.22 Feb 10th Queen City Tune Up 2019 Men
322 Mississippi** Win 13-2 1187.21 Ignored Mar 2nd Mardi Gras XXXII
112 Wisconsin-Whitewater Win 13-6 1906.21 Mar 2nd Mardi Gras XXXII
23 Texas Tech Win 13-8 2327.29 Mar 2nd Mardi Gras XXXII
27 LSU Win 13-10 2105.88 Mar 2nd Mardi Gras XXXII
185 Alabama-Birmingham** Win 13-4 1631.96 Ignored Mar 3rd Mardi Gras XXXII
82 Texas State Win 12-8 1883.8 Mar 3rd Mardi Gras XXXII
159 Mississippi State Win 13-5 1725.81 Mar 16th Tally Classic XIV
68 Cincinnati Loss 10-13 1187.23 Mar 16th Tally Classic XIV
61 Tennessee Win 12-10 1792.31 Mar 16th Tally Classic XIV
15 Central Florida Loss 10-15 1536.71 Mar 16th Tally Classic XIV
79 Tulane Loss 10-12 1218.3 Mar 17th Tally Classic XIV
43 Harvard Loss 9-14 1198.41 Mar 17th Tally Classic XIV
**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)