Targeted Intervention
Programming is never a perfect science. However, we must seek to understand the basics of scientific experimentation to better serve our athletes and improve our programming skills. Here are the variables of a basic scientific experiment. Think of an experiment as a cause-and-effect proposition.
1) Dependent Variable: The effect. What we are attempting to measure? In the case of programming, the adaptation we are seeking.
2) Independent Variable: The cause. The independent variable is what we are attempting to manipulate to test the effect of the dependent variable. In programming these are what we call the acute programming variables (APV’s): exercise, exercise order, number of sets, intensity, rest, and tempo.
Targeted Intervention
Great scientists/programmers attempt to manipulate as few independent variables as possible. Why may you ask? If we change too many at once, it’s too difficult to decipher what worked and what didn’t. What was the cause? Here is a real-world example. Athlete #1 and Athlete #2 play for the same hockey club. How would you alter their programming? Here are the questions I ask:
How can I maintain the same program within the group while individualizing needs?
How can I manipulate the fewest APV’s to seek the desired adaptation I’m looking for?
Ideas for Action:
Athlete #1 Targeted Intervention: Add two additional working sets to each foundational lift. Measure performance after micro-cycle.
Athlete #2 Targeted Intervention: Eliminate high impulse jumps. Add stretch-shortening plyometrics. Add two additional reps of 10 meter sprints. Measure performance after micro-cycle.
What if the intervention doesn’t work? That’s ok. Many times, it may not. However, the underlying reasoning doesn’t change. Seek to alter minimally, measure, then manage.
Here is a video explaining the science of program design called: A Scientists Guide to Program Design. Targeted intervention is not synonymous with a programming face lift. To the contrary a minimalist approach is necessary.
