Coach D and Trent discuss the basics of programming for the Masters athlete. Our programming philosophy is built upon the Stress-Recovery-Adaption cycle, originally outlined in Hans Selye’s General Adaptation Syndrome in 1936. When we talk about training, we think of individual workouts as stressors, and the time between workouts spent sleeping and eating as recovery. If the stressor is sufficient to disrupt homeostasis AND the recovery is sufficient between sessions, then an adaptation occurs. It’s easy to apply to strength training – the tonnage moved (weight x reps) is the stressor, the food and sleep in between the session is the recovery, and getting stronger is the outcome, the adaptation – but it applies to all aspects of physiology.
Thus, programming is the manipulation of the basic training variables to achieve a desired outcome over a period of time. We also subscribe to the Minimum Effective Dose principle. This principle is taken from medicine, and means that we use the absolute minimum amount of stress needed to drive adaptation. Hard is good. Hard is necessary, if the workout is going to provide a stress. But more is not better, and we want to make our workouts just hard enough to drive progress, and no more. We can’t forget about recovery — if a single workout is so taxing that it leaves us sore and “wrecked” for a week, then it prevented productive training during that week, and may have cost us whatever adaptation we gained from doing that workout (since we tend to detrain without engaging in the SRA cycle).
So, we aim to make our workouts just hard enough, and to change a single variable at a time. The basic variables are intensity (the weight on the bar in a strength program, or the target speed at which a row is performed in conditioning work) and volume (how many sets we perform). Other variables include exercise selection, which we rarely change in a strength program since the basic compound lifts drive the most strength gains, and frequency (how often you do an exercise in a week or training cycle). Importantly, when designing programming we only change one variable at a time, so that we know what works (or doesn’t). Changing multiple variables at once does not give us useful data regarding what is actually driving progress.
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