1RM Calculator — Estimate Your One-Rep Max

What Is a One-Rep Max (1RM)?

Your one-rep max (1RM) is the heaviest weight you can lift for a single repetition with proper form. It's the most fundamental measure of absolute strength and serves as the foundation for nearly every serious training program.

Knowing your 1RM lets you calculate training percentages. Most programs prescribe loads as a percentage of 1RM — for example, "5 sets of 5 at 80%" means using 80% of your max for working sets.

How Is It Calculated?

Rather than attempting a dangerous maximal single, you can estimate your 1RM from a submaximal set. This calculator uses five validated formulas:

• Epley (1985): weight × (1 + reps / 30) — the most widely used formula, reliable for 1-15 reps.
• Brzycki (1993): weight × 36 / (37 - reps) — produces slightly conservative estimates, preferred by many coaches.
• Lombardi (1989): weight × reps^0.1 — a power-law model that works well across rep ranges.
• Mayhew et al. (1992): weight × 100 / (52.2 + 41.9 × e^(-0.055 × reps)) — exponential model validated across multiple populations.
• Wathen (1994): weight × 100 / (48.8 + 53.8 × e^(-0.075 × reps)) — often the most accurate for bench press and squat.

We average all five for the most reliable estimate. For best accuracy, use a set of 3-5 reps performed to or near failure.

Using Training Percentages

Once you know your 1RM, you can program training loads for any goal. The percentage-based training table above maps each percentage to its typical rep range and training outcome:

• 90-100% (1-3 reps): Maximal strength and power. Used in peaking phases and powerlifting programs.
• 80-85% (3-6 reps): The strength sweet spot. Programs like 5/3/1 and Starting Strength live here.
• 65-75% (8-12 reps): Hypertrophy range. Where most bodybuilding volume accumulates.
• 60% and below (12+ reps): Muscular endurance. Useful for deload weeks and metabolic conditioning.

RepStack uses these exact percentages when generating progressive overload recommendations. Your training percentages update automatically as your e1RM improves.

Which Formula Is Most Accurate?

Research by LeSuer et al. (1997) compared seven prediction equations across 67 trained lifters performing bench press, squat, and deadlift. Key findings:

• The Mayhew and Wathen formulas produced the smallest average prediction errors across all three lifts.
• Epley and Brzycki slightly overpredict at higher rep ranges (8+) but are accurate under 6 reps.
• No single formula was best for every lift or every person.

A separate meta-analysis by Mayhew et al. (1992) found the exponential model (used in the Mayhew formula) correlated at r = 0.98 with actual 1RM across 220 subjects. The practical takeaway: averaging multiple formulas minimizes individual formula bias and gives the most reliable estimate.

Why Does e1RM Matter for Programming?

Estimated 1RM (e1RM) is the single most useful number for tracking strength progress over time. Unlike raw weight or reps alone, e1RM accounts for both — so you can compare sessions even when rep ranges differ.

RepStack calculates your e1RM automatically after every set you log. When your e1RM stops increasing, the AI coach detects the plateau and adjusts your programming — adding reps, bumping weight, or suggesting a deload.

Epley vs Brzycki: Which Is Better?

For practical purposes, the difference is minimal. Epley tends to predict slightly higher at higher rep ranges, while Brzycki is more conservative. Both are within 2-3% of each other for sets under 10 reps.

The key takeaway: consistency matters more than the formula. Pick one formula (or average them) and track trends over time. That's exactly what RepStack does.

Tips for Accurate Estimation

• Use a set of 3-5 reps taken close to failure for best accuracy.
• Higher rep sets (10+) produce less reliable estimates.
• Ensure consistent form — a grinder rep skews the calculation.
• Track your e1RM over weeks, not individual sessions.
• Test with compound lifts (bench, squat, deadlift) — formulas are less validated for isolation exercises.