PhD Pinboard: Integrating Training Load Monitoring with Developmental Pathways in Youth Basketball
- Jo Clubb
- 3 hours ago
- 9 min read
This PhD Pinboard article by Jonathon Lever explores training load monitoring in youth basketball and how it integrates with coaching and youth development goals.
I’m Jono Lever, the Research and Innovation Sport Scientist at the University of Notre Dame, and formerly a Sport Scientist and Assistant Strength & Conditioning Coach with the NBA Global Academy in Australia.
I recently completed my PhD at the University of Technology Sydney, where my research focused on how training load monitoring can be meaningfully integrated into high-performance youth basketball development pathways.
My thesis, “Integrating Training Load Metrics with Player Development Pathways in High-Performance Youth Basketball,” examined how internal and external training load data can be used not just to monitor athletes, but to support coaching decisions, guide long-term development, and verify whether training is actually delivering the intended stimulus.
High-performance youth basketball athletes increasingly train in environments that resemble professional programs, while still navigating growth, maturation, schooling, and long-term development. Within this context, training load monitoring is often discussed, widely collected, and inconsistently applied. Too often, data exist without clear links to coaching intent, practice design, or player development priorities.
This PhD was driven by a simple question I kept returning to in applied practice:
How can training load monitoring actually help coaches do their job better in developing young basketball players?
From there, the research followed four linked studies that explored longitudinal training loads, positional and seasonal demands, coaches’ perspectives on monitoring, and whether the physical outputs of training actually aligned with what coaches intended to develop. Together, these studies aimed to bridge the gap between measurement and meaning in high-performance youth environments.
Why Training Load Matters in High-Performance Youth Basketball
High-performance youth basketball sits in a unique and challenging space. Players are exposed to training environments that increasingly resemble professional programs, often involving multiple daily sessions, competition travel, and year-round schedules. At the same time, they are navigating rapid growth, maturation and academic demands.
Within this context, training load monitoring is widely discussed and commonly performed, but far less consistently impactful. In many youth environments, load data exist in isolation:
Collected because it can be
Reviewed retrospectively
Rarely linked directly to coaching intent, practice design, or long-term development
Yet adolescence is a period where poorly managed progression can have lasting consequences, including injury risk, stalled development, or burnout. If monitoring is going to justify its place in youth programs, it needs to do more than describe what happened yesterday.
It needs to help coaches:
Plan appropriate progression
Balance development and performance
Confirm whether training is actually doing what it is meant to do
This PhD was motivated by that gap, between data collection and decision-making, and by a desire to better align monitoring with how coaches actually think and work in high-performance youth basketball environments.
From the Court to the Data: Studying Load in a Youth Basketball Academy
This research was embedded within a high-performance youth basketball academy over multiple seasons.
Rather than examining short snapshots or isolated training blocks, the work followed players longitudinally across multiple years, capturing how training exposure and load evolved as athletes progressed through the program.
Working within the academy environment reinforced that training load is rarely delivered exactly as planned. Sessions evolve in real time, player behaviour influences intensity, and unstructured elements are a feature of basketball practice rather than an exception. These realities shaped both the questions asked in this research and how the findings should be interpreted in applied settings.
How training load was measured
Internal training load was quantified using session Rating of Perceived Exertion (sRPE), calculated as session duration multiplied by each athlete’s post-session RPE (Foster et al., 2001).
This approach was selected due to its practicality, validity in youth populations, and alignment with how coaches already reflect on session difficulty (Scantlebury et al., 2018). Weekly average values were used for season and year-level analyses.
External training load was measured using inertial measurement units and a local positioning system, capturing movement demands such as:
Total and relative distance
PlayerLoad and its derivatives
High-speed running exposure
External training load was expressed per minute for drill-level analyses to allow meaningful comparison across activities, while weekly average values were used for season- and year-level analyses.
Going beyond session totals
Rather than focusing only on daily or weekly totals, the analysis also examined:
Training load across academic terms (training blocks/seasonal phases) and development years
Positional differences
Drill-level load profiles, linked to coach-defined development goals.
