What Every Mountain Athlete Needs to Know About Heart Rate Variability

I recently sat down with Dr. Marco Altini—a PhD data scientist, guest lecturer at Vrije Universiteit Amsterdam, advisor for Oura, author of over 50 peer-reviewed papers, and founder of the HRV4Training platform—to talk about heart rate variability. Marco is also a Boston Qualifier and ultra-runner who treats his own body like a walking laboratory. But the reason I wanted to talk to him was not his software or his resume. It was his philosophy.

In a world where wearables are trying to sell you a green light or a readiness score to run your training, Marco has been a voice of restraint. He is the data scientist telling you that if you wake up feeling great but your watch says you are tired, you should trust yourself, not the machine.

What followed was one of the most clarifying conversations I have had about a tool that our coaching team uses daily—and one that I think many athletes are misusing.

A note on how we got here: Our coaching team’s understanding of HRV has evolved significantly over the years, from initial skepticism of app-based recommendations to a more nuanced framework for using HRV as one input within a structured coaching approach. This article represents our current thinking, shaped heavily by the research and philosophy of Dr. Altini.

What Does HRV Actually Measure?

Your heart does not beat at a constant frequency. There is always some variation between beats, measured in milliseconds, and that variation is not random. When measured at the right time—first thing in the morning or during sleep—it reflects the activity of your autonomic nervous system (ANS).

The ANS controls many functions you do not consciously manage: heart rate, digestion, breathing rate. It has two main branches. The parasympathetic branch (“rest and digest”) is more active when you are resting and recovering; it modulates heart rhythm, and higher parasympathetic activity means higher variability between heartbeats. The sympathetic branch (“fight or flight”) puts the body in a state to act. Stress of any kind—physical, emotional, environmental—activates the sympathetic branch and suppresses variability. Heart rate works in the opposite direction: stress pushes it up, rest brings it down. Most people can relate to this intuitively. When you are stressed, you can feel your heart racing. HRV is simply a more sensitive, measurable expression of that same physiology.

Generally, higher HRV (more variability between heartbeats) is associated with a more relaxed, rested, and recovered state, as well as improved cognitive functioning and better emotional regulation under stress. Lower HRV (less variability) is associated with more inflammation, increased disease risk, and a more stressed physiological state. Research has consistently linked higher resting HRV to better executive functioning, improved focus, and more effective coping strategies—qualities that matter in the mountains as much as they do anywhere else.

But here is the critical distinction that Marco kept returning to: HRV reflects your response to stress, not the stress itself. If you respond well to a hard training day, your HRV will bounce back to normal within 24 hours. Good variability does not mean you experienced no stress. It means you handled it. And if your HRV does not renormalize within a day, something is likely off.

What Factors Influence Your HRV?

HRV responds within the incredibly dynamic system that is the human body. Its complexity allows it to react quickly to both external changes (temperature, altitude) and internal changes (mood, cognitive processes, digestion). This sensitivity is both its strength as a signal and the reason it must be interpreted carefully. A single reading taken in isolation tells you very little. A trend over days and weeks, measured consistently and understood against the backdrop of your training, sleep, and life stress, tells you a great deal.

The major factors that influence HRV include:

Exercise and training status. Athletes who exercise regularly tend to have higher resting HRV than sedentary individuals. However, HRV is temporarily suppressed during and immediately after exercise, returning to baseline once recovery is complete. The time course of that return is itself a useful signal of how well you are absorbing a given training load.

Sleep. Both quality and quantity of sleep strongly affect HRV. Poor sleep is one of the most common causes of suppressed morning readings. The association is strong enough that some researchers have proposed low HRV as a screening tool for sleep disorders.

Stress. Psychological and emotional stress suppress HRV through the same sympathetic pathway as physical stress. Work pressure, relationship strain, financial worry—these all show up in the data. This is why most of the time when HRV trends negative, it is life happening, not training.

Mood and mood disorders. Anxiety and depression are significantly associated with lower HRV. The brain exerts an inhibitory influence on heart rate at rest, and mood disorders weaken this influence, reducing variability.

