The female VO2max problem: why your Garmin number may not reflect your fitness

You know how to run well. A week of difficult training and the Garmin VO2max number climbs. Then it drops in the cold, or after a hard block, or for no obvious reason at all. If a lab test produces an entirely different figure, the question is why.

VO2max estimates from wrist devices are based on algorithms built on exercise physiology research that, for many years, predominantly used male participants. That imbalance matters because the accuracy differences are real and can affect how female runners interpret their fitness data.

The algorithm’s blind spot

Wearables do not measure VO2max directly. Instead, the Firstbeat algorithm that powers Garmin’s estimate analyses the relationship between heart rate and running pace during qualifying sessions. It selects 20-30-second windows where heart rate is above approximately 70 per cent of maximum and movement is steady, then extrapolates from those submaximal data points to estimate oxygen uptake at full effort.

The problem starts with the training data behind the algorithm. According to a validation study by Wiecha et al. (2023) involving 5,260 endurance athletes, 84.76 per cent were men, reflecting a well-documented historical pattern of underrepresentation of women in exercise physiology research.

Why female physiology can confuse the algorithm

Women tend to have lower average VO2max values than men due to differences in haemoglobin concentration, body composition, and cardiovascular physiology. Beyond that, factors such as stroke volume, heart rate response, and hormonal fluctuations across the menstrual cycle may affect the physiological signals the algorithm uses to estimate aerobic capacity. The relationship between pace, heart rate, and fitness may therefore be more variable than the prediction model assumes. However, direct evidence linking menstrual cycle phase to Garmin VO2max error is limited, and the wording should remain cautious.

The directional bias

Research has identified sex differences in the direction of VO2max miscalculation. A 2017 study using the Garmin Forerunner found that the predicted VO2max underestimated values for women and overestimated them for men. Polar’s V800 showed the opposite pattern: overestimation for women, underestimation for men. Different algorithms, samples, and testing conditions can all produce directional differences, and the magnitude and consistency of any sex-specific bias vary across devices and generations.

What does appear likely is that certain assumptions built into these algorithms about how heart rate relates to pace, how body composition affects aerobic capacity, and what a normal pace-to-HR curve looks like may not hold equally across sexes. This is a possible explanation rather than a confirmed mechanism.

The heart rate measurement problem

Behind the algorithm lies the optical heart rate sensor, and that is where physics comes in.

Optical sensors measure changes in blood flow under the skin using light. An American College of Cardiology press release summarising research presented at ACC.17 reported wrist device error margins ranging approximately ±15 to ±34 beats per minute under the specific devices and conditions tested. That is not a universal figure for all wrist sensors, but it illustrates how much input error the VO2max calculation can work with. Firstbeat’s own validation reports approximately 5 per cent mean absolute error when paired with a chest strap; wrist-only heart rate raises that to 5-8 ml·kg⁻¹·min⁻¹.

Skin tone is a further variable. Some studies have found higher margins of error in optical heart rate readings for individuals with darker skin tones. However, findings are mixed, and newer multi-wavelength sensors have reduced but not eliminated the gap.

What the validation studies actually show

When Garmin’s VO2max algorithm is tested against laboratory spirometry, the picture is mixed. In a study of the Garmin Forerunner 245 by Engel et al. (2025), the smartwatch underestimated VO2max on average across athletes, with mean differences of -4.73 ml·min⁻¹·kg⁻¹ and -4.05 ml·min⁻¹·kg⁻¹ for the first and second qualifying runs. Subgroup analysis revealed substantially better accuracy in moderately trained athletes (mean absolute percentage error of 4.1-2.8 per cent) than in highly trained athletes, where the watch underestimated by 6.3 ml·min⁻¹·kg⁻¹ with a mean absolute percentage error of 10.4-9.4 per cent.

For female runners tracking VO2max trend to monitor endurance progress, the practical implication is to weigh training pace, race performances, and perceived effort alongside the watch figure rather than relying on the absolute number alone.

Practical guidance: how to use your number

• Treat it as a trend, not a fact. Consistent increases over weeks and months indicate aerobic improvement. A sustained drop signals something has changed.
• Use a chest strap for important qualifying sessions. Firstbeat’s validation places accuracy within approximately 5 per cent of laboratory spirometry under controlled conditions when using chest-strap heart rate.
• Set your actual maximum heart rate. Garmin defaults to the 220 minus age formula, which is typically wrong by 10-15 beats for trained athletes. A 15 bpm error in maximum heart rate produces a 7-9 per cent error in the VO2max output.
• Understand device-specific patterns. If your device consistently underestimates your race performance or perceived fitness, note the gap.
• Get lab tested for consequential decisions. If VO2max will inform a significant training or racing decision, laboratory respiratory gas analysis is the only reliable figure.

The bigger picture

Women’s participation in endurance sport has grown substantially over recent decades, increasing the need for reliable fitness measurement. Wearable VO2max algorithms were developed in an era when women were underrepresented in exercise physiology research. More recent validation studies suggest the sex discrepancy in algorithm accuracy may be narrowing, though independent evidence across current device generations remains thin.

