Where coaching practice diverges
from the evidence
What 63 Australian triathlon coaches told us about how they actually prescribe, measure, monitor, and manage training load — and where those practices only partially align with evidence-based recommendations.
Most coaches prescribe load.
Fewer systematically monitor it.
Evidence-based recommendations for training load management are well-established in the literature. But how closely do practising coaches actually follow them? This study measured the gap — across prescription, measurement, monitoring, communication, and role allocation — in the Australian triathlon coaching population.
The question is not whether coaches know what they should do. The question is whether they have built the process to actually do it.
63 coaches. 18 questions.
An Australian coaching snapshot.
An online survey of 63 qualified Australian triathlon coaches, capturing how they prescribe training load, which metrics they use, how often they view data and communicate with athletes, what technology they rely on, and how they allocate responsibility across the load management process.
Almost all participants (94%) coached age-group athletes, with an average squad size of 17.4 athletes. The sample represents the practical reality of community-level coaching — not elite programme structures.
Coaches prescribe with feel.
They measure with data.
RPE and subjective effort dominate prescription (78%), while objective metrics — time, distance, pace, and power-based load scores — dominate measurement (81% and 73% respectively). The two sides of the training load process are speaking different languages.
Coach's Read
This is not necessarily a problem. Prescribing with feel and measuring with data can work — but only if the coach has a deliberate system for translating between the two. Without that bridge, prescription and measurement drift apart.
"Prescribing with feel and measuring with data
is not a contradiction. But it is a tension
that needs managing."
Most coaches view data weekly.
But 37% only communicate monthly.
Coaches view training load data more frequently than they communicate about it. The most common data-viewing frequency was weekly (44%), but the most common communication frequency with athletes about load was monthly (37.2%). That gap matters in a sport where weekly load decisions shape injury risk, fatigue, and adaptation.
Coach's Read
If a coach sees a problem in the data but waits until a monthly check-in to act on it, the training has already been done. Communication cadence is not just a preference — it is an operational decision with direct consequences for athlete outcomes.
How many hours do athletes actually have?
Coaches estimated the weekly training availability of their athletes. The numbers rise steadily with athlete level — but adherence tells a different story. Non-elite athletes complete 77–82% of prescribed work. Elite athletes reach 96%.
Coach's Read
The adherence plateau across non-elite levels (~78–82%) is important. It means coaches should expect roughly one in five prescribed sessions to be missed or modified — and should build prescription tolerances accordingly. The elite adherence figure (96%) reflects a fundamentally different athlete-coach relationship, not just better discipline.
Four places where coaching practice
diverges from the evidence.
The paper's deeper finding is not that coaches lack knowledge. It is that the full load management process — from prescription through to communication — has structural gaps that reduce its effectiveness.
TrainingPeaks leads.
But it is not universal.
More than half of coaches used TrainingPeaks as their primary TMS. But a meaningful proportion still relied on messaging tools, spreadsheets, or written plans — methods that make it harder to integrate subjective feedback with objective data in a single view.
Coach's Read
A TMS is not inherently better than a spreadsheet. But it does natively integrate prescription, measurement, subjective feedback, and communication in one place. If a coach is juggling three separate systems, the question is whether load management is harder than it needs to be.
"The gap is not knowledge.
It's systematic practice."
Who owns each stage
of the load process?
The study found that responsibility shifts across the load management process. Prescription is predominantly coach-led. Measurement and monitoring are increasingly shared. Management — the final stage where load is adjusted in response to data — becomes collaborative.
Coach's Read
This is a sophisticated finding. The shift from coach-led prescription to collaborative management implies that the load process is not a one-way instruction — it is a partnership that deepens as it moves from planning to response. Coaches who treat the whole process as coach-owned may be missing athlete input that would improve outcomes.
62% monitor both acute and chronic load.
27% watch only the short term.
Most coaches assessed accumulated load across both acute and chronic timeframes — a finding broadly aligned with evidence-based recommendations. But more than a quarter focused only on acute (short-term) load, and 10% only on chronic load.
A predominantly short-term focus may limit a coach's ability to detect the gradual fatigue accumulation that precedes overtraining. The reasons behind such preferences could include scepticism toward long-term planning, given the unpredictable non-sport lives of age-group athletes.
Coach's Read
Acute load tells you what happened this week. Chronic load tells you what has been building. Comparing the two gives you the tension between stimulus and fatigue — which is where coaching decisions actually live. Without both views, you are flying partially blind.
Monitor Both Timeframes
Monitor both acute and chronic loads to understand current fatigue levels and the magnitude of the stimulus that can be prescribed to produce training adaptations.
Make Load Collaborative
Load management can be achieved collaboratively with athletes. Facilitate this through appropriate technology — a TMS that captures both subjective and objective data centrally.
Close the Communication Gap
If you are viewing data weekly but only communicating monthly, the process has a structural lag. Communication cadence is not just a preference — it shapes how quickly you can respond.
This study changes how you
evaluate your own practice.
- Stop assuming your monitoring frequency is enough — check the gap between viewing and communicating
- Start treating acute + chronic timeframe comparison as baseline practice, not optional analysis
- Consider whether your TMS captures both objective data and subjective athlete feedback
- Ask whether your athletes know their role in the load process — and whether that role changes across stages
"The gap is not knowledge.
It's systematic practice. Most coaches know
what they should monitor. Fewer have built
the process to actually do it."
This study gives you the mirror: where the typical load process works, where it thins, and where the evidence says it should be thicker. Summit adds the coaching decision — informed by the intersection of evidence and practice.
Leighton Wells
Sport scientist, endurance coach, and founder of Summit Triathlon Coaching
What this study does not claim.
The results are specific to an Australian triathlon coaching context and may not be generalisable to coaches in other countries. Coaches completed the survey based on recall, and memory is fallible. The study does not differentiate by coach experience level, and it does not claim that non-TMS approaches are inferior — only that centralised data capture makes the full load process more visible.
Future research could explore how coaches of different experience levels implement the load process, how online coaching compares to face-to-face coaching, and how real-time logging rather than recall might provide more accurate data.
This is Summit's interpretation. The published paper is the primary record.