We have discussed heart rate variability before but it remains a frequently used and more frequently misunderstood metric. So what is the reality of the science behind this oft touted measure of training and racing readiness?

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Table of Contents

• Heart rate variability revisited.

• Mike Sheridan, another endurance athlete who prove …

• Episode takeaways:

  • References used for the MMB

Heart rate variability revisited.

Heart rate variability (HRV) has become one of the most widely used metrics for assessing training readiness in endurance sports, but the reality is more nuanced than many marketing claims suggest. HRV measures the variation in time between heartbeats and reflects activity within the autonomic nervous system. In general, higher HRV is associated with greater parasympathetic (“rest and recover”) activity, while suppressed HRV may indicate stress, fatigue, illness, poor sleep, or insufficient recovery.

In practice, HRV can be a useful tool when viewed as part of a larger picture rather than a standalone decision-maker. Trends over time are far more valuable than single daily readings. Athletes who monitor HRV consistently under VERY strict similar conditions—typically first thing in the morning—can often identify patterns associated with accumulated fatigue, overreaching, travel stress, or impending illness. A sustained downward trend may suggest the need for additional recovery or reduced training intensity.

However, HRV is highly sensitive to many factors unrelated to fitness or training readiness. Alcohol consumption, dehydration, psychological stress, sleep disruption, caffeine intake, altitude, illness, and even measurement timing can significantly influence readings. Because of this variability in the assessment of….variability, athletes may overreact to normal day-to-day fluctuations if HRV is interpreted too rigidly.

Scientific evidence suggests HRV-guided training can modestly improve training adaptation in some athletes, particularly endurance athletes, but results are inconsistent across populations. Importantly, subjective measures such as mood, motivation, sleep quality, muscle soreness, and perceived fatigue often correlate as strongly—or more strongly—with performance readiness than HRV alone.

In this episode’s MMB we review the most up to date evidence and provide some guidelines and a healthy dose of skepticism to the hype around HRV. In reality the most effective approach is to integrate HRV with other indicators rather than treating it as a definitive “green light” or “red light” system. Used intelligently, HRV can help athletes avoid excessive fatigue and better individualize recovery, but it remains one imperfect data point within the broader context of training, lifestyle, and personal experience.

Mike Sheridan, another endurance athlete who proves that for some, age really need only be a number

Mike according to Mike: Author of “Dare to Dream” Only took up running at 60 - went on to become 4th man ever to go sub 3 over 70+. Currently British marathon record holder 2.59.13 (V70) & world 50k record holder (V70)

Mike Sheridan is a British masters marathon runner best known for becoming one of the very few men over age 70 to break the three-hour barrier in the marathon. In the 2021 London Marathon, Sheridan ran 2:59:37 at age 72, becoming the first British man over 70 to run a sub-3 marathon. (My BEST Runs)

He followed that up in 2023 with a 2:59:13 performance at the London Marathon, which set a British M70 record. (Newbury Today) All of this despite only taking up running in his sixties!

Sheridan is often discussed alongside legendary masters runners such as Ed Whitlock and Gene Dykes. Whitlock remains the officially recognized M70 world-record holder with 2:54:48, while Dykes ran 2:54:23 on a non-ratified course. (Wikipedia)

Mike is considered one of the greatest age-group marathoners ever and one of only a handful of runners over 70 to achieve a sub-3-hour marathon. His performances are especially admired because they came well into his seventies rather than immediately after turning 70. (My BEST Runs)

In our conversation Mike tells me how he manages running at his age, how he stays injury free and how he continues to find joy in a sport that often wears people down who are much younger than he.

Episode takeaways:

• Believe in your potential, even if you're not about to run a 5k in 20 minutes right out of the gate.

• Starting your running journey might mean walking half a mile first - no shame in that game!

• Success in running isn't about Olympic medals, but about taking those baby steps and showing up.

