Why Whoop Falls Short: Lessons from Early Physiologists on True Performance Readiness

There are two lesser-known quotes from early physiologists that have influenced my work more than any others. These quotes, while seemingly simple, provide profound insights into why many modern wearable companies fail to accurately measure readiness, quantify fitness, or predict exercise performance. Despite being foundational to our understanding of human cardiovascular control, the significance of these statements has been largely forgotten in today’s fitness and wearable technology landscape.

“Exercise, more than any other stress, taxes the regulatory ability of the cardiovascular system. The advantage to the investigator is that more is learned about how a system operates when it is forced to perform than when it is idle.”?– Loring B. Rowell,?Human Cardiovascular Control?(1986)

“Scaling from measurements at rest suffers from the marked random variation characterizing that loosely defined state.”?– Joseph Barcroft,?Features in the Architecture of Physiological Function?(1934)

These quotes underscore the core issue with relying on resting physiological data for performance readiness assessments. They set the stage for understanding why real physiological stress testing, rather than idle measurements, is essential for gaining true insights into an athlete’s performance capacity. Despite their importance, the insights of early physiologists like Barcroft and Rowell are often overlooked or misunderstood today. Barcroft’s most impactful work dates back to the early 1900s, and while Rowell’s contributions are more recent, they have similarly faded into obscurity in mainstream fitness discussions. Yet, their work remains crucial for properly interpreting modern physiological data, particularly in the context of wearable technology and fitness tracking.

The Problem with Wrist-Worn Wearable Devices

Today, wearable technology companies—like WHOOP and Oura—are focused on providing users with insights into their fitness, recovery, and overall readiness. However, many of these companies lack a deep understanding of the underlying physiology they are attempting to measure, leading to flawed interpretations and inaccurate conclusions. The root of the problem lies in their heavy reliance on resting data, such as heart rate variability (HRV), resting heart rate, and sleep patterns, to predict performance readiness. Without grasping the basic principles established by early physiologists, such as the stress-induced behavior of the cardiovascular system, wearable companies fail to contextualize their data properly.

This reliance on resting data for assessing fitness and readiness ignores the critical fact that true fitness and performance capacity can only be fully understood when the body is subjected to stress. At rest, the body’s physiological systems, including the cardiovascular system, are operating at a minimal level, far from the demands placed on them during intense physical activity. As Rowell pointed out, more is learned about how the cardiovascular system works when it is forced to perform under stress, such as during exercise, than when it is idle. If these early insights were more widely recognized, many of the flawed assumptions currently underpinning modern wearables would be avoided, and devices could more effectively assess athletic readiness and potential.

Understanding the Importance of Exercise Data

Loring B. Rowell’s statement emphasizes a fundamental truth about physiological systems: they reveal their true nature when challenged by stress. For the cardiovascular system, this stress comes most naturally in the form of exercise, which forces the heart, lungs, and circulatory system to work at their peak to deliver oxygen and nutrients to muscles. At rest, these systems aren’t taxed, and the data collected from them—such as HRV or resting heart rate—doesn’t provide a full picture of an athlete’s readiness to perform under real-world conditions.

Rowell’s insight is crucial for understanding why many wearable devices fall short in assessing performance readiness. Modern devices often rely on resting data, which fails to capture the dynamic responses of the body under stress. For instance, heart rate variability (HRV) is often measured while the user is asleep or at rest. HRV, a measure of the variation in time between heartbeats, is sometimes used as a proxy for recovery and readiness. However, it doesn’t provide a reliable indicator of how well the body can cope with the demands of exercise or competition. The cardiovascular system, when idle, isn’t revealing its true capacity.

Exercise forces the cardiovascular system to work harder, allowing researchers and athletes to see how well the body can handle stress. This is why exercise-induced data is so much more valuable than resting data for assessing readiness. As Rowell’s statement highlights, it’s only when the body is forced to perform that its true capacity is revealed. Consequently, any assessment that focuses only on resting physiological data will miss the full picture of an athlete’s preparedness.

This principle is best exemplified by the gold-standard VO2max test, which measures the body’s ability to deliver and utilize oxygen during maximal physical exertion. VO2max is widely regarded as one of the most reliable indicators of cardiovascular fitness. It provides a far clearer understanding of an athlete’s capacity than resting data points, such as heart rate, blood pressure, or blood oxygenation levels. VO2max assesses how efficiently the body can function at peak levels, whereas resting measures can only offer a static, incomplete snapshot.

