EWMA baseline

An exponentially weighted moving average, or EWMA, is a statistical method for tracking a rolling average that gives more weight to recent readings and progressively less weight to older ones, rather than treating every past data point equally. This makes it responsive to genuine recent change while still smoothing out normal day-to-day noise.

Sloane uses an EWMA baseline, built over a trailing 14 to 30 day window, across each signal it reads: heart rate variability, sleep, calendar load, telemetry friction and the rest. The result is a rolling picture of what is normal for that specific person, updated continuously as new data arrives.

This matters because population averages are a poor basis for individual coaching. A resting heart rate, a meeting count or a level of after-hours messaging that is unremarkable for one person may represent a significant change for another. Judging everyone against the same fixed threshold produces both false alarms and missed signals.

By comparing today's reading to a person's own EWMA baseline rather than a fixed number, Sloane can notice when something has genuinely shifted for that individual, even if the absolute numbers would look ordinary out of context. This is the core statistical method underneath Sloane's coaching, applied consistently across every signal it reads.