Programming with VBT
Translating bar-speed data into actual training plans: sets, reps, loads, and the day-to-day adjustments that follow.
Programming with VBT is the discipline of using bar-speed data — both prescriptive (target velocities) and descriptive (measured velocities) — to drive the actual load on the bar. It’s a small, specific change to traditional periodisation that compounds: programs become self-correcting session-to-session instead of frozen against a 6-week-old 1RM.
What it changes about a program
In order of how often they show up:
- Loads follow the velocity, not the percentage. Instead of pinning a working set to a fixed percentage, you pin it to a target velocity and let the load be whatever produces that speed today. On a recovered day the bar gets heavier; on a flat day it gets lighter. The training stimulus equalises across days that would otherwise differ. (Velocity targets come from the velocity zone you’re training, read against the athlete’s own profile.)
- Volume is capped by fatigue, not by rep counts. Instead of a fixed rep target, you run sets to a velocity-loss cutoff. Fresh athletes get the volume; tired athletes don’t accumulate damage.
- Block transitions read from the data. When the load–velocity profile flattens (slope decreases), the block has produced its adaptation; move on. When it doesn’t, the block needs another week.
The shift from %1RM to velocity targets
%1RM is a forecast — a load that should produce a particular effort if the 1RM is current and the athlete is on a normal day. Velocity targets are a measurement — the load that did produce the targeted effort, today, with this body.
Both are useful. %1RM is faster to write and easier for new lifters to follow; velocity targets self-correct for readiness and don’t require recent maxing. Most experienced coaches blend the two: %1RM as the planning tool, velocity targets as the in-session enforcement.
Where %1RM still wins
VBT-driven programming isn’t always the right tool. Where staying with percentages is the cleaner call:
- High-rep accessory work. A lateral raise’s load is too light for velocity to read well, and the precision isn’t worth the data-collection overhead.
- Athletes without a stable velocity profile. New lifters and athletes returning from injury often have noisy velocity data — their profile shifts week-to-week as technique stabilises. Use percentages until the profile holds.
- Skill-dominant lifts. Olympic lift technique work (skill rep counts at moderate loads) is about quality, not load. Velocity is downstream of skill on these; chase the technique, not the number.
Looking for the protocol? Turning these principles into a worked program — block layout, target velocities, the day-to-day adjustments — is its own write-up.
Applications and example uses of velocity based training (VBT)
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Charts in this topic
Load–velocity profile
The load-vs-speed function for a given lift and athlete. Plot a few sub-maximal sets and you can read 1RM from the line, compare lifts side-by-side, and see why a single percentage of 1RM lands different athletes in different velocity zones.
Bar velocity drops across a set
Per-rep velocity loss for a single working set. The cutoff line marks where the set should end.
RPE × reps table
Percentage of 1RM at every RPE × rep combination. Coaches use it forward (load → effort) and backward (effort → load), in both directions every session.
Bryan Mann's 5 velocity zones
The canonical 5-zone velocity model. Mean concentric bar speed maps to a dominant training quality across the 0.00–2.00 m/s range.
Load–power profile
Mechanical power output across the working load range, plotted in watts. The parabolic shape peaks at an intermediate load — typically 30–50 % 1RM for the squat.
Maximum-power profile
A load–power profile with the apex called out — a horizontal dashed line at peak power in watts and a vertical dashed line at the load that produces it, meeting at the maximum-power point.
Minimum velocity threshold by lift
Minimum velocity threshold values for back squat, front squat, bench, all three deadlifts, barbell row, and overhead press — by training level (novice / elite) and by effort tier (max out / tough / moderate).
20% velocity loss maximises strength
Pareja-Blanco 2017 — squat 1RM gains scale with the velocity-loss cap inside each set. Strength response peaks around 20 % v-loss, then drops as fatigue overruns adaptation.
VBTcoach 3-zone model
A simplified velocity-zone model defined on the % 1RM axis. Three load bands — Speed, Power, Strength — instead of Mann's five velocity-axis zones.
VBT has better results than %s
Vasiljevic 2024 — velocity-based training out-performed percentage-based on every test, including 1RM squat, 1RM bench, squat jump, and countermovement jump.
Machines match free weights for gains
Hernández-Belmonte 2023 found no statistical difference between machine-only and barbell-only training on most athletic measures — barbells edged ahead on change-of-direction and balance.
Cluster sets boost power gains
Morales-Artacho 2018 — cluster sets out-gained traditional 6×6 sets at every load tested (25 / 50 / 75 % 1RM), with the biggest gap at the peak-power region around 25 % 1RM.
Cluster sets boost strength gains
Akhil Samson 2018 — cluster sets out-performed traditional sets on every compound lift tested over 8 weeks — bench, shoulder, row, sumo squat, back squat, calf raise.
