Key result
Autoregulated training boosts VO₂max by ~3.9 mL/kg/min vs conventional programming in competitive speed skaters.
Why the study?
Multidomain reserve modelling based on aerobic, neuromuscular, and autonomic systems remains under-researched, and whether autoregulated training improves physiological reserve over conventional programming was unknown.
Does autoregulated macro-microcycle training using HRV and RPE feedback improve physiological reserve and adaptability compared to volume-matched conventional programming in competitive speed skaters?
RCT (n=18)
Does autoregulated macro-microcycle training using HRV and RPE feedback improve physiological reserve and adaptability compared to volume-matched conventional programming in competitive speed skaters?
Mean Difference: 3.9
p-value: p=0.010
Autoregulated training using HRV and RPE feedback significantly improves aerobic capacity, neuromuscular power, and autonomic balance in competitive speed skaters compared to conventional linear periodization.
Hypothesis-generating in athletes; does not support practice change without randomized confirmation.
The personalization of training is one of the main pillars of performance science, but multidomain reserve modelling based on aerobic, neuromuscular, and autonomic systems remains under-researched. Unlike fixed-load models, the approach uses real-time heart rate variability (HRV) and performance load ratio (PLR) feedback to tune training and recovery, offering a new, evidence-based approach to maintaining the adaptive potential of speed skating. This study tested whether an autoregulated macro–microcycle using readiness signals improves physiological reserve versus volume-matched conventional programming. Eighteen intercollegiate athletes underwent 24 weeks of closely supervised training with the same volume but different load-modulation guidelines. The intervention arm maintained daily intensity using HRV-based readiness thresholds and session-RPE feedback, whereas the control group followed preset linear periodization. Outcomes included maximal oxygen uptake (VO₂max), lactate threshold (LT), Wingate anaerobic peak power, countermovement jump (CMJ), heart rate recovery at 1 min (HRR-1), root mean square of successive differences (RMSSD), the low-frequency to high-frequency ratio (LF/HF), and a composite Performance Reserve Index (PRI). Linear mixed model analysis, subgroup contrast, correlation matrices, and cluster segmentation analyses were done. Compared with conventional programming, larger gains were observed for VO₂max (+ 3.9 mL/kg/min, p = 0.010, d = 0.92), lactate threshold (+ 0.57 mmol/L, p = 0.003, d = 1.04), Wingate peak power (+ 67 W, p = 0.005, d = 1.00), CMJ height (+ 4.2 cm, p = 0.021, d = 0.83), HRR-1 (+ 8.3 bpm, p = 0.009, d = 0.93), RMSSD (to 47.6 ms, p = 0.007, d = 0.96), and PRI (0.62→0.85, p < 0.001, d = 2.41). The coordinated aerobic, neuromuscular, and autonomic pattern indicates tighter stimulus–recovery coupling under autoregulation. The autoregulated macro-microcycle training resulted in combined advantages in aerobic capacity, neuromuscular power, and autonomic balance, demonstrating the effectiveness of individualized feedback control as the next-generation paradigm for maximizing long-term adaptation in competitive speed skating. Coaches can apply simple HRV thresholds and sRPE bounds to cap or extend sessions and use PLR bands to schedule deloads and Zone-2 extensions. The study was retrospectively registered with the UK ISRCTN registry (ISRCTN16362421) on 04 September 2025.
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Di et al. (2025) conducted an RCT in Competitive speed skating (n=18). Autoregulated macro-microcycle training vs. Volume-matched conventional programming (preset linear periodization) was evaluated on Maximal oxygen uptake (VO₂max) (MD +3.9 mL/kg/min (d = 0.92), p=0.010). Autoregulated macro-microcycle training improved VO₂max (+3.9 mL/kg/min, p=0.010) and other physiological markers compared to conventional programming in competitive speed skaters.
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