FitEngineering

Muscle gain

Clean bulking: adding muscle without the fat

Muscle is built far more slowly than fat is stored, so a bulk is won or lost on the size of the surplus. Too small and nothing happens; too large and you spend six months gaining weight you will spend the next six months removing. The margin is narrower than the noise on your scale — which is the whole reason this page exists.

Twelve weeks of daily weigh-ins, 72 kg starting weight

a conservative surplus: about +100 g per week

71.4 72.2 72.9 73.7 wk 0 wk 4 wk 8 wk 12
The underlying gain here is perfectly constant at 100 g per week — 1.2 kg over the twelve weeks. Look what that does to the feedback you get: 56 % of mornings are heavier than the morning before, and even the 7-day average moves backwards in five of the eleven weeks. At this rate of gain a single week tells you nothing, and the week-to-week average is barely better. Only the trend fitted over the whole block is unambiguous.

01Muscle is built far more slowly than fat is stored

This is the asymmetry that makes bulking hard. Your body will happily add fat at almost any rate you feed it. Skeletal muscle grows at a rate set by training, recovery, hormones and training age — and no amount of extra food raises that ceiling.

Which means every calorie of surplus beyond what muscle synthesis can actually use has exactly one place to go. Published guidance for natural bodybuilders in the off-season is a slightly hyper-energetic diet targeting a gain of 0.25–0.5 % of body weight per week for novices and intermediates, and around 0.25 % for advanced lifters.1

This page targets 0.1–0.25 % of body weight per week — the conservative end of that guidance, on the assumption that most people reading this are past their first years of training.

70–180 g / week Target rate of gain for a 72 kg lifter. That is 0.9–2.2 kg over a twelve-week block — and a meaningful share of even that is glycogen and water rather than contractile tissue.

If you have been training seriously for years, the honest number is the bottom of that range or below it. Muscle gain slows as you approach your ceiling, and a surplus that was appropriate in your first year becomes a fat-gain programme in your fifth.

02A bigger surplus does not buy more muscle

This is the claim most worth checking, because it contradicts what most people do. The cleanest evidence comes from a randomised trial in elite athletes doing four extra strength sessions a week for 8–12 weeks. One group followed a meal plan engineered for a positive energy balance of roughly 500 kcal a day; the other ate freely.

Guided surplus vs ad libitum eating2

Energy intake3585 vs 2964 kcal
Body weight change+3.9 % vs +1.5 %
Fat mass change+15 % vs +3 %
Lean body mass gainno difference

The larger surplus bought five times the fat gain and no extra lean mass. The authors' own conclusion was that excess energy intake in a weight-gain protocol should be treated with care.

A later randomised trial in trained lifters compared maintenance, a 5 % surplus and a 15 % surplus over eight weeks. Its regression analysis found that the rate of body mass gain predicted the change in skinfold thickness, and concluded that faster weight gain primarily increases the rate of fat gain rather than augmenting strength or muscle thickness.3

A 2019 review of the whole question was blunt about the state of the evidence: the exact energy cost of hypertrophy is not known, and there is no validated "sweet spot" for a surplus that maximises muscle relative to fat.4 That uncertainty is an argument for erring small and measuring, not for erring large and hoping.

Why a small surplus, restated. The surplus is not the raw material for muscle — food you eat this week does not become tissue this week. It is a permissive condition. Its job is to make sure energy availability is never the limiting factor, and a small one does that just as well as a large one, while the large one also fills adipose tissue.

03How big is the surplus, in calories?

Percentages of maintenance are an awkward way to state this, because maintenance is the number you do not know. Work from the tissue instead.

Published estimates for the energy cost of depositing a kilogram of skeletal muscle sit between roughly 1,450 and 1,780 kcal — muscle is about 75 % water, so it is a surprisingly cheap tissue to build.4 Body fat is the expensive one, at the conventional figure of about 7,700 kcal per kilogram.5 Assume a well-run bulk deposits roughly equal parts muscle and fat and a kilogram of gain costs somewhere near 4,600 kcal.

