Hi Dr. Ron

Which Base figure would you use?.

Here is what I do to some extent

Before selecting a Base figure the raw data needs to be massaged somewhat before we put it through its paces.
The first step is to eliminate Outliers from the data.(the following is a simple method or one could use Grubb's method of identifying outliers.).

Using excel and its inbuilt functions will assit

Step 1
using the function Quartile in excel
@sum((quartile 3) - (quartile 1)) * 1.5

Step 2
@sum((quartile 1 )+ answer from Step1

Any score/time that is outside of the the above needs to be deleted from the data
Now find the Mean and Stdev of the data this will become the Base figure.

With the help of the Base figure we need to develop a Performance envelope.
Each performance line of each runner needs to be assigned a Z score.Using these Z scores one needs to find the Max and Min Z scores for a range of typical Variables using the individual runners performance lines or if there is not enough data for a runner then you need to use the whole Database figures in preference to the individual runners Max/Min Z scores.

X*Y/sqrt(Z)
X=Min Z score
Y=LTD Stdev
Z= number of starts for this variable or LTD number of Starts

Subtract this score from your Base figure this becomes your Lower Performance figure, now do the same but substitute the Min Z score with the Max and now you have the upper Performance figure.

Its important to find Max/Min Z scores from your database for a whole range of variables and then apply them when the data is thin and most should be Class specific.