How to Create a Load-Velocity Profile: Practical Guide

The load-velocity profile (LVP) is the foundation of evidence-based velocity-based training. Without it, VBT is just measuring bar speed without context. With it, you can estimate 1RM on any training day in under 10 minutes, autoregulate load prescription based on daily readiness, and track strength adaptation with more precision than traditional percentage-based methods allow.

A 2017 study by Gonzalez-Badillo et al. showed that individual LVP-based 1RM estimates correlated with actual measured 1RM at r = 0.98 across 77 trained subjects — accuracy comparable to performing an actual 1RM test, but without the fatigue cost. This guide walks through the complete process: equipment selection, testing protocol, regression analysis, and daily use.

What Is a Load-Velocity Profile?

The load-velocity profile is a linear regression line describing the relationship between the load lifted (as % 1RM or kg) and the mean concentric velocity (MCV) produced at that load, when the athlete moves with maximal intentional velocity. The relationship is described by Hill's force-velocity curve: as load increases, velocity decreases in a near-perfectly linear fashion within the 30–100% 1RM range.

Two anchor points define the line:

• V0 (velocity at zero load): The theoretical maximum bar velocity if the load approached zero. Estimated by extending the regression line to the y-axis intercept. Typically 1.2–1.8 m/s for the back squat in trained athletes.
• L0 (load at zero velocity): The theoretical maximum load the athlete could lift, estimated by extending the regression line to the x-axis intercept. Corresponds to theoretical 1RM. Typically within 2–5% of measured 1RM.

The practical output of the LVP is a simple formula: Estimated 1RM = Load (kg) / (1 − (MCV − V0) / V0), or more practically, a regression-based lookup table that converts any measured MCV at a known load into an estimated 1RM on that day.

Equipment and Prerequisites

Building a valid LVP requires:

• Velocity sensor: An IMU-based device or linear position transducer with accuracy of ±0.02–0.05 m/s MCV. Accuracy below this threshold produces regression lines with excessive error that renders 1RM estimation unreliable.
• Calibrated weight plates: Plate weight discrepancies larger than 1% introduce load error into the regression. Weigh all plates before the testing session on a calibrated scale.
• Consistent bar height and grip position: The LVP is exercise-specific and setup-specific. Any change in bar path, stance, or grip will alter the velocity values at each load and invalidate the existing profile.
• Athlete prerequisites: The athlete must be familiar with maximal intentional velocity on the target exercise. Athletes with less than 3 months of barbell training typically produce inconsistent velocity data because technique variability dominates velocity noise.

Step-by-Step Testing Protocol

The goal is to collect 5–7 load-velocity data points spanning approximately 40–95% of estimated 1RM with minimal fatigue accumulation between sets.

1. General warm-up: 10 minutes of light cardiovascular activity and dynamic mobility specific to the test exercise.
2. Specific warm-up set 1: 5 reps at approximately 30% estimated 1RM; full velocity intent. Record MCV. Rest 2 minutes.
3. Specific warm-up set 2: 3 reps at approximately 45% estimated 1RM; full velocity intent. Record MCV. Rest 2 minutes.
4. Test set 1: 3 reps at approximately 55% estimated 1RM. Use the best MCV from the 3 reps (not the mean across reps, since fatigue within the set reduces the last rep). Rest 3 minutes.
5. Test sets 2–5: Single reps at 65%, 75%, 85%, 92% estimated 1RM. Rest 3–4 minutes between each. The heavier loads require only single reps to minimize fatigue accumulation.
6. Optional test set 6: If the athlete is fresh, add a single at 97–98% to establish a point near the minimum velocity threshold. Only include if technique remains clean.

Critical protocol rule: every rep must be performed with maximal intentional velocity — including warm-up sets. Submaximal effort at any load point compromises the regression line. Cue: "Move the bar as fast as you possibly can on every single rep, regardless of the load."

Building the Regression Line

Once you have 5–7 data points (load, MCV), plot them on a scatter graph with load on the x-axis and MCV on the y-axis. Apply a linear regression (least-squares fit). For the back squat and most lower-body exercises, this relationship is linear with r² typically 0.97–0.99 in trained athletes.

