Which equations are commonly used to estimate 1RM from submaximal lifts?

Which equations are commonly used to estimate 1RM from submaximal lifts?

• A. Brzycki
• B. Epley
• C. Lombardi
• D. All of the above

Answer: (D)

Estimating a true 1RM from submaximal lifting relies on simple models that link how much weight you lift to how many reps you can perform before failure. Several formulas are commonly used for this purpose: Brzycki, Epley, and Lombardi. Each one expresses 1RM as a function of the weight lifted and the number of reps completed, but they make different assumptions about how load and repetitions relate. Brzycki uses a hyperbolic relationship: 1RM = W / (1.0278 − 0.0278 × reps). It tends to be accurate across a typical rep range (about 2–10) and is straightforward to apply. Epley assumes a roughly linear gain in 1RM with each additional rep: 1RM = W × (1 + reps/30). This is simple to use and often matches real 1RM values well for moderate rep sets. Lombardi adopts a power-law approach: 1RM = W × (reps)^0.10. The exponent creates a different curve, which can fit some lifters’ data better, especially at lower rep counts. All of these are widely taught and used because they provide practical, quick estimates from submaximal data. Remember, they’re estimates and carry some error, so the choice of formula can depend on the athlete and the rep range you’re using.

Estimating a true 1RM from submaximal lifting relies on simple models that link how much weight you lift to how many reps you can perform before failure. Several formulas are commonly used for this purpose: Brzycki, Epley, and Lombardi. Each one expresses 1RM as a function of the weight lifted and the number of reps completed, but they make different assumptions about how load and repetitions relate.

Brzycki uses a hyperbolic relationship: 1RM = W / (1.0278 − 0.0278 × reps). It tends to be accurate across a typical rep range (about 2–10) and is straightforward to apply.

Epley assumes a roughly linear gain in 1RM with each additional rep: 1RM = W × (1 + reps/30). This is simple to use and often matches real 1RM values well for moderate rep sets.

Lombardi adopts a power-law approach: 1RM = W × (reps)^0.10. The exponent creates a different curve, which can fit some lifters’ data better, especially at lower rep counts.

All of these are widely taught and used because they provide practical, quick estimates from submaximal data. Remember, they’re estimates and carry some error, so the choice of formula can depend on the athlete and the rep range you’re using.