Substances. Caffeine, alcohol, nicotine, and sleeping pills all affect HRV. Caffeine consumption before exercise has been shown to delay the return of HRV to baseline. The more recent the use, the stronger the influence.

Sex. Women generally tend to have higher HRV, particularly before menopause, when estrogen increases parasympathetic influence on heart activity. For female athletes, menstrual cycle phase can cause HRV fluctuations that wearables may misinterpret as stress or under-recovery. We cover this in detail in our companion article on HRV and the menstrual cycle.

Age. HRV generally declines with age, likely due to decreased parasympathetic nervous system activity. However, endurance athletes who maintain high fitness levels can preserve higher HRV values well into middle age.

Body composition. Obesity is generally associated with lower HRV, partly because excess body weight creates additional physiological stress and is associated with lifestyle factors that reduce variability.

Seasonality. Resting heart rate tends to be lower in summer and higher in winter, with HRV following the inverse pattern. If you live somewhere with distinct seasons, you may see a chronic baseline shift that has nothing to do with your training or recovery. Whether this means you truly cannot assimilate as much stress in winter is an open question, but it is worth keeping in mind before you panic about a slow downward drift that started when the days got short.

Why Are Readiness Scores Misleading?

Many wearables now offer compound readiness scores that aggregate sleep, HRV, resting heart rate, and activity into a single number. In principle, the idea makes sense. In practice, Marco argues these scores do athletes a disservice.

The problem is that these scores mix behavioral assumptions with physiological data. If you logged more activity than usual, the algorithm assumes you must be less ready. If you slept fewer hours, the score drops. But these are deterministic rules, not measurements of how your body actually responded. More exercise does not automatically mean less readiness. A couple of short sleep nights do not necessarily mean you cannot perform.

Marco gave the cleanest example: you could edit your sleep duration inside an app and watch your readiness score change—while your actual physiology has not changed at all. That is a damning indictment of black-box scoring.

There is another problem these scores conceal. The main limiter for most endurance athletes on any given day is probably muscular soreness. No wearable on the market today can measure muscular soreness. So compound scores hide the limitations of the technology behind an illusion of comprehensiveness.

The better approach is to break it down. Look at individual components—especially resting HRV and resting heart rate—as objective data points. Use your training load and life context as the behavioral lens. And always start with the subjective question: How do you feel?

Why Is HRV a Response to Stress, Not a Predictor of Performance?

This is perhaps the single most important concept, and the one I find myself explaining to athletes constantly.

A low HRV does not mean you cannot execute your workout. It means your capacity to assimilate that workout—to actually get better from it—may be compromised. Research on HRV-guided training shows that the HRV-guided group does not necessarily perform better on any given session. They improve more over time, because they are not adding stress to a body that is already stressed.

If you have a low HRV on race day, it does not matter—you are racing. You will recover afterward. But during a training block, piling on intensity when your nervous system is already suppressed means you can execute the session but will not extract the adaptation from it. It is essentially wasted work.

And here is the nuance that trips people up: some athletes think that if they train hard and do not see an HRV suppression the next morning, they did not train hard enough. Marco was emphatic that this is completely wrong. If you see a suppression, you went beyond your capacity to assimilate that stimulus. The fittest athletes have the most stable HRV data. They rarely show suppressions from training. Their bodies bounce back quickly, which is exactly why they can handle high training loads. Stable data is the goal, not higher numbers.

What Should You Do When the Data Says Red but You Feel Green?

This is the question I hear most from athletes. Marco’s first response is always the same: How do you feel?

When athletes come to him with HRV concerns, often the subjective part is not even part of the conversation. They have outsourced their self-awareness to the device. But the tool does not know what you know about yourself.

Marco’s practical approach: if the data shows a suppression but the athlete feels good, do the session and watch what happens. Typically, if it was nothing—a bad meal, a glass of wine, a restless night—the data normalizes within a day or two. He gives it two to three days before considering any adjustment, and almost every time, things renormalize on their own.

If the athlete feels bad and the data is also suppressed, that is when action is warranted. The data is confirming what the body already knows.