• Heart rate variability is the hot topic, but don’t let it dictate your training decisions too harshly.

References used for the MMB

Addleman, J. S., Lackey, N. S., DeBlauw, J. A., & Hajduczok, A. G. (2024). Heart Rate Variability Applications in Strength and Conditioning: A Narrative Review. Journal of functional morphology and kinesiology, 9(2), 93. https://doi.org/10.3390/jfmk9020093

• Conducted a narrative review on the use of heart rate variability (HRV) in strength and conditioning, focusing on athlete monitoring, recovery, overtraining, and HRV-guided programming.

• Reviewed literature identified through searches of PubMed and Scopus using keywords related to HRV, strength training, overtraining, and HRV-guided training.

• Synthesized evidence on how HRV responds to endurance training, resistance training, overreaching, and recovery across different athletic populations.

• Evaluated methodological considerations for HRV monitoring, including time-domain metrics (especially RMSSD), recording protocols, device selection, and interpretation relative to individual baselines and rolling averages.

• Proposed preliminary evidence-based guidelines for implementing HRV monitoring and HRV-guided training in strength and conditioning settings.

Bellenger, C. R., Fuller, J. T., Thomson, R. L., Davison, K., Robertson, E. Y., & Buckley, J. D. (2016). Monitoring Athletic Training Status Through Autonomic Heart Rate Regulation: A Systematic Review and Meta-Analysis. Sports medicine (Auckland, N.Z.), 46(10), 1461–1486. https://doi.org/10.1007/s40279-016-0484-2

• The authors systematically selected studies (n=27) assessing HRV (RMSSD, HF power, SD1), heart rate recovery, and heart rate acceleration to compare autonomic responses between performance-enhancing training and overreaching.

• Positive training adaptations (improved endurance performance) are associated with increases in vagal-related HRV indices (RMSSD, HF power, SD1), improved post-exercise HR recovery, and increased HR acceleration.

• Overreaching (negative adaptation) also increases some post-exercise HRV and HR recovery measures, meaning these markers alone cannot reliably distinguish fatigue from beneficial adaptation.

• Resting HRV changes are inconsistent and relatively insensitive to overreaching, suggesting limited usefulness for detecting training stress or maladaptation.

• HR acceleration may decrease with overreaching, making it a potential indicator of training-induced fatigue.

• Main conclusion: no single autonomic measure is sufficient; multiple HR-based indices are needed to differentiate positive training adaptation from negative training stress.

Besson, C., Baggish, A. L., Monteventi, P., Schmitt, L., Stucky, F., & Gremeaux, V. (2025). Assessing the clinical reliability of short-term heart rate variability: insights from controlled dual-environment and dual-position measurements. Scientific reports, 15(1), 5611. https://doi.org/10.1038/s41598-025-89892-3

• Measured heart rate variability (HRV) in 34 healthy, physically active adults using a standardized protocol across home and laboratory settings, supine and standing positions, over two consecutive days.

• Tested whether short-term HRV readings were reliable across environments, body positions, and repeated measurements using statistical reliability methods (especially ICCs and error metrics).

• Found that HRV is generally stable and reliable when strict protocols are followed, with good consistency across home vs lab and across days.

• Identified that RMSSD and heart rate were the most reliable HRV measures, while frequency-domain metrics (e.g., LF, HF, LF/HF ratio) were more variable and sensitive to conditions, especially standing posture.

• Concluded that standardized short-term HRV protocols can be used confidently in real-world and lab settings, but results depend strongly on controlling posture, timing, and environmental factors.

Esco, M. R., Fields, A. D., Mohammadnabi, M. A., & Kliszczewicz, B. M. (2025). Monitoring Training Adaptation and Recovery Status in Athletes Using Heart Rate Variability via Mobile Devices: A Narrative Review. Sensors (Basel, Switzerland), 26(1), 3. https://doi.org/10.3390/s26010003

• Conducted a narrative review on the use of mobile HRV technologies for athlete monitoring, focusing on methodological considerations related to device selection, HRV metric choice, recording procedures, and longitudinal interpretation of HRV data.

