Science
We publish the rules the app runs.
Flexbound's methodology is versioned data with citations, not prompt text. These pages document each engine: the formula, the evidence grade, and where the estimate stops being trustworthy.
Training
Progressive overload & double progression
How Flexbound decides when you add weight: the rep-target gate, repeating missed prescriptions, and smallest-practical increments.
Read the methodology →Estimated 1RM: the Epley formula and its limits
The exact formula behind every e1RM in the app, why we chose it, and the rep ranges where the estimate is trustworthy.
Read the methodology →RPE and RIR: measuring effort you can log
What reps-in-reserve actually measures, the evidence lifters can estimate it, why every planned set ships with an RIR target, and where self-rated effort breaks down.
Read the methodology →Programming
Nutrition
Adaptive TDEE from your own logs
Mifflin-St Jeor as the starting estimate, then energy-balance math over confirmed intake and weight trend. No AI guessing.
Read the methodology →Protein targets that match the evidence
Where Flexbound’s per-pound protein targets come from, by goal, and why more isn’t automatically better.
Read the methodology →Recovery
Coming to iOS
This math ships in the app.
Every page in this library runs deterministically in Flexbound. The work is versioned, cited, and auditable. Coming to iOS.