#96 Berry (13-2)

avg: 913.54  •  sd: 94.77  •  top 16/20: 0%

Click on a column to sort  • 
# Opponent Result Game Rating Status Date Event
91 Alabama Win 13-12 1072.88 Jan 25th T Town Throwdown XX
168 Illinois State Win 13-7 719.2 Jan 25th T Town Throwdown XX
190 Tennessee-Chattanooga -B** Win 13-1 39.61 Ignored Jan 25th T Town Throwdown XX
139 LSU Win 13-9 953 Jan 25th T Town Throwdown XX
91 Alabama Win 15-12 1248.38 Jan 26th T Town Throwdown XX
184 Harding** Win 13-2 457.76 Ignored Jan 26th T Town Throwdown XX
137 Union (Tennessee) Win 13-11 786.67 Jan 26th T Town Throwdown XX
139 LSU Win 15-8 1099.24 Jan 26th T Town Throwdown XX
179 Tennessee Tech Win 13-7 603.13 Feb 8th Bulldog Brawl
189 Mississippi State-B** Win 13-2 189.18 Ignored Feb 8th Bulldog Brawl
109 Missouri S&T Loss 11-13 592.13 Feb 8th Bulldog Brawl
144 Vanderbilt Win 13-9 893.44 Feb 8th Bulldog Brawl
105 Mississippi State Win 15-13 1055.59 Feb 9th Bulldog Brawl
93 Southern Illinois-Edwardsville Loss 14-15 811.21 Feb 9th Bulldog Brawl
104 Lipscomb Win 13-10 1171.08 Feb 9th Bulldog Brawl
**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)