Underfueling, Overreaching, and Wearable Signals: What Trends Can—and Cannot—Tell You

If your HRV falls, resting heart rate rises, sleep becomes less settled, and familiar workouts feel harder, your wearable is showing strain. It is not showing the cause.

Low energy availability (LEA), a recent increase in training, illness, travel, psychological stress, poor sleep, medication changes, and several medical conditions can produce overlapping signals. A wearable can help you notice a change from your baseline, but it cannot diagnose relative energy deficiency in sport (RED-S) or reliably distinguish underfueling from overreaching.

Why the Signals Overlap

LEA occurs when dietary energy is insufficient for both exercise and normal physiological function. RED-S is the broader syndrome of health and performance effects that can result from problematic LEA, and it can affect athletes of any sex.¹

Functional overreaching is a short period of increased training stress followed by recovery and adaptation. Non-functional overreaching and overtraining syndrome involve longer-lasting performance problems, but there is no single accepted biomarker that confirms either condition.²

That is why HRV, resting heart rate, sleep, soreness, mood, and performance should be interpreted as context—not labels. A systematic review found that resting HRV changes associated with reduced performance were generally small and that additional measures of training tolerance were needed.³

What the RED-S Evidence Does—and Does Not—Show

A systematic review and meta-analysis reported LEA in 2,737 of 6,118 athletes and estimated that 460 of 730 athletes across eight studies were at risk of RED-S.⁴ Those pooled figures came from different sports, populations, and screening methods. Being classified as “at risk” is not the same as receiving a diagnosis.

The IOC REDs Clinical Assessment Tool version 2 (CAT2) combines history, symptoms, examination, and, when appropriate, laboratory or imaging information. The IOC states that it should be used by trained clinicians as part of a broader assessment, not as a stand-alone questionnaire or wearable score.¹⁵

In a cohort of more than 200 elite athletes, those classified in the orange category had higher prospective bone-stress-injury odds than athletes in the green category (OR 7.71, 95% CI 1.26–39.83). The wide interval and incomplete radiological confirmation of prospective injuries limit the precision of that estimate, and the authors called for further validation.⁶

How to Read Wearable Trends Responsibly

Start with four questions rather than a diagnosis:

1. Is the change real? Compare several readings with your own longer-term baseline, measurement conditions, and normal day-to-day variation.
2. Did training change? Note abrupt increases in volume, intensity, competition, or consecutive hard sessions.
3. Did fueling or life context change? Consider reduced appetite, missed meals, travel, work stress, sleep disruption, or illness without assuming that one factor is responsible.
4. Are symptoms or performance changing too? A repeated drop in expected performance, unusual fatigue, mood changes, recurrent injury, or endocrine symptoms deserves more attention than an isolated device score.

Use the observation to decide what information to gather and whether to seek help—not to assign yourself to a diagnostic category.

Observation	Possible explanations	A cautious next step
Wearable change after a clear training increase	Normal short-term fatigue, overreaching, illness, or another stressor	Reduce or replace a hard session if needed; review symptoms and performance before resuming progression
Wearable change alongside missed meals, appetite changes, weight change, or repeated low-intake days	LEA is possible, but the signal is not specific	Discuss energy needs with a sports dietitian or clinician, especially if symptoms or performance are also changing
Training and fueling both changed	Multiple stressors may be contributing	Avoid adding load while gathering a fuller history; seek professional assessment when concerns persist or red flags are present
One unusual reading without symptoms	Measurement noise or normal variation	Recheck under similar conditions and avoid changing a whole program from one value

What Short-Term Studies Tell Us About Wearables

In a randomized study of 20 cyclists, a single day of LEA produced different sleep and recovery responses depending on whether the deficit came from diet or exercise. Overnight HRV did not differ clearly between conditions.⁷ That result reinforces a limitation: the absence of an HRV warning does not rule out LEA, and a change in HRV does not identify it.

Fuel needs also vary substantially with training demands. A study of 27 cross-country skiers found different reported energy intake across training and competition days.⁸ Those group averages are not calorie targets for an individual; they illustrate why a static intake assumption can miss changes in workload.

A study of 10 male collegiate soccer players examined within-day energy balance and metabolic markers, but the relationships were inconclusive.⁹ It supports further research into meal timing, not a diagnostic rule based on eating windows.

Safer Responses to Concerning Trends

When workload has risen and recovery feels inadequate, a temporary reduction in volume or intensity can be reasonable. When intake has become inconsistent or symptoms suggest LEA, restoring regular meals and training-day fueling with guidance from a qualified sports dietitian is safer than relying on a generic carbohydrate rule.

Neither response should become a home diagnostic experiment. Improvement after rest or increased intake does not prove what caused the original pattern, and lack of improvement should not be the only trigger for medical care.

Seek prompt assessment from a sports medicine clinician when you have localized or recurrent bone pain, a suspected bone stress injury, menstrual disruption, low libido or other endocrine changes, repeated illness or injury, marked weight change, or persistent fatigue and performance decline. Chest pain or pressure, fainting, severe shortness of breath, or other acute symptoms warrant urgent medical care.

Using WHOOP, Oura, Garmin, and Apple Watch Data

Different devices use different sensors, sampling schedules, and proprietary scores. Focus on trends within the same device rather than comparing an absolute HRV or readiness score with someone else’s.

A meta-analysis found that weekly averaged heart-rate-derived indices distinguished functionally overreached athletes better than isolated values. Those were group-level findings about training status, not a test for LEA or RED-S.¹⁰

Useful habits include:

• Measure under reasonably consistent conditions.
• Review repeated trends alongside sleep, symptoms, performance, and recent training.
• Treat estimated calories and readiness scores as estimates.
• Check whether a device or app changed its algorithm or measurement method.
• Bring the trend history to a clinician as supporting context, not as a conclusion.

What SensAI Can Help With

SensAI combines personal context from connected health data with LLM-powered conversational coaching. Apple Watch data connects directly through HealthKit; Garmin, Oura, and WHOOP data can flow through HealthKit when those services write supported data there.

Raw HealthKit data stays on-device. Aggregated recovery metrics—such as HRV trends, sleep quality, and workout summaries—can be used server-side to support coaching. SensAI can generate daily recovery summaries and regenerate a weekly program from actual performance and recovery context. It does not diagnose RED-S, confirm LEA, or replace a clinician or sports dietitian.

Frequently Asked Questions

Can HRV detect low energy availability?

No. HRV can change with many stressors, and short-term LEA does not always produce a distinct HRV change.³⁷ Interpret it with symptoms, performance, training, sleep, and clinical context.

How can I tell whether I am underfueling or overreaching?

Wearable data alone cannot make that distinction. Review recent changes in training and eating, then involve a qualified clinician or sports dietitian when symptoms persist, performance continues to decline, or RED-S red flags are present.

Should I change carbohydrate intake when HRV drops?

Not because of HRV alone. Regular training-day fueling matters, but an isolated wearable change does not establish a carbohydrate deficit. A sports dietitian can help assess total energy needs, meal timing, and sport-specific demands.

What should I do with one low readiness score?

Consider how you feel and what changed, then look for a repeated pattern. One score may justify an easier day when symptoms support that choice, but it should not trigger a diagnosis or a rigid protocol.

The useful question is not “Which condition did my wearable find?” It is “What changed, what other evidence do I have, and do these symptoms need professional assessment?”

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References

Footnotes

1. Mountjoy M, Ackerman KE, Bailey DM, et al. “2023 International Olympic Committee’s (IOC) Consensus Statement on Relative Energy Deficiency in Sport (REDs).” British Journal of Sports Medicine, 2023. https://pubmed.ncbi.nlm.nih.gov/37752011/ ↩ ↩²

2. Meeusen R, Duclos M, Foster C, et al. “Prevention, Diagnosis and Treatment of the Overtraining Syndrome: Joint Consensus Statement of the European College of Sport Science (ECSS) and the American College of Sports Medicine (ACSM).” Medicine & Science in Sports & Exercise, 2013. https://pubmed.ncbi.nlm.nih.gov/23247672/ ↩

3. Bellenger CR, Fuller JT, Thomson RL, et al. “Monitoring Athletic Training Status Through Autonomic Heart Rate Regulation: A Systematic Review and Meta-analysis.” Sports Medicine, 2016. https://pubmed.ncbi.nlm.nih.gov/26888648/ ↩ ↩²

4. Gallant TL, Ong LF, Wong L, et al. “Low Energy Availability and Relative Energy Deficiency in Sport: A Systematic Review and Meta-analysis.” Sports Medicine, 2025. https://pubmed.ncbi.nlm.nih.gov/39485653/ ↩

5. Stellingwerff T, Mountjoy M, McCluskey WT, et al. “Review of the Scientific Rationale, Development and Validation of the International Olympic Committee Relative Energy Deficiency in Sport Clinical Assessment Tool: V.2 (IOC REDs CAT2)—by a Subgroup of the IOC Consensus on REDs.” British Journal of Sports Medicine, 2023. https://pubmed.ncbi.nlm.nih.gov/37752002/ ↩

6. Heikura IA, McCluskey WTP, Tsai MC, et al. “Application of the IOC Relative Energy Deficiency in Sport (REDs) Clinical Assessment Tool Version 2 (CAT2) Across 200+ Elite Athletes.” British Journal of Sports Medicine, 2024. https://pubmed.ncbi.nlm.nih.gov/39164063/ ↩

7. Smith ES, Kuikman M, Rusell S, et al. “Twenty-Four-Hour Low Energy Availability Induced by Diet or Exercise Exhibits Divergent Influences on Sleep and Recovery Indices Among Female and Male Cyclists.” Medicine & Science in Sports & Exercise, 2025. https://pubmed.ncbi.nlm.nih.gov/40523229/ ↩ ↩²

8. Bushmanova EA, Lyudinina AY, Bojko ER. “The Prevalence of Low Energy Availability in Cross-Country Skiers During the Annual Cycle.” Nutrients, 2024. https://pubmed.ncbi.nlm.nih.gov/39064722/ ↩

9. Lee S, Moto K, Han S, Oh T, Taguchi M. “Within-Day Energy Balance and Metabolic Suppression in Male Collegiate Soccer Players.” Nutrients, 2021. https://pubmed.ncbi.nlm.nih.gov/34444803/ ↩

10. Manresa-Rocamora A, Flatt AA, Casanova-Lizón A, et al. “Heart Rate-Based Indices to Detect Parasympathetic Hyperactivity in Functionally Overreached Athletes: A Meta-analysis.” Scandinavian Journal of Medicine & Science in Sports, 2021. https://pubmed.ncbi.nlm.nih.gov/33533045/ ↩