Why Resting Data Alone Falls Short

Joseph Barcroft’s observation adds another layer of complexity to this discussion. His quote about the limitations of scaling from resting measurements points to the inherent variability in what we consider a “resting” state. Rest, as a physiological state, is highly inconsistent, influenced by numerous factors such as sleep cycles, environmental conditions, mental stress, and random biological fluctuations. These factors create significant variability in resting physiological data, making it difficult to accurately assess performance readiness based solely on these metrics.

Wearable devices like WHOOP and Oura often collect HRV data during sleep or idle periods, assuming that these resting states provide a stable baseline for measuring recovery and readiness. However, as Barcroft noted, the variability in resting measurements makes it unreliable for such assessments. HRV, for example, changes throughout the night depending on sleep stage, circadian rhythms, and other physiological processes. As a result, a high HRV reading during a particular phase of sleep might indicate good recovery, but it doesn’t account for factors like muscle soreness, fatigue, or injury that could still impair performance. This leads to misleading results, where an athlete may be told they are ready to perform based on their resting HRV when, in reality, their body is far from prepared for intense activity.

By relying on these inconsistent resting metrics, wearable companies like WHOOP provide data that can mislead coaches and athletes into making incorrect training decisions. Athletes may believe they are more recovered and ready to train than they truly are, or they might be advised to rest when they are actually capable of performing well. This flawed approach stems from a misunderstanding of the body’s physiological response to stress and the inherent variability of the resting state.

Why Stress Testing Provides a Better Understanding of Readiness

When we bring these two physiological insights together, it becomes clear that current wearable readiness assessments based on resting data are insufficient. Resting measures fail to capture the body’s true performance potential under stress, and the variability inherent in rest makes it difficult to draw reliable conclusions. In contrast, assessments that incorporate exercise or performance-based stressors provide a clearer, more actionable picture of an athlete’s readiness.

Stress tests eliminate many of the random fluctuations present during rest and provide a more stable and accurate measure of the body’s readiness to perform. For example, VO2max testing reveals how well the cardiovascular system delivers oxygen to working muscles during peak exertion, providing a direct measure of an athlete’s endurance and performance capacity. By observing how the body functions under load, we can gain a more precise understanding of its inherent capabilities and limitations.

The NNOXX Approach: Real-Time, Exercise-Induced Readiness Assessment

Recognizing the limitations of relying on resting physiological data, NNOXX Inc. has developed a new readiness assessment that focuses on real-time physiological data recorded during exercise. By measuring metrics like muscle oxygenation (SmO2), NNOXX offers a more robust and accurate indicator of performance readiness. Muscle oxygenation measures how well oxygen is supplied to and utilized by working muscles during exercise, a critical predictor of performance capacity.

Unlike HRV, which can fluctuate significantly and give misleading insights, muscle oxygenation directly reflects how muscles are coping with physical stress and how efficiently they are recovering. For instance, even if an athlete’s HRV is high, severe muscle soreness or poor recovery may still impair their performance—a limitation HRV alone cannot detect. NNOXX’s approach, by focusing on real-time data during exercise, captures these subtle but important physiological responses, providing a clearer picture of an athlete’s readiness.

By measuring muscle oxygenation during exercise, NNOXX provides a reliable, actionable metric of how well muscles are functioning under load, directly correlating with endurance and performance outcomes. This makes the NNOXX approach far more valuable for athletes looking to optimize their training and performance, as it moves beyond the limitations of resting data and reveals the body’s true capacity to perform under stress.

Conclusion

The insights of early physiologists like Loring B. Rowell and Joseph Barcroft are as relevant today as ever. Their observations about the limitations of resting data and the importance of stress testing provide critical lessons for modern wearable companies. By relying too heavily on resting physiological metrics, companies like WHOOP fail to capture the full picture of an athlete’s readiness. Exercise-induced data, such as muscle oxygenation, provides a much clearer and more actionable assessment of true performance potential. As NNOXX demonstrates, focusing on real-time data during exercise offers a more reliable way to measure readiness and optimize performance, moving beyond the flawed assumptions that currently undermine many modern wearables.