From target rate to daily surplus

72 kg lifter at 0.1 %/wk (70 g)≈ 45 kcal/day
72 kg lifter at 0.25 %/wk (180 g)≈ 120 kcal/day
100 kg lifter at 0.25 %/wk (250 g)≈ 165 kcal/day
Practical range50–200 kcal/day

Arithmetic from the tissue costs above, not a figure lifted from a guideline. Published recommendations are higher — one review advises practitioners to start conservatively at ~1,500–2,000 kJ/day, or 360–480 kcal4 — because they target the faster rate of gain in section 01. At the slower rate, the surplus needed is genuinely this small.

Fifty to two hundred kilocalories a day. That is a slice of bread at the bottom and a handful of nuts at the top. And now the awkward part.

It is very difficult to count your way to a 100 kcal surplus

Self-reported intake is systematically biased. In the reference study, subjects under-reported what they ate by 47 % and over-reported activity by 51 %, with normal metabolisms throughout.6 A systematic review of 59 studies covering 6,298 free-living adults found the same underestimation across every common dietary assessment method when checked against doubly labelled water.7

Measuring expenditure is difficult too. Testing seven wrist-worn devices against indirect calorimetry, no device achieved an energy-expenditure error below 20 %; the best had a median error near 27 % and the worst around 93 %, even though heart rate was accurate to within 5 % on six of them.8

100 kcal target, ±600 kcal instrument On a 2,800 kcal intake, a 20 % error is 560 kcal — several times the entire surplus you are trying to establish. The surplus is smaller than the resolution of the tool you would use to set it.

This is not an argument against tracking. Logging consistently makes your intake repeatable, and a consistent method turns most of the error into a fixed offset, so a change you make is a real change. But the absolute number is a hypothesis. At this size, the surplus cannot be set by counting at all — it can only be set by the scale.

04The scale closes the loop — once you filter it

Body weight integrates your true energy balance whether or not you logged it accurately. Researchers use this directly: a model driven only by demographics and repeated body weight measurements tracked change in energy intake to within 40 kcal/day of the doubly-labelled-water reference over two years.9

The obstacle is that a bulk has a far worse signal-to-noise ratio than a diet, because the signal is so much smaller. Day-to-day variation in body mass has a standard deviation around 0.53 % of body mass — water bound to sodium, glycogen and gut contents, not tissue.10 Notice that the noise is roughly five times a week's worth of progress.

72 kg lifter gaining 0.1 % per week

Signal — real weekly change≈ +0.07 kg
Noise — SD of a single reading≈ 0.38 kg
Signal-to-noise, one weigh-in≈ 0.2
Noise after a 7-day average≈ 0.24 kg
Signal-to-noise, one week of average≈ 0.3
Signal-to-noise, four weeks of average≈ 1.2

Averaging does not deliver the full √7 gain because consecutive days are correlated — a high-carb weekend raises the baseline for several days. In the series plotted above the lag-1 autocorrelation was 0.59 and the 7-day average reduced the noise by a factor of about 1.7.

Read that table twice, because it is the single most useful thing on this page. At this rate of gain, one week of data cannot tell you anything at all, even filtered. The signal only rises above the noise at around a month. Anyone adjusting their intake weekly during a bulk is responding purely to water.

Which is also why the moving average alone is not enough here, and a fitted trend is. In the chart at the top of this page the 7-day average went backwards in five of eleven weeks while the true gain never once stopped. A line fitted across the whole block had no such trouble. Modelling of this exact problem found that daily weights over periods longer than 28 days were required to estimate a change in energy intake to better than ±300 kcal/day.11

Bulking also has a specific trap that dieting does not. Starting a surplus raises carbohydrate intake, glycogen stores refill, and each gram of stored glycogen brings roughly three grams of water with it. The first one to two weeks of any bulk therefore show a jump of a kilogram or more that is not fat and not muscle — which, at a target of 70–180 g per week, is more than a month's worth of real progress arriving in a fortnight and then stopping. If you set your surplus from that first fortnight you will conclude you are gaining far too fast and cut food just as the real process begins. Discard the first two weeks and fit the trend from week three.

05Monitoring steers a bulk — it does not build the muscle

Almost everything on this page is about measurement: how fast to gain, how small the surplus really is, and why only a filtered trend can tell you whether you are on target. That matters, because an unmonitored bulk runs for months before it shows you it was wrong, and by then the extra weight is mostly fat.

But measuring is not the mechanism. The scale reports the outcome; it does not produce it. Muscle is built by hard, progressive resistance training, and by eating well enough to support that training. Those two do the work. The surplus and the trend line only decide how much of what you gain is muscle rather than fat.

The short version. Train hard and eat properly, and careful monitoring turns a good process into a controlled one. Monitor carefully without training hard, and the trend line has nothing worth steering.

Keep the bulk on target

WeightManager plots your raw readings, a moving average and a linear trend line, each togglable on its own, over windows from one week to all time. It runs entirely on your device: no account, no cloud, no server. Log manually, import a CSV, or sync a smart scale through Health Connect.

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References

  1. Iraki J, Fitschen P, Espinar S, Helms E. Nutrition recommendations for bodybuilders in the off-season: a narrative review. Sports. 2019;7(7):154. doi:10.3390/sports7070154
  2. Garthe I, Raastad T, Refsnes PE, Sundgot-Borgen J. Effect of nutritional intervention on body composition and performance in elite athletes. Eur J Sport Sci. 2013;13(3):295–303. doi:10.1080/17461391.2011.643923
  3. Helms ER, Spence AJ, Sousa C, et al. Effect of small and large energy surpluses on strength, muscle, and skinfold thickness in resistance-trained individuals: a parallel groups design. Sports Med Open. 2023;9(1):102. doi:10.1186/s40798-023-00651-y
  4. Slater GJ, Dieter BP, Marsh DJ, Helms ER, Shaw G, Iraki J. Is an energy surplus required to maximize skeletal muscle hypertrophy associated with resistance training? Front Nutr. 2019;6:131. doi:10.3389/fnut.2019.00131
  5. Helms ER, Aragon AA, Fitschen PJ. Evidence-based recommendations for natural bodybuilding contest preparation: nutrition and supplementation. J Int Soc Sports Nutr. 2014;11:20. doi:10.1186/1550-2783-11-20
  6. Lichtman SW, Pisarska K, Berman ER, et al. Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. N Engl J Med. 1992;327(27):1893–1898. doi:10.1056/NEJM199212313272701
  7. Burrows TL, Ho YY, Rollo ME, Collins CE. Validity of dietary assessment methods when compared to the method of doubly labeled water: a systematic review in adults. Front Endocrinol. 2019;10:850. doi:10.3389/fendo.2019.00850
  8. Shcherbina A, Mattsson CM, Waggott D, et al. Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. J Pers Med. 2017;7(2):3. doi:10.3390/jpm7020003
  9. Sanghvi A, Redman LM, Martin CK, Ravussin E, Hall KD. Validation of an inexpensive and accurate mathematical method to measure long-term changes in free-living energy intake. Am J Clin Nutr. 2015;102(2):353–358. doi:10.3945/ajcn.115.111070
  10. Schneditz D, Hofmann P, Krenn S, Waller M, Mussnig S, Hecking M. Day-to-day variability in euvolemic body mass. Ren Fail. 2023;45(2):2273421. doi:10.1080/0886022X.2023.2273421
  11. Hall KD, Chow CC. Estimating changes in free-living energy intake and its confidence interval. Am J Clin Nutr. 2011;94(1):66–74. doi:10.3945/ajcn.111.014399