Mean Absolute Percentage Error (MAPE)
MAPE is the standard metric for measuring how far an app's predicted calorie value diverges from a known reference value, expressed as a percentage.
Mean Absolute Percentage Error (MAPE) is the average of the absolute differences between predicted and reference values, expressed as a percentage of the reference. For calorie tracking app accuracy testing, the formula is:
MAPE = mean(|predicted_kcal − reference_kcal| / reference_kcal) × 100
A 5% MAPE means an app’s calorie estimates are on average within ±5% of the weighed reference. We use MAPE as the headline accuracy metric on every review and ranked list because it is interpretable, symmetric in error direction, and comparable across apps that use different food databases.
Why MAPE and not raw error
Raw error (kcal off) penalizes large meals more than small ones. Percentage error normalizes for portion size. MAPE is the metric used in dietary-assessment validation literature (Schoeller 1995; Subar 2015) — using it here makes our numbers comparable to peer-reviewed work.
Known limits
MAPE punishes consistent over- and under-estimation equally. An app that systematically reports 10% high on every meal has the same MAPE as an app that randomly varies ±10%. We report MAPE alongside the directional bias when the bias is non-trivial.