Cluster sets sustain bar speed
Tufano 2016 — cluster set training (3×(6×2) with intra-set rest) maintains mean concentric velocity across all 36 reps; traditional 3×12 sets decline within sets and cumulatively across sets.
Submaximal training wins long-term
Izquierdo-Gabarren 2010 — across 8 weeks, stopping sets short of failure (20% velocity loss) produced steady gains while training to failure (40% velocity loss) lost performance early and never caught up.
Training to failure slows jump recovery
Gonzalez-Badillo 2016 — jump performance crashed 44 % immediately after a higher-effort squat workout (3×8) and stayed depressed for 48 hours; the lower-effort 3×4 group bounced back inside 6 hours.
Lower velocity loss, better gains
Pareja-Blanco 2017 — training to 20 % velocity loss out-gained 40 % on 1RM, bar velocity, jump, and type-II muscle fibres, while doing significantly less total volume.
Back squat 1RM fluctuates daily
Zourdos 2016 — three trained powerlifters tested daily for 36 days. Day-to-day variation runs ± 3-5 % from the previous day's reading, even with no programmed change in load.
Failure loses at every set count
Peterson 2005 (meta-analysis) — strength effect-size for not-to-failure conditions exceeded failure conditions at every set count, and the gap widened with more sets.
Prilepin's chart
The canonical reps × intensity × session-volume table from Soviet weightlifting research. For each load band, the prescribed reps per set, optimal session total, and acceptable total range.
VBT-adjusted loads beat fixed loads
Muñoz de la Cruz 2023 — six weeks of resistance training with daily VBT-adjusted loads out-gained a fixed-load prescription on every outcome, including strength, jumps, and 30 m sprint metrics.
Individualised VBT beats group loads
Dorrell 2020 — six weeks of VBT, with one group prescribed loads from a shared group-mean profile and the other from each athlete's own load-velocity profile. The individualised group out-gained on every measure.
How cluster sets break up a set
Four cluster-set protocols (4×5, 7×3, 10×2, 20×1) drawn to scale on a 10-minute session timeline. All four equate to ~20 reps at the same %1RM but distribute them very differently.
RPE conversion chart
All four common effort languages on one chart — RPE 5.5–10, RIR 5–0, velocity loss 5–45 %, last-rep velocity 0.52–0.25 m/s. Drop a finger on any row to read across.
Velocity loss thresholds by goal
The five velocity-loss bands, how hard each one makes a set, and what each is best for — 0–10 % for power and peaking, 10–20 % for quality volume, 20–30 % for strength and hypertrophy, 30–40 % for hypertrophy blocks, 40 %+ only when failure is the point.
Squat bar path
The squat bar should track a vertical through mid-foot. Side by side with the classic fault — hips shooting back out of the bottom, carrying the bar forward before the lifter drags it back to lockout.
Snatch bar path
What a good snatch trace looks like — the bar drifting back past the knees, the hips sending it up rather than out, and a tight turnover loop finishing behind the line it started on.
Velocity target → today's load
How a velocity target turns into a weight on the bar. Warmup sets build the day's load–velocity profile, a target band is laid across it, and the crossing drops to the load axis as the working weight.
Velocity target blocks (18 weeks)
An 18-week strength cycle written entirely in bar speeds. The target velocity steps down once per block; the working load climbs — and wobbles — because it is read off the athlete's profile every session rather than prescribed.
Power vs strength + power
Cormie 2007 — 12 weeks of jump squats, matched for total work. Adding 3×3 back squats at 90 % 1RM produced the same jump and power gains as power-only training, plus everything the power-only group failed to gain.
Power cycle anchor loads
A load–power curve marked with the three loads a 16-week power cycle works across — 92.5 % for overspeed, 100 % for max power, 107.5 % for overload — read as percentages of the load that produces peak watts.
Squat depth and power transfer
Rhea 2016 — 28 highly trained athletes, 16 weeks, identical programs bar squat depth. Quarter squats put 15 % on the vertical jump and 2 % on the 40; full squats put on 1 % and nothing.
Volume and hypertrophy
Pelland 2026 — 67 studies, 2,058 participants. Muscle growth rises with weekly sets across the whole range the literature covers, with diminishing returns and a credible interval that never touches zero.
Frequency and strength
Pelland 2026 — 67 studies, 2,058 participants. With weekly set volume controlled, strength gains rise with frequency and the credible interval never touches zero. Diminishing returns past two sessions.
Ballistic power vs heavy strength
Cormie 2010 — 24 relatively weak men, 10 weeks, jump squats at 0–30 % 1RM versus back squats at 75–90 % 1RM. Jump and sprint improved the same in both groups. Squat 1RM went up 31 % versus 4.5 %.