Perception of bar velocity loss in resistance exercises: accuracy across loads and velocity loss thresholds in the bench press

Antonio Dello Iacono*, Kevin Watson, Milan Marinkovic, Israel Halperin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Purpose: Velocity-based training is used to prescribe and monitor resistance-training based on velocity outputs measured with tracking devices. When tracking devices are unavailable or impractical to use, perception of velocity loss (PVL) can be used as a substitute, assuming sufficient accuracy. Here we investigated the accuracy of PVL equal to 20% and 40% relative to the first repetition in the bench press exercise.

Methods: Following a familiarization session, 26 resistance-trained men performed four sets of the bench press exercise using four different loads based on their individual load-velocity relationships (~40-90% of one-repetition maximum [1RM]), completed in a randomized order. Participants verbally reported their PVL at 20% and 40% velocity loss during the sets. PVL accuracy was calculated as the absolute difference between the timing of reporting PVL and the actual repetition number corresponding to 20% and 40% velocity loss measured with a linear encoder.

Results: Linear mixed-effects model analysis revealed four main findings. First, across all conditions, the absolute average PVL error was 1 repetition. Second, the PVL accuracy was not significantly different between the PVL thresholds (𝛽=0.16, P=0.267). Third, greater accuracy was observed in loads corresponding to the mid-portion of the individual load velocity relationships (~50-60% of 1RM) compared to lighter (60%1RM, 0.63 ≤ 𝛽 ≤0.84, all P values
Conclusions: PVL can be implemented as a monitoring and prescription method when velocity tracking devices are impractical or absent.
Original languageEnglish
Pages (from-to)488-494
Number of pages7
JournalInternational Journal of Sports Physiology and Performance
Issue number5
Early online date16 Mar 2023
Publication statusPublished - 31 May 2023


  • auroregulation
  • biomechanics
  • velocity-based training
  • monitoring


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