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About this tool
Smooth daily weigh-ins into a 7-day moving average and an exponential trend line, with the weekly rate and implied calorie balance.
A rolling weigh-in average replaces a single noisy scale reading with the average of your last several days, which is the only way to see a change of 0.5 kg a week through daily swings of 1-2 kg. This tool computes a simple moving average over a window you choose, an exponentially weighted trend using the Hacker's Diet smoothing factor of 0.1, and a least-squares weekly rate with an R-squared fit. It then converts that rate into an implied energy balance at about 7,700 kcal per kilogram.
Open Weigh-In Rolling Average Tool on AltFTool — it loads instantly in your browser.
Enter the values you already know.
Fine-tune the options to match your scenario.
Read the result and use it in your planning or reporting.
A window average for a plain readable number and an exponential trend that reacts faster to a genuine change of direction.
Reports the standard deviation of readings around the trend, so you know how far off the line is normal for you.
Flags when the window is incomplete or when the straight-line fit explains too little of the variation to trust yet.
Seven days is the usual choice because it covers a full weekly routine — weekday meals, weekend eating, training days and rest days all appear exactly once. Shorter windows react faster but stay noisy; longer windows are smoother but lag a real change by more days.
Because a single reading includes fluid, glycogen and gut contents, which move by a kilogram or more overnight. The moving average cancels most of that out. If your latest reading is further from the trend than your usual daily noise, it is almost certainly fluid.
A moving average gives every reading in the window equal weight and drops the oldest one entirely. An exponential trend weights recent readings more heavily and never fully forgets older ones — with a smoothing factor of 0.1 each new reading moves the line one tenth of the way towards itself.
At least a week, and ideally two to three. With daily noise of around 0.5 kg and a target rate of 0.5 kg per week, a few days of data cannot separate signal from noise — which is why the R-squared figure here stays low until the log is long enough.
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