The return-to-play (RTP) process after injury is complex, non-linear, and multifactorial. Recent evidence shows that assessing tissue healing is not enough; athletes also need to be progressively re-exposed to the physical and cognitive demands of training and competition.
A progressive process to restore the athlete’s ability to tolerate pre-injury training loads.
In this context, the framework proposed by Taberner et al. (2019) has become a key point of reference. Their approach uses GPS data to gradually reintroduce players to pre-injury training loads, ensuring smooth and progressive re-exposure to the demands of training and competition. This approach guides on-pitch rehabilitation, reduces the risk of reinjury, and supports a safe return to performance. (2)
The key steps of Taberner’s framework include:
- Progressively reintroduce not only volume but also specific skills and cognitive demands.
- Quantify pre-injury loads through GPS (training & match).
- Use these chronic loads as a target to achieve before returning to competition.
Sample return to chronic running loads following the Taberner approach (Control–Chaos Continuum). High-speed running, >5.5 m·s⁻¹; sprint distance, >7 m·s⁻¹; explosive distance, accelerating/decelerating from 2 to 4 m·s⁻¹ in <1 s.
This example from Taberner et al. (2019) shows how players are gradually reintroduced to running loads based on their pre-injury chronic levels. Data are representative of a central defender’s game load, that is, the physical demands of the game (mean) and respective training and concurrent (including game), in both absolute and relative terms (game load, i.e., 2× = two games). The first two bars represent the reference pre-injury chronic load — the first combining training and match load, and the second representing training load only — while the remaining bars illustrate the weekly progression during the return-to-play (RTP) process, culminating with re-exposure to pre-injury training demands.
Beyond traditional GPS metrics
Traditional GPS metrics, such as counting accelerations above fixed thresholds or measuring high-speed running, remain valuable tools. Still, they don’t always capture the real mechanical demands of training and match play.
They often:
• treat speed and acceleration as separate variables;
• rely on absolute thresholds that may not reflect individual players’ capacity;
• and risk missing actions that truly involve high or even maximal mechanical effort.
The Acceleration–Speed Profile (ASP): assessing real mechanical outputs
To overcome these limitations, the Acceleration-Speed Profile offers a more complete view of the actual mechanical work performed by the athlete. (3)
It integrates speed and acceleration into a single mechanical framework, assessing each player’s output across their full velocity spectrum.
Rather than relying on arbitrary thresholds, the ASP provides an individualised representation of the mechanical work done on the pitch.
A typical ASP of an athlete. The red shaded area represents 80 % of the athlete’s maximum ASP. Every effort within this zone marks a high- or near-maximal mechanical action.
Case study: integrating the Taberner framework with ASP analysis
To put these concepts into practice, we applied Taberner’s framework to the on-field return of an elite rugby player after a type 2b hamstring strain.
The player was expected to return to full team training (RTT) after 6 weeks and to competition (RTG) after 10 weeks.
Alongside the progressive exposure to training loads described by Taberner et al., we integrated the ASP to monitor mechanical recovery throughout the process.
Using traditional GPS monitoring, the athlete’s progression successfully restored training volumes to pre-injury chronic load levels, aligning with the Taberner model.
The graphs below show the weekly progression of total distance (m), high-metabolic-load distance (HMLD, m), sprint distance (> 7 m/s, m), and accelerations (> 2.5 m/s², n), demonstrating a structured and gradual return to pre-injury demands.
Weekly progression of total distance, HMLD, sprint distance, and accelerations during the return-to-play process. Blue bars represent chronic load (first bar = training + match, second = training only); yellow bars indicate the on-field rehab phase; green bars mark the return to training (RTT); and light blue bars represent the return to game (RTG) period. The bar marked with the “OK” symbol indicates the week when the injured athlete matched pre-injury load levels, consistent with the return-to-play framework by Taberner et al.
What if we integrate the ASP?
When we looked at the ASP at the time of return to training (RTT – green line in the graph), a different picture emerged. The player’s ASP curve was still below the pre-injury profile (shown in red), indicating that, despite meeting the expected training volumes across all the KPIs analysed, as prescribed by the Taberner framework, mechanical recovery was not yet complete.
ASP evolution throughout the return-to-play process — red shows the pre-injury profile, yellow the on-field rehab, green the return to training (RTT), and light blue the return to game (RTG). The graph highlights how, at RTT, the player’s mechanical profile had not yet reached pre-injury levels.
Take-home message
Taberner’s framework remains the backbone of an evidence-based RTP process.
However, integrating the ASP adds another dimension, providing insight into the mechanical work performed during recovery. The ASP doesn’t replace the Taberner framework; it enriches it, adding a deeper understanding of the mechanical work performed during the return-to-play process.
By combining both methods, practitioners can bridge the gap between training-load readiness, as indicated by Taberner’s approach, and the mechanical work captured through the ASP, ensuring a safer, more precise, and ultimately more effective return to competition.
Author: Alberto Botter
References
- Impellizzeri, F. M. et al. (2020). Training Load and Its Role in Injury Prevention, Part I. J Athl Train.
- Taberner, M., Allen, T., & Cohen, D. D. (2019). Consider the ‘control-chaos continuum’. Br J Sports Med.
- di Prampero, P. E. et al. (2023). Mechanical and Metabolic Power in Accelerated Running – PART I: The 100-m Dash. Eur J Appl Physiol.