Until that evidence base matures, VO2max estimates are best treated as one measure among several, alongside race performances, training pace at given heart rates, and perceived effort.

Quick answers

Why does my Garmin VO2max go up and down week to week?
The Firstbeat algorithm reads the relationship between heart rate and running pace during qualifying sessions. Heat, fatigue, poor sleep, a loose strap, and wrist sensor dropout all elevate heart rate relative to pace, which the algorithm reads as reduced fitness. The number reflects input data quality as much as actual fitness change. A single qualifying run with a chest strap in consistent conditions is more informative than several wrist-only readings taken across varying weather.

Is Garmin VO2max less accurate for women?
Validation studies show directional biases that differ between device brands. Some studies find Garmin underestimates VO2max in women while overestimating in men; Polar has shown the opposite pattern on certain devices. The algorithms were developed on datasets that were heavily male-skewed, which may contribute to sex-specific error patterns. However, the size and consistency of the effect vary by device generation and athlete fitness level.

Does using a chest strap improve Garmin VO2max accuracy?
Yes, meaningfully. Firstbeat’s own validation reports a mean absolute error of approximately 5 per cent when paired with a chest strap. Wrist-only heart rate raises that error to 5-8 ml·kg⁻¹·min⁻¹.

How important is setting the correct maximum heart rate in Garmin?
Significant. Firstbeat’s data show that a 15 bpm error in maximum heart rate results in a 7-9 per cent error in VO2max. The default 220 minus age formula is typically off by 10-15 beats per minute for trained athletes. Setting a measured maximum heart rate from a ramp test or a verified hard effort materially improves the estimate.

Does the menstrual cycle affect Garmin VO2max readings?
Plausibly, though direct evidence is limited. Progesterone in the luteal phase elevates heart rate at a given pace, which the algorithm could interpret as reduced fitness. HRV changes and elevated resting heart rate during the luteal phase may also affect recovery scores that feed into the broader training load picture. Tracking VO2max alongside cycle phase over several months is the best way to identify whether a personal pattern exists.

This article is part of the site’s female athlete tech coverage. For tested product recommendations across wearables, recovery trackers, and heart rate monitors, see the best wearables for female endurance athletes.

---

Explore the full resource library

This site covers endurance sport technology across a range of dedicated reference sections. Each one collects the most relevant articles, tests, and analysis on its topic in one place.

Brand and product guides

• Amazfit — the full Amazfit range from Balance to Cheetah to T-Rex, accuracy tests, HYROX partnership, and Zepp Health analysis
• Apple Watch for Sport — athlete-first coverage of Apple Watch across running, cycling, and triathlon
• COROS — watches, features, and firmware across the full COROS range
• Garmin — the company, the platform and the full range, and the starting point for choosing across every Garmin product line
• Garmin Edge — bike computers from entry-level navigation to flagship endurance and mountain biking
• Garmin Fenix — every model, feature, and firmware development for Garmin's flagship outdoor watch
• Garmin Forerunner — the full Forerunner line covered from entry level to triathlon flagship
• Garmin Instinct — rugged GPS watches for endurance and adventure athletes
• Garmin Features Explained — how Garmin's metrics work, from Training Load and Body Battery to Race Predictor and HRV Status
• Polar — watches, sensors, Polar Flow and training science across the full Polar range
• Suunto — Race, Vertical, Run and the SuuntoPlus ecosystem
• Strava — features, privacy, segments, and how Strava fits into a serious training setup
• Wahoo — KICKR trainers, ELEMNT bike computers, and the Wahoo ecosystem
• WHOOP — strain, recovery, sleep and the full WHOOP ecosystem

Sport and topic guides

• Running Watches — how to choose by discipline: road racing, trail, track, beginner, and multisport
• Triathlon and Multisport Technology — watches, sensors, and race-day tools for swimmers, cyclists, and runners
• HYROX — training science, race analysis, and technology for the functional fitness race format
• parkrun — technology, training, and performance for the weekly 5K
• Hiking Technology — navigation, safety, and trail tech for walkers and hikers
• Heart Rate Monitoring — optical sensors, chest straps, accuracy comparisons, and how to set training zones
• GPS Accuracy — how satellite systems perform across brands, terrains, and conditions
• Recovery Trackers — WHOOP, Oura, and the science of readiness scoring
• Female Athlete Tech — wearables, physiology, and performance for female endurance athletes, covering cycle-synced training, RED-S, HR accuracy, and VO2max
• Sports Science — peer-reviewed research on HRV, VO2max, lactate threshold, running power, wearable accuracy, and supplementation
• Testing Methodology — how this site tests GPS accuracy, heart rate, battery life, and other performance claims

Content series

• Release Radar — confirmed launches, leaks, and rumours across Garmin, Apple, COROS, Polar, Suunto, and Wahoo
• Deep Dive Feature Files — weekly firmware feature updates across all brands (bug fixes excluded)
• Fix Files — weekly firmware bug fix tracking across all brands

Last Updated on 24 July 2026 by the5krunner