The key insight is that most of the time when HRV trends negative, it is life happening, not training. Travel, sick kids, seasonal allergies, work stress—these all show up in the data. A well-designed training plan should not put an athlete in a physiological hole on its own. So when the data dips, it is often an invitation for a conversation: “Hey, your numbers have been low for two days. What is going on?” That conversation is where the real coaching happens.

When and How Should You Measure HRV?

Timing

The right time to measure is either first thing in the morning or during sleep. Morning has advantages: you capture the full restorative effect of sleep, and whatever stressors hit you the day before, you are measuring after your body has had its best chance to recover. Nighttime wearable measurements can work too, but they are inherently noisier if sleep is fragmented, and they sample earlier in the recovery window.

Measure at the same time every day. HRV follows a circadian rhythm, and inconsistent timing introduces noise that obscures the signal. Avoid ingesting caffeine before your measurement, and exercise after measuring, not before.

Body Position

Marco strongly recommends measuring while sitting up rather than lying down. When you change from lying to sitting, the body has to respond—redistributing blood volume, adjusting pressure so you do not faint. This orthostatic stress amplifies the signal. Changes that might be invisible while lying down become obvious when upright.

A concrete example: if you are slightly sick, your nighttime heart rate might go from 48 to 50—a change so small it is indistinguishable from normal variation. But sit up that same morning, and instead of 51 it is 63. The orthostatic stressor reveals what lying down conceals. There was even a recent study where athletes went to altitude and showed no change in their nighttime HRV, but when they measured standing in the morning, the suppression was dramatic. Convenience does not always equal useful data.

Devices

In a medical setting, HRV is measured using an electrocardiogram (ECG), which detects the electrical activity of the heart directly. HRV is calculated from the time in milliseconds between successive R-peaks in the cardiac cycle (R-R intervals). This is the gold standard.

Chest straps are the most practical ECG-based tool for athletes. They use two electrodes on the sternum and can measure R-R intervals with high accuracy during varying exercise intensities. Some models, such as the Polar H10, have published validation data showing strong correlation with medical-grade ECG. Not all chest straps that measure heart rate accurately can also measure HRV accurately—check for published validation before relying on one.

Smartwatches and rings use photoplethysmography (PPG)—infrared light that detects blood volume changes in blood vessels to estimate heart activity. This is an indirect measurement. PPG can produce good HRV estimates during sleep or a short morning measurement when there is minimal movement, and the correlation with ECG is generally high under those conditions. However, PPG is sensitive to motion, can be affected by arterial stiffness and age, and is the least accurate method during activity. Not all optical sensors are created equal. Whatever device you use, make sure it has published validation data against an ECG.

How Is HRV Calculated?

Most consumer HRV products use RMSSD (root mean square of successive differences) as their calculation method. This involves measuring the time difference between each pair of successive heartbeats in milliseconds, squaring each value, computing the mean, and taking the square root. RMSSD is the standard because it measures HRV accurately without being affected by breathing rate, which itself influences heart rate even at rest.

One important technical note: higher mean heart rates are naturally associated with lower HRV. If your resting heart rate changes—from improved fitness, illness, or any other reason—your HRV will shift as a downstream effect, independent of any change in autonomic function. Always consider mean heart rate alongside HRV when interpreting trends.

Is Higher HRV Always Better?

No. This is a widespread misconception.

HRV has a very strong genetic component. Even among people of the same age, sex, fitness level, and training background, absolute HRV values are all over the map. You cannot build a meaningful frame of reference from population data. The only useful baseline is your own, built over one to two months of consistent measurement.

Once you have that baseline, the goal is stability within your normal range—not climbing above it. Abnormally high HRV, especially paired with a suppressed heart rate, can actually indicate fatigue, not fitness. It is similar to what athletes notice during exercise: when you cannot get your heart rate up to where you expect it during a workout, that usually signals fatigue, not a breakthrough. The same logic applies to resting physiology.

Much of the HRV increase people see as beginners get fitter is actually a downstream effect of resting heart rate dropping. A lower resting heart rate creates more room for beat-to-beat variation. The HRV change is largely accounted for by the heart rate change—it is not an independent signal of fitness.

There is no single HRV score that is “healthy” for everyone. Population data shows wide ranges by age and sex, with women generally showing higher HRV than men and values declining with age across both sexes. But the standard deviations within each group are large. Your individual baseline is the only number that matters for guiding your training decisions.

