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WP2 · Adaptive TDEEPublished · April 1, 2026

Adaptive TDEE with periodic recalculation

An energy estimate that combines logged intake and weight trend.

The problem with static TDEE

The classic TDEE calculation (BMR × activity multiplier) is a starting point — not a fixed truth. Everyone has a different activity level, and metabolic adaptation causes energy output drift during cuts (Trexler et al. 2014).

With sufficiently complete data, Vytrix estimates energy use from average logged intake and change in a smoothed weight trend. The outcome remains an estimate and is not an automatic guarantee of a specific result.

How it works

Vytrix estimates energy use from average logged intake and the change in a smoothed weight trend. In the start-up period, this outcome is combined with a formula estimate; the weighting increases as more data is available.

The chosen boundaries, blend and energy densities are Vytrix implementation choices, not a clinically validated protocol. Short-term changes in fluid and glycogen can noticeably affect the outcome.

In the Vytrix app

Look at your trend over time

This weight overview shows how the app displays measurements over several weeks. Together with your nutrition logs, this gives context to an energy estimate.

Real app image · example data

Trexler curve and metabolic adaptation

During weight loss, energy expenditure may change; the extent varies per person and context. Vytrix uses logs to periodically update its energy estimate, but this does not guarantee a specific waste outcome.

Read further and apply

TDEE-drift during a 12-week cut (illustrative)

A static BMR×activity number remains 2700 kcal. The actual energy output (rolling measurement from kcal intake and weight progression) gradually drops to ~2350 kcal — approximately 13% metabolic adaptation, well within the 5–15% range reported by Trexler et al. (2014).

230025002700week 0week 4week 8week 12kcal/day
Formula-TDEE (static)Vytrix Adaptive TDEE
Curve is illustrative; absolute values ​​depend on individual baseline values. Methodology and source: Trexler et al. 2014, Müller et al. 2015.