See which training days and exercises carry the largest share of your entered demand without pretending the result is a physiological fatigue measurement.
| Exercise | Day | Working sets | Effort 1–5 | Overlap demand 1–3 |
|---|
Two weekly programs can contain the same number of working sets while placing very different amounts of demanding work into individual sessions. Heavy sets, high-effort sets and exercises that overlap strongly with other work can make a day feel more concentrated than a simple set count suggests. This analyzer gives that concentration a visible planning score.
Each entered exercise receives a transparent score: working sets × effort rating × overlap-demand rating. Higher effort and higher overlap demand increase the score. The formula is intentionally simple enough to audit and change; it should not be confused with a validated physiological fatigue equation.
The output ranks training days by total demand points and shows each day's share of the entered demand. It also counts high-effort sets using your chosen threshold. This helps you spot weeks in which several demanding sessions are clustered together or one day carries a disproportionate amount of the entered workload.
Exercises can impose different demands on related regions or movement patterns. A hinge, row and another pulling movement may be entered with different overlap values depending on how you want to model the session. Because the input is subjective, the tool keeps the overlap score visible rather than presenting it as a hidden fact.
Use the report as a conversation starter with your program. If one day contains a large share of demand points, you might inspect exercise order, set counts, rest periods or the placement of another hard session. The tool does not automatically tell you to remove work.
A four-day plan could have similar weekly sets on all days yet produce one very dense day because several high-effort, high-overlap exercises are grouped together. The analyzer will show that concentration. Whether it is desirable depends on your goals, schedule and actual response.
Fatigue is not a single quantity that can be read directly from exercise names and a few ratings. Sleep, nutrition, stress, training history, execution and many other factors matter. Treat demand points as a bookkeeping model for program structure, not a health or recovery diagnosis.
Look at the day share first, then inspect the exercises contributing to that day. If one session contains a large fraction of the entered demand, check whether that is deliberate. You can then compare its position with other demanding sessions and examine whether exercise order or set distribution should be reconsidered. Because the score multiplies three user-entered inputs, changing any one assumption changes the result. Record those assumptions when comparing versions of the program. That makes the analyzer more useful as a repeatable audit and less likely to be mistaken for a direct measurement of fatigue.
A useful weekly audit compares the proportion of demand points assigned to each day rather than focusing only on the single largest exercise. If one day dominates, inspect the next-highest day as well. Two high-demand sessions separated by an easy day can create a different schedule from two high-demand days placed consecutively, even if the weekly total is identical. The analyzer does not solve that spacing problem automatically, but it gives you the day-level information needed to ask it.
Data-quality check: decide what “effort 5” and each overlap value mean before entering multiple sessions. Consistent scales make repeated audits more useful.
The demand table becomes more informative when you compare adjacent training days. A high score on one day may be unimportant if the neighboring sessions are deliberately easier; the same score may deserve attention if another demanding session sits immediately beside it. The analyzer does not infer that relationship automatically, so use the day-level distribution as the starting point for the next scheduling review.
When comparing versions of a program, keep the scoring scale constant. Otherwise, a change in demand points may simply reflect that effort or overlap ratings were entered differently. Consistent inputs make the output useful for longitudinal program audits.
If you repeat this analysis for several weeks, use the same 1–5 effort scale and overlap definitions each time. Consistency is what makes the trend meaningful as a bookkeeping measure. A change in score can then be traced to a changed set count, effort rating or overlap assumption rather than a changing scoring system.
No. They are a transparent planning score using the inputs you provide.
Because the tool is designed to surface concentration of demanding work, and effort is one of the user-defined components.
Yes, when their effort or overlap-demand ratings differ.
Not automatically. The tool identifies concentration; your goals and program context determine whether it matters.
It lets you define which effort ratings count toward the high-effort set count in the report.
No. It describes program structure and does not measure your physiological recovery state.