Athletic populations require high-precision body composition assessments to identify true change. Least significant change determines technical error via same-day consecutive tests but does not integrate biological variation, which is more relevant for longitudinal monitoring. The aim of this study was to assess biological variation using least significant change measures from body composition methods used on athletes, including surface anthropometry (SA), air displacement plethysmography (BOD POD), dual-energy X-ray absorptiometry (DXA), and bioelectrical impedance spectroscopy (BIS). Thirty-two athletic males (age = 31 ± 7 years; stature = 183 ± 7 cm; mass = 92 ± 10 kg) underwent three testing sessions over 2 days using four methods. Least significant change values were calculated from differences in Day 1 Test 1 versus Day 1 Test 2 (same-day precision), as well as Day 1 Test 1 versus Day 2 (consecutive-day precision). There was high agreement between same-day and consecutive-day fat mass and fat-free mass measurements for all methods. Consecutive-day precision error in comparison with the same-day precision error was 50% higher for fat mass estimates from BIS (3,607 vs. 2,331 g), 25% higher from BOD POD (1,943 vs. 1,448 g) and DXA (1,615 vs. 1,204 g), but negligible from SA (442 vs. 586 g). Consecutive-day precision error for fat-free mass was 50% higher from BIS (3,966 vs. 2,276 g) and SA (1,159 vs. 568 g) and 25% higher from BOD POD (1,894 vs. 1,450 g) and DXA (1,967 vs. 1,461 g) than the same-day precision error. Precision error in consecutive-day analysis considers both technical error and biological variation, enhancing the identification of small, yet significant changes in body composition of resistance-trained male athletes. Given that change in physique is likely to be small in this population, the use of DXA, BOD POD, or SA is recommended.