What Is Parasympathetic Saturation?

This matters for our community, because many Uphill Athlete clients train at high volumes and have very high fitness levels.

Parasympathetic saturation means HRV stops tracking parasympathetic activity accurately because the receptors in the heart are maxed out. Marco’s analogy: think of a glass of water. If the level never reaches the top, you can measure it perfectly. But once the glass is full, you can keep pouring—the level stays the same. You have lost the signal.

This tends to happen in people with very low resting heart rates who train at high volumes, particularly if they measure lying down. The fix is the same: measure sitting or standing. The orthostatic stress brings the signal back below the saturation ceiling, restoring its sensitivity.

If your resting heart rate is very low, you are training hard, and your HRV has not budged in weeks, saturation is a likely explanation.

Why Does Stability Matter More Than Magnitude?

Beyond your daily HRV score and your weekly average, there is another metric worth watching: the coefficient of variation, or CV. This measures how much your HRV jumps around from day to day within a given week.

A weekly average of 100 milliseconds could mean every day was right around 100, or it could mean you bounced between 80 and 120. The average looks the same but the story is very different. High CV—a lot of jumping around—typically reflects a body that is being repeatedly stressed and recovering incompletely. One day suppressed from a hard session, the next rebounding after rest, then hammered again.

Low CV—stable data within your normal range—means you are absorbing stress and bouncing back consistently. That is the signal of an athlete whose training is well-calibrated to their recovery capacity. Like everything with HRV, compare your CV to your own history, not anyone else’s.

Can HRV Detect Illness?

During the pandemic, there was hype about HRV “predicting” illness. Marco was careful with this language. HRV can detect illness—it can reflect a physiological response to an infection already present in your body, even before you have noticeable symptoms. But it is not predicting the future. Your body is already fighting something; you just have not noticed yet.

In most cases, the data simply confirms what you already feel. The value of the objective measurement is that it can occasionally catch something you might have dismissed, or give you permission to take the rest day you were waffling about. But it is not a crystal ball.

Why Can’t HRV Replace a Training Plan?

One of the most important things Marco said came when I asked about using HRV to manage chronic load accumulation across a multi-week training block.

His answer confirmed my experience: HRV is often a lagging indicator at this timescale. By the time you see a sustained suppression over weeks, you have probably already dug yourself into a hole. The data did not warn you in advance; it is confirming the damage after the fact.

This means HRV can never replace a well-structured training plan. Athletes who train based solely on wearable signals—going hard whenever the device says green, resting only when it says red—are not training. They are reacting. And that approach will eventually break them.

HRV works as a feedback mechanism for small, daily adjustments within a thoughtful periodized plan. Maybe today’s hard session gets pushed to tomorrow. Maybe a recovery week gets extended by a couple of days. But the architecture of the training—the progression, the deloads, the taper—has to come from the coach’s understanding of the athlete and the principles of training science. You need to deload before the data tells you to.

What Is the Right Hierarchy for Making Training Decisions?

I asked Marco: if you were programming the logic behind a coaching intelligence system, what is the first question it should ask before it even looks at HRV data?

His answer was immediate: How do you feel?

That is the hierarchy:

1. Subjective perception. How does the athlete feel today?
2. Context. What is happening in their life? Where are they in their training block? What are the upcoming goals?
3. HRV and resting heart rate. The objective physiological signals.
4. Training load metrics. The quantitative record of what has been done.

HRV is not at the top of the list. But it earns its place as a valuable, objective data point that can start conversations, confirm what we are seeing subjectively, and occasionally flag something we might have missed. It can also do something underappreciated: provide confidence. When an athlete is feeling good, the training is going well, and the HRV data is stable within their normal range, that is a genuinely reassuring signal that the process is working.

Data is an input into judgment, not a replacement for judgment. That is the principle we coach by at Uphill Athlete, and after spending time with Marco Altini, I am more convinced than ever that it is the right one.

This article is based on a conversation between Steve House and Dr. Marco Altini, a lot of reading by Uphill Athlete coaches, as well as many discussions.

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