• Evaluated two main ideas: RMSSD is the preferred HRV metric for field-based athlete monitoring due to its reliability, reduced sensitivity to respiratory variation, and validity in ultra-short recordings; the utility and limitations of mobile HRV devices, including chest straps, wrist wearables, rings, and smartphone-based photoplethysmography (PPG) systems.

• Recommended standardized HRV collection procedures, particularly consistent morning recordings under controlled conditions.

• Emphasized longitudinal HRV interpretation using weekly mean RMSSD and RMSSD coefficient of variation as complementary markers of chronic training adaptation and short-term autonomic perturbation/recovery status.

Gronwald, T., Kock, H., Röglin, L., Möhle, M., Kircher, E., Hoos, O., & Ketelhut, S. (2025). Recovery of Linear and Nonlinear Heart Rate Variability Metrics After Short-Term Moderate versus Vigorous Intensity Exercise: A Cross-Sectional Randomized Cross-Over Study. European journal of sport science, 25(11), e70077. https://doi.org/10.1002/ejsc.70077

• Compared recovery after moderate treadmill exercise and vigorous exergaming in 26 recreationally active adults

• Measured heart rate, heart rate variability (HRV), DFAa1, blood pressure, and pulse wave velocity before exercise and during 45 minutes of passive recovery

• Vigorous exercise caused slower recovery of parasympathetic (“rest-and-digest”) activity.

• Traditional HRV measures stayed suppressed longer after vigorous exercise.

• DFAa1 increased more after vigorous exercise, suggesting the body entered a more tightly controlled, less complex recovery state.

• Main conclusion: Harder exercise creates a bigger physiological disturbance, so the autonomic nervous system takes longer to return to baseline, and DFAa1 may be a useful tool for monitoring recovery and training stress.

Kellmann, M., Bertollo, M., Bosquet, L., Brink, M., Coutts, A. J., Duffield, R., Erlacher, D., Halson, S. L., Hecksteden, A., Heidari, J., Kallus, K. W., Meeusen, R., Mujika, I., Robazza, C., Skorski, S., Venter, R., & Beckmann, J. (2018). Recovery and Performance in Sport: Consensus Statement. International journal of sports physiology and performance, 13(2), 240–245. https://doi.org/10.1123/ijspp.2017-0759

• The authors conducted a narrative review of existing research on recovery, fatigue, and performance in sport science.

• They evaluated different athlete monitoring methods, including:

  • Performance tests

  • Physiological markers (e.g., heart rate variability, blood biomarkers)

  • Psychological questionnaires

• They highlighted heart rate variability (HRV) as a key physiological marker of recovery because it reflects autonomic nervous system balance and can indicate stress vs. recovery status in athletes - noting that no single measure (including HRV) is sufficient on its own.

Shaffer, F., & Ginsberg, J. P. (2017). An Overview of Heart Rate Variability Metrics and Norms. Frontiers in public health, 5, 258. https://doi.org/10.3389/fpubh.2017.00258

• The authors reviewed and compared multiple HRV studies and normative datasets, analyzing how differences in recording length, methods, and subject conditions affect HRV measures and their reliability.

• HRV is highly context-dependent, varying with recording length, sampling rate, device type, and artifact correction; ultra-short, 5-min, and 24-hour measures are not interchangeable.

• Respiration strongly influences HRV, with slower/deeper breathing increasing RSA and altering frequency-domain patterns, especially during paced or resonance breathing.

• Data quality is critical, as even small artifacts can significantly distort HRV metricsIndividual factors shape HRV, including age-related decline, sex differences, resting heart rate, and overall health status.

• Interpretation depends on timescale, with 24-hour HRV best for prognosis, 5-minute for standardized assessment, and ultra-short recordings limited in reliability.