The objective was to determine the test-retest reliability and concurrent validity of a drone system in comparison to a radar device. Seventeen male collegiate soccer players participated in two maximal 30-meter sprint runs. The test-retest reliability of the drone system was evaluated using intraclass correlation coefficients (ICC_3,1), coefficient of variation (CV%), and standard error of measurement (SEM). Subsequently, the systematic bias and consistency of the two devices on various force-velocity (F-V) variables (e.g., maximal velocity [V_max], theoretical maximal velocity [V₀], theoretical maximal horizontal force [F₀], the slope of the F-V relationship [S_FV]) were evaluated using linear mixed model (LMM) and Bland-Altman analysis. The drone system demonstrated moderate to excellent test-retest reliability across all variables (0.59 ≤ ICC ≤ 0.95; CV% < 10%). While LMM analysis detected significant systematic differences for V_max (p = 0.013) and V₀ (p = 0.012), Bland-Altman analysis confirmed high practical agreement with minimal bias (≤ 1.12%) and narrow limits of agreement (LoA < 10%). P_max, split times (T_5m–T_20m) and average accelerations (A_10m–A_20m) demonstrated greater consistency (%Bias ≤ 0.76%) with no significant systematic bias (p > 0.05). Conversely, early-acceleration and model-derived metrics (Tau, A_max, F₀, S_FV) exhibited significant bias (p ≤ 0.028) and wide LoA exceeding 10% (e.g., F₀: -13.37% to 8.56%; S_FV: -11.54% to 18.18%). In conclusion, although the drone system exhibits high monitoring value in the maximum speed phase, early-acceleration metrics (A_max, F₀, and T_5m) should be interpreted with caution for individual-level monitoring. The tracking instability during the early acceleration phase necessitates further algorithm optimization.

• The study evaluated a consumer-grade drone system for sprint force-velocity profiling against a radar using multi-faceted statistical analyses (ICC, CV%, SEM, LMM, Bland-Altman).

• The drone system demonstrated moderate-to-excellent reliability (ICC: 0.59–0.95) and high practical agreement in the maximum speed phase (bias ≤ 1.12%; LoA < 10%), but exhibited significant systematic bias during the initial acceleration phase.

• While suitable for group-level monitoring of maximum velocity metrics, the identified early-phase tracking instability provides clear targets for algorithm optimization in future drone-based sports technology applications.