Drills were categorised based on their intended developmental focus, allowing comparison between training intent and physical output, rather than assuming that session design automatically translated into a specific stimulus.
Integrating coaching context
Quantitative monitoring was complemented by semi-structured interviews with academy coaches, exploring how training load information was perceived, interpreted, and applied in practice.
This mixed-methods approach ensured that findings were interpreted within the real constraints of basketball coaching, including unstructured training elements, tactical priorities, and the need for flexibility in session delivery (Abraham et al., 2006; Partington & Cushion, 2013).
The intent was not to control or optimise training through data alone, but to understand how monitoring could meaningfully support decision-making in a high-performance youth environment.
What We Learned: Four Key Insights from a Youth Basketball Academy
Internal training load progresses across development years.
Internal training load, quantified using session-RPE, increased progressively across training years.
Second-year players accumulated more sessions, longer session durations and higher weekly internal sRPE load compared with their first year in the program.
Within each year, internal load also varied across academic terms. Later terms generally accumulated higher loads than earlier ones, aligning with periods of greater training density and competitive preparation.
Importantly, no meaningful positional differences were observed in internal load. Despite guards and frontcourt players experiencing different movement demands, perceived training stress was broadly shared across roles. This highlights the value of internal load for understanding how training is experienced, not just what it looks like externally.
External training load varies by season and position, not necessarily by year.
In contrast to internal load, external training load did not continue increasing year-on-year.
Instead, it varied primarily by academic term (seasonal phase). Higher volumes and intensities were observed in off-season and preseason periods. Lower external training loads occurred during competitive phases.
This pattern suggests that as players progressed, the academy shifted emphasis from more work to different work. Training evolved toward greater specificity, tactical focus, and efficiency, rather than simple accumulation of volume.
Clear positional differences were evident:
Backcourt players accumulated higher distance per minute, PlayerLoad per minute, and deceleration counts
Frontcourt players experienced different mechanical profiles despite similar overall exposure.
These findings reinforce that external load should be interpreted through the lens of role and movement demands, not just total training time or age.
Coaches value monitoring - when it fits their workflow
Interviews with academy coaches revealed a consistent theme:
monitoring was useful when it supported coaching, not when it competed with it.
Coaches viewed performance development holistically, prioritising:
Effort
Discipline
Coachability
Decision-making under fatigue
Physical metrics were valued when they supported these priorities, not when they attempted to override them.
Monitoring was most useful when it:
Supported communication
Helped manage fatigue and recovery
Provided confirmation rather than prescription
Coaches resisted:
Rigid thresholds
Overly complex composite metrics
Reports that were disconnected from practice language
Adoption was improved when data were:
Consistently defined
Reported in shared time windows
Framed in terms of drills and weekly planning.
Training intent often aligns with output - but not always
The final study examined whether coach-prescribed development goals matched the physical loads actually delivered.
Using drill-level external training load data, development goal categories could be classified with approximately 66% accuracy, with key contributors including high-intensity decelerations, vertical PlayerLoad, and high-speed running. This suggests that different training intentions were often associated with distinct physical outputs, but with meaningful overlap.
Importantly, a large proportion of total training time was spent in general, tactical, or less-structured drills, rather than tightly defined physical development activities. These drills often involved variable constraints and open decision-making, meaning physical load could fluctuate based on player behaviour and session flow.
As a result, some drills did not deliver clearly differentiated physical outputs despite having specific development intentions, while others accumulated substantial load despite minimal physical intent.
Together, these findings highlight the value of routine “fidelity checks”, using monitoring to confirm what training actually delivered rather than assuming intent and output are always aligned.
What This Means for Coaches and Practitioners in Youth Basketball
Taken together, these findings suggest several key principles for practitioners working in youth basketball.
Use monitoring to guide progression, not just record load.
Internal training load increased across years, but external training load did not indefinitely escalate. This supports development models that prioritise quality and specificity over simple volume increases.
Periodise around the calendar.
Seasonal differences in load emphasise the importance of aligning physical stress with:
- Academic pressures
- Recovery opportunities
Monitoring helps verify whether these shifts are actually occurring.
