Why scenarios, and why no target
Searching the literature for validation of the lean-mass-divided-by-chosen-body-fat formula returns nothing. It is arithmetic used in coaching culture, not a research finding. This tool therefore waits for a scenario you choose and labels the result as a conversion.
Body-fat percentage correlates with half-marathon times in recreational runners, but a cross-sectional association does not support a prescription such as "lose X kg, gain Y seconds".
What the running-only reference includes
The reference equals 30 kcal per kg of current fat-free mass plus estimated gross running cost at the entered weekly mileage. It is a comparison line, not a minimum intake, diagnosis or assurance of safety.
It deliberately omits strength work, cycling and every other training cost. Add those separately before comparing the number with a full-day intake plan. Recalculate when weekly running changes.
When the answer is "don't"
For a large share of runners, weight may not be the constraint. In a meta-analysis of 6,118 athletes, 44.7% were classified with low energy availability, and prevalence was higher in men (49.4%) than women (44.2%).
Low energy availability was associated with lower run performance, endurance, coordination, concentration, judgment and explosive power, alongside impaired bone health and higher bone-stress-injury risk. In male endurance athletes it also correlates with lower testosterone, lower bone density and a reduced resting metabolic rate. These findings describe associations and risk background, not an individual causal forecast.
The body-fat input is the weakest link
Everything here scales off fat-free mass, so the body-fat input matters more than the arithmetic. Bioimpedance scales carry meaningful individual variability on single and repeat measurements. Use the same device and conditions to follow a trend rather than treating one scenario result as precise.
Screening, and when to involve a clinician
Two validated-in-progress questionnaires exist, and they are sex-specific. LEAF-Q is the established screening route for female athletes. For men, LEAM-Q was developed more recently — in its validation cohort, low sex drive was the single most effective self-reported symptom for identifying men needing further clinical assessment.
Screening questionnaires flag risk; they do not diagnose. Missed periods, repeated bone-stress injuries, persistent fatigue or frequent illness are reasons to involve a sports physician or dietitian rather than to adjust a calculator input.