Abstract
This study introduces a novel time-series method to optimize performance in professional cycling, analyzing cardiovascular reactivity and power output in elite cyclists during monument races. Integrating power meter and heart rate data, we derive critical power (CP), assess effort intensity (% CP), and track heart rate dynamics across race quartiles (Q1, Q2, Q3, Q4), revealing heart rate dynamics in elite cyclist. Preliminary testing of this method showed that Top 10 cyclists show significantly higher heart rate increase rates in Q1 (p < 0.05) and greater heart rate modulation in Q1 and Q3 (p < 0.05) than non-top cyclists (Top 11-30), indicating superior cardiovascular responsiveness. Key features include: • Thorough raw data preprocessing for reliability. • Power output normalization to CP for consistent assessment. • Sigmoid modeling of heart rate rise to gauge cardiovascular reactivity. This R-based, reproducible method empowers sports scientists and coaches to boost cyclist performance, with potential use in other endurance sports.