Individualise by role, not just age.
Positional differences in external load reinforce the need for role-specific interpretation, even when total training time appears similar.
Keep monitoring coach-centred.
Monitoring is most effective when:
- Metrics are familiar
- Outputs reflect how coaches design sessions
Complexity should only be added if it improves decision-making.
Verify intent, don’t assume it.
Drill-level analysis provides a practical method to confirm whether training is delivering the intended stimulus, and to adjust training design when it is not.
Final Reflections
Completing this PhD reinforced that training load monitoring is most valuable when it sits within the coaching process, rather than alongside it.
Across this work, the data did not simplify decision-making or replace coaching judgement. Instead, it provided context, highlighted patterns over time, and occasionally challenged assumptions about what training was actually delivering.
One of the clearest messages from this research is that progression in youth basketball is not simply about doing more.
Internal and external training loads evolved differently across the academy, reflecting changes in exposure, training structure, and season demands rather than linear increases in physical work. This reinforces the importance of viewing development as a process shaped by timing, role, and environment, not just volume.
Perhaps most importantly, working within a real-world academy environment highlighted that training is rarely delivered exactly as planned. Unstructured elements, player behaviour, and contextual constraints all influence the stimulus athletes experience. In this context, monitoring is best used as a tool for verification and refinement, helping practitioners confirm whether training aligns with developmental priorities without constraining coaching creativity.
Ultimately, this work has shaped how I now think about monitoring in youth sport: not as a solution in itself, but as a means of better aligning intent, practice, and long-term development.
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References
Lever, J. R., Duffield, R., Murray, A., Bartlett, J. D., & Fullagar, H. H. (2024). Longitudinal internal training load and exposure in a high-performance basketball academy. The Journal of Strength & Conditioning Research, 38(8), 1464-1471.
Lever, J. R., Duffield, R., Murray, A., Bartlett, J. D., & Fullagar, H. H. (2024). Quantifying the training demands of a highly trained male youth basketball players by year, term and position. Journal of Sports Sciences, 42(17), 1597-1604.
https://doi.org/10.1080/02640414.2024.2402619
Lever, J. R., Murray, A., Bartlett, J. D., Aurellado, I., Duffield, R., & Fullagar, H. H. (2025). Revisiting the playbook: Coaches’ opinions and current views of performance, development and load monitoring in highly-trained male youth basketball players. International Journal of Sports Science & Coaching, 20 (5), https://doi.org/10.1177/17479541251342023
Lever, J. R., Duffield, R., Murray, A., Bill, H.A., Bartlett, J. D., & Fullagar, H. H. (2026). Does the Intent Match the Output: Aligning Development Goals With Training Load in Youth Basketball. European Journal of Sport Sciences, 26(3),
FAQs
What did this research show about how load progresses in a youth basketball academy?
Internal training load increased across development years, primarily through greater training exposure and session duration. External training load, however, did not continue to increase year-on-year, instead varying more by academic term and training phase.
Why did internal and external load show different patterns across the program?
Internal load captured how training was experienced as exposure increased, while external load reflected how training content and structure changed across the calendar. Together, this showed that progression in the academy was not simply about doing more physical work each year.
What did you learn about positional demands in youth basketball training?
Backcourt players consistently accumulated higher distance per minute, PlayerLoad per minute, and deceleration counts than frontcourt players. These differences were evident despite similar overall training exposure, highlighting the importance of role-specific interpretation.
How much of training was actually tightly structured around physical goals?
A substantial proportion of total training time was spent in general, tactical, or less-structured drills. These activities often produced variable physical loads depending on player behaviour and session flow, rather than clearly defined physical targets.
Do drills usually deliver the physical stimulus coaches intend?
Often, but not always. Drill-level analysis showed meaningful alignment between intended development goals and physical output, but with overlap between categories and drift in some cases.
What is the practical value of monitoring training intent versus output?
It allows practitioners to verify what training actually delivered, rather than assuming intent and stimulus are aligned. This supports refinement of practice design without constraining coaching creativity.