Heart rate variability (HRV) dynamics following training sessions provide insight into the balance between physiological stress and recovery. Traditional approaches often reduce HRV to scalar summaries, overlooking the information contained in the full recovery trajectory. This study applies **Functional Principal Component Analysis (FPCA)** to HRV recovery profiles, enabling multidimensional characterization of features such as depth of suppression, speed of return, and potential overshoot.