Originally Posted by Justin McCallon
So, basically, you're giving everybody a score based on the top performer, but you're accounting for standard deviation.
For my own records and playing around I was doing:
#1. Get all the numbers/times and figure out whether a high score is good (i.e. Deadlifts) or Bad (i.e. 5k run)
#2. Find the Mean (ie. average) of these scores
#3. Find the Standard Deviation of these scores
#4. Create a new data set of standardized scores (ie. z-scores) by subtracting the mean from each score and dividing by the standard deviation. Ie
z = (original score - mean) / stddev
#5. Now work with the columns of z scores. If the z score is negative when a positive score is good, make it 0. If the z score is positive when a negative score is good, make it 0. Ie. delete the ones that are already below average scores.
#6. Create a Final Score column, which is the sum of the absolute value of the z-score columns. The one with the largest score wins.