My phone's health app tells me I slept 7 hours and 23 minutes last night with a sleep quality rating of "Good." My subjective experience: restless, light, woke twice, felt exhausted upon waking. This discrepancy illustrates both the promise and limitations of consumer sleep tracking technology. The data is useful for trends over time; the absolute numbers are often misleading. Understanding what these tools can and cannot do helps you use them appropriately. Sleep tracking apps fall into three categories: phone-based (using accelerometer to detect movement), wearable (wrist bands, watches, rings), and external devices (under-mattress sensors, bedside monitors). Each has different accuracy profiles. Phone-based tracking is the least accurate, as it only detects major movement when the phone is nearby. Wearables provide reasonable accuracy for sleep-wake detection and trend tracking. Under-mattress sensors can approximate sleep stages but still lack the precision of clinical polysomnography. Sleep stage estimation by consumer devices is the most misleading feature. These devices use movement patterns and heart rate variability to estimate whether you're in light, deep, or REM sleep. Validation studies show that consumer devices correctly identify sleep stages only 50-60% of the time—barely better than chance. Deep sleep estimates are particularly unreliable. You shouldn't make decisions based on whether you got "enough" deep sleep according to your device; the margin of error is too large. The useful function of sleep trackers is identifying trends across multiple nights. If your sleep quality consistently degrades when you drink alcohol, sleep with a partner who snores, or have late-afternoon caffeine, the trend data reveals these patterns. If your sleep efficiency drops after travel or during particularly stressful periods, the tracker documents this. This longitudinal data provides actionable information that single-night assessments cannot. The potential harm from sleep trackers comes from two sources. First, "orthosomnia"—anxiety about achieving "optimal" sleep numbers that actually worsens sleep by creating performance pressure around sleep itself. If checking your sleep score causes anxiety that prevents you from sleeping, the tracker is counterproductive. Second, misdiagnosis risk: someone with sleep apnea might interpret poor sleep quality as insufficient sleep hygiene and not seek appropriate medical evaluation. Heart rate variability (HRV) tracking during sleep may be the most useful consumer metric. HRV reflects autonomic nervous system balance; higher HRV generally indicates better recovery and stress resilience. Tracking your nightly HRV over time reveals whether you're recovering well from training, managing stress effectively, or approaching illness before symptoms appear. A sudden HRV drop often precedes getting sick by a day or two, providing useful warning. The practical recommendation: use sleep trackers for trend data and interesting background information, not as authoritative assessments of your sleep quality. Track subjective morning alertness alongside tracker data and see if correlations exist. If your tracker consistently shows "good" sleep but you feel terrible, trust your subjective experience over the device. These tools are best viewed as rough guides rather than diagnostic instruments.