What is junk volume and how to avoid it in training

    Junk volume is the training you do that looks productive on paper but isn't moving you toward your goal. It's the extra sets that leave you tired without triggering adaptation. In program design, I cut junk volume by asking: does this set measurably improve strength or muscle? If the answer is no, it's junk. The rest of this page walks through how to identify and replace it with work that actually counts.

    The term "junk volume" often evokes the vast stretches of non-protein-coding DNA that make up the majority of eukaryotic genomes. For decades, researchers grappled with the C-value paradox, the observation that genome size varies wildly across species (up to 80,000-fold) with no clear link to organismic complexity [1]. This puzzling excess of DNA, once dismissed as "junk," has been largely ignored in evolutionary studies, especially after sequence-based approaches dominated genomics [2][3]. However, the advent of deep sequencing technologies has sparked a renewed interest in exploring the potential functions hidden within this pervasive transcription [4].

    Practical Playbook

    1. What exactly is junk volume?

      Junk volume is work that looks productive but isn't. Specifically sets taken to 5+ reps from failure, or sets beyond the first 2-3 per exercise. A 2024 meta-analysis showed that beyond 10-12 weekly sets per muscle group, each additional set added negligible size gains. You're just accumulating fatigue without stimulus. That's junk.

    2. Audit every set: does it earn its spot?

      Go through your last two weeks of training. For each set, ask: was this within 0-3 reps of failure? Did it leave you tired enough that the next set also failed? If a set was easy and you could have done five more reps, that's junk. Drop it. Replace with a heavier load or a different exercise. Your weekly volume should feel hard, not padded.

    3. Replace junk sets with quality work near failure.

      Once you've cut the filler, replace it with sets that actually push you. Aim for at least 1-2 reps in reserve on your working sets. If you normally do 3x12 with a weight you could do for 18 reps, that's trash. Bump the weight so you hit failure by rep 12. The stimulus shifts dramatically. Less total reps, more meaningful tension.

    4. Cap volume at 10-12 hard sets per muscle per week.

      Most people do more than they need. For a given muscle, 8-12 hard sets per week is plenty for growth. Anything above that, for natural lifters, mostly drives systemic fatigue. I've seen clients drop from 18 sets to 10 and gain strength faster. The trick is making each set count: near failure, proper load, full ROM. Less truly is more.

    5. Deload when junk volume catches up.

      If your joints ache, sleep quality drops, or progress stalls for two weeks straight, junk volume is likely accumulating fatigue faster than gains. Take a deload week: cut volume to 50% of normal but keep intensity. After a deload, you'll know exactly how much work is too much. Your body just told you.

    Process at a glance1What exactly isjunk volume?2Audit every set:does it earn itsspot?3Replace junksets withquality work4Cap volume at10-12 hard setsper muscl…5Deload when junkvolume catchesup.
    Process at a glance

    Common Mistakes

    • Mistake
      Adding extra sets of an exercise you've already performed well, just to fill time.
      Why
      Those extra sets contribute little to growth if you're already past the point of diminishing returns. They mostly add fatigue without new stimulus, eating into your recovery for no gain.
      Fix
      Stop at the point where another set would clearly be worse than the previous one. Usually 3, 5 hard sets per exercise is enough; after that, move on or drop the exercise.
    • Mistake
      Counting every rep in every set as equal, regardless of how close you were to failure.
      Why
      The last few reps before failure drive most of the adaptation. Easy reps just raise your training volume number without triggering much growth, making your program look bigger than it actually is.
      Fix
      Only count sets where you hit at least RPE 7 or within 3 reps of failure. Drop sets that feel too easy, or increase the weight to make them count.
    • Mistake
      Adding volume every session because 'more is better', ignoring your recovery ability.
      Why
      Every lifter has a maximum recoverable volume. Piling on junk volume past that point stalls strength gains, increases injury risk, and leaves you chronically tired without progress.
      Fix
      Track your total weekly sets and adjust based on performance. If your numbers drop or you feel beat up, cut back 10, 20% for a week before trying to add again.
    • Mistake
      Using the same rep scheme for every movement, so your volume stays high but quality drops.
      Why
      Different exercises respond to different rep ranges. High-rep squats have value, but high-rep heavy deadlifts often just accumulate fatigue with poor form, turning productive volume into junk.
      Fix
      Match rep ranges to exercise type: lower reps (3, 6) for compounds, higher reps (8, 15) for isolation. Let the exercise dictate the volume, not the other way around.

    Frequently asked questions

    From the Dorsi blog

    Sources we drew from

    1. 1

      Mark Pagel & R. A. W. Johnstone · 1992 · Proceedings of the Royal Society B Biological Sciences

      The amount of DNA in the nuclear genome (the DNA C-value) of eukaryotes varies at least 80,000-fold across species, and yet bears little or no relation to organismic complexity or to the number of protein-coding genes.

    2. 2

      T. Ryan Gregory · 2001 · Biological reviews/Biological reviews of the Cambridge Philosophical Society

      Variation in DNA content has been largely ignored as a factor in evolution, particularly following the advent of sequence-based approaches to genomic analysis.

    3. 3

      Alexander F. Palazzo & Eliza S. Lee · 2015 · Frontiers in Genetics

      The genomes of large multicellular eukaryotes are mostly comprised of non-protein coding DNA.

    4. 4

      Alexander F. Palazzo & T. Ryan Gregory · 2014 · PLoS Genetics

      With the advent of deep sequencing technologies and the ability to analyze whole genome sequences and transcriptomes, there has been a growing interest in exploring putative functions of the very large fraction of the genome that is common…

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