What are the 3 biggest misconceptions when it comes to load monitoring?

We consulted six experts to discuss the top three misconceptions about load monitoring; here’s what they shared with us.

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Jake Gillies

First Team Sport Scientist, Bristol Bears

Misconception 1: Volume is the key component of load monitoring

A lot of discussion around “load monitoring” focuses on aspects of volume, and rightly so, because “volume” and “load” tend to be synonymous. However, one thing that doesn’t often get investigated is how that volume is accrued.

Take a GPS metric such as high speed running (HSR). Regardless of whether it is absolute or relative, it is a volume metric. Players of all sports will have norms for their training and matches, and one of our jobs as practitioners is to identify anything out of the ordinary. We can get hung up on the