A TDEE estimate is only as honest as its assumptions. Below is what the literature actually says about
where these calculators break down — and how this tool tries to do better. Citations refer to the
sources listed at the end.
1. They predict a population, not you
Equations like Mifflin-St Jeor and Harris-Benedict are regressions fit to groups. They work “reasonably
well across large groups, but an individual can easily be 10–20% above or below the prediction”
[Problems]. A true maintenance of 2,800 kcal could be predicted anywhere from ~2,400 to
~3,200. The Pontzer life-course dataset is blunter still: total expenditure varies
more than ±20% between people even after controlling for fat-free mass, fat mass,
sex and age [Pontzer 2021]. That irreducible spread is why we show a range, not just a point.
2. Activity buttons are too blunt
“Sedentary / lightly / moderately / very active” are vague. A student who lifts five days a week but
sits otherwise may pick “very active,” while a warehouse worker with no gym time picks “moderately active”
and is badly under-counted [Problems]. We instead build a Physical Activity Level from your
described job (PAL bands from the FAO/Black tables: seated 1.4–1.5, standing work 1.8–1.9,
strenuous 2.0–2.4 [Estimating]) and add each workout separately via METs
[Computational].
3. Exercise calories are inflated
Trackers, cardio machines and online calculators routinely overstate burn: “someone who believes they
burn 800 calories during a workout may actually burn 400–600” [Problems]. Two guards keep us
honest — we use moderate MET values, and we count only the net cost above rest
(MET − 1), because the resting calories during that hour are already inside your base multiplier.
4. NEAT is the hidden hundreds
Non-Exercise Activity Thermogenesis — walking, fidgeting, standing, chores — is the single largest swing
factor. “Two people with identical workouts can differ by hundreds of calories per day because one
naturally moves much more than the other” [Problems]. In sedentary people EAT can be ~0% of
expenditure; NEAT makes up the remainder [Estimating]. That’s why a step count moves your
number here, and why the honest range stays wide.
5. Total weight ≠ metabolic tissue
Fat-free mass is what correlates with resting metabolism, “independent of age, BMI, and other metabolic
variables” [One2One]. Two 158-lb people at 33% vs 45% body fat had RMRs of 1,571 vs 1,252
kcal/day [One2One]. Equations on total weight alone can’t see that. With a body-fat input we
switch to Katch-McArdle (370 + 21.6 × lean mass) and cross-check it against the FFM equation
23.9 × FFM + 372 [Estimating] and the Pontzer FFM power law [Pontzer 2021].
6. Metabolism isn’t static
After a prolonged deficit, every component of expenditure falls — BMR, NEAT, the thermic effect of food,
even the cost of moving — by more than lost tissue predicts. This adaptive
thermogenesis persists after weight stabilises, and its size is proportional to the deficit
[Trexler 2014]; very-low-calorie dieting slows metabolism to protect vital organs
[One2One]. Overfeeding pushes the other way (~+7% acutely [Trexler 2014]).
The diet-history selector applies a modest version of this.
7. On plasma donation — where the numbers actually come from
This figure is derived from biochemistry, not invented. Plasma is 91–92% water and 8–9%
solids, carrying ~70–90 g/L of protein [StatPearls][Deranged Physiology].
A plasma session keeps ~690–880 mL (more for heavier donors), removing roughly 50–66 g of protein.
The cost has two parts: the caloric content that leaves (~4 kcal/g) and the energy to
resynthesise it (~2.2 kcal/g). A PhD-biochemistry itemisation pegs a whole-blood unit at
~425–460 kcal of content, “higher” once synthesis inefficiency is added [Maynard]; an
apheresis director cites ~500 kcal to replace a donation [Columbia] and UC San Diego ~650
[UCSD]. Those higher figures are for whole blood, most of which is hemoglobin.
Plasma donation returns your red cells [StatPearls], so the plasma-specific number is lower,
~355–455 kcal — which is what this tool computes, scaled by your weight. It remains the most variable
input (hydration, diet, protein level, donation type), so it’s the one we let you tune directly.
Finally, the honest disclaimer no parser can remove: self-reported activity is biased.
People over-report exercise and under-report sitting; structured-text parsing makes the estimate
granular and transparent, but it cannot make a rough self-description accurate. Treat the output
as a hypothesis to test against two weeks of weigh-ins, not a measurement. The gold standard remains
indirect calorimetry or doubly-labelled water [Estimating].
8. BMI is a population tool, not a verdict on you
The BMI shown above is just weight ÷ height² — a fine screen across large groups, but it
cannot tell muscle from fat. A lean 180-lb lifter and a sedentary 180-lb person get the
identical BMI, and muscular athletes are routinely flagged “overweight” or even “obese.” It also ignores
fat distribution, age, sex, and ethnicity. This is the same lesson as the rest of the tool: total weight
hides body composition. Read your BMI as rough context, and trust your body-fat % and the mirror over the
category label.
9. How the macro targets are built (and why the deep cut is red)
Protein comes first, set per Stronger By Science [SBS]: ~2.0 g/kg bodyweight
to maintain or gain (women ~1.75), and — when you enter body-fat % — scaled to fat-free mass
(~2.35 g/kg FFM), which SBS argues is the more accurate anchor. Dieting raises the target (≥2.5 g/kg FFM,
up to 4.0) to defend lean mass, and the benefit is larger the leaner you are. This converges with
Roberts/Helms’ 1.8–2.7 g/kg (up to 3.5) [Roberts 2020]. Fat is set at
15–25% of calories (a little lower on a cut) with a 0.5 g/kg floor for hormones [Roberts 2020],
and carbohydrate takes the remaining “energy budget.” Resistance trainees genuinely don’t
need the 4–7 g/kg carb loads borrowed from endurance sport — low-carb doesn’t impair lifting performance or
hypertrophy signalling [Carb Need].
The slider turns red toward the −1,000 deficit for a reason: a gradual loss of
0.5–1% of bodyweight per week best preserves muscle [Bulk/Cut], and the size of
the deficit drives the size of the metabolic adaptation and muscle loss [Trexler 2014]. The
badge tells you your personal weekly rate, since “too aggressive” depends on your bodyweight — a
−1,000 deficit is ~1.1%/week for an 80 kg lifter (danger) but only ~0.9% for someone at 100 kg. These macros
are a research-grounded starting point; adherence and two weeks of real-world adjustment matter more than the
decimals.
This tool is for education and self-experimentation, not medical advice. Energy needs in pregnancy,
growth, illness, or endocrine disorders fall outside these equations — consult a qualified professional.