Quality check: If any data point falls more than 0.08 m/s from the regression line, discard it — it was likely a technical error or submaximal effort. Rebuild the regression with the remaining points. Do not use a profile with fewer than 4 valid data points.

Most VBT software (and PoinT GO's app) performs this regression automatically and generates the line equation in the format: MCV = m × Load + b, where m is the slope and b is the y-intercept. The slope m typically ranges from −0.010 to −0.015 m/s per 1% 1RM for the back squat.

Store the profile by exercise and date. A trained athlete should rebuild their LVP every 6–8 weeks or after any significant training block that changes their strength level — because as 1RM increases, the entire regression line shifts (V0 stays relatively stable; L0 moves rightward).

Establishing Your Minimum Velocity Threshold

The minimum velocity threshold (MVT) is the MCV produced at true 1RM — the lowest velocity at which the athlete can still complete the lift. Published MVT values for major exercises:

• Back squat: 0.25–0.35 m/s (mean: 0.30 m/s)
• Bench press: 0.17–0.25 m/s (mean: 0.21 m/s)
• Deadlift: 0.08–0.18 m/s (mean: 0.13 m/s)
• Power clean: 0.80–1.00 m/s (reflects the ballistic nature of the lift)

Individual MVT values vary by ±0.05–0.10 m/s from published group means. If you have performed an actual 1RM test in the past 3 months, use the MCV recorded at that 1RM as your personal MVT rather than the published average. Personal MVT values improve the precision of daily 1RM estimates from ~5% to ~2% error.

Using the LVP for Daily 1RM Estimation

Once the LVP is established, daily 1RM can be estimated in two reps at the start of any session:

1. Load the bar to approximately 65% of your last documented 1RM.
2. Perform one rep with maximal velocity intent. Record MCV.
3. Apply the LVP regression: solve for Load (1RM) using the MVT as your target MCV.
4. Alternatively: calculate the % 1RM corresponding to the measured MCV using your profile, then multiply actual load by (100 / %1RM) to get estimated 1RM.

Example: An athlete's LVP equation is MCV = −0.012 × %1RM + 1.32. They load 80 kg and measure MCV = 0.65 m/s. Solving: 0.65 = −0.012 × %1RM + 1.32 → %1RM = 55.8% → Estimated 1RM = 80 / 0.558 = 143.4 kg. If their MVT is 0.30 m/s, this estimate can also be derived by extending the regression to the MVT point.

This method, applied at the session's start, gives the athlete's training load prescription for that day — adjusted for whether they are 95% of their best (prescribe near-planned loads) or 88% (reduce intensity by one level and add volume, or reschedule the high-intensity session).

When and How to Update the Profile

The LVP must be updated when the athlete's strength level changes meaningfully — otherwise daily 1RM estimates drift further from reality over time. Specific triggers for profile rebuild:

• After any 6–8 week strength training block where significant 1RM improvement is expected
• After return from injury or detraining (>3 weeks away from the primary exercise)
• When daily 1RM estimates from the existing profile deviate by >5% from subjective effort perception on repeated test days
• After any change in exercise setup (different bar type, rack height, stance width, footwear)

Profile updates use the same testing protocol described above. The key comparison between old and new profiles: if the slope (m) stays similar but the y-intercept (b) increases, absolute strength has improved while relative power at each %1RM is maintained — a positive training outcome. If the slope flattens, the athlete has improved more at light loads than heavy — suggesting a shift toward power-speed qualities.

References

1. Gonzalez-Badillo, J.J., & Sanchez-Medina, L. (2010). Movement velocity as a measure of loading intensity in resistance training. International Journal of Sports Medicine, 31(5), 347–352.
2. Jidovtseff, B., et al. (2011). Using the load-velocity relationship for 1RM prediction. Journal of Strength and Conditioning Research, 25(1), 267–270.
3. Weakley, J., et al. (2021). Velocity-based training: From theory to application. Strength and Conditioning Journal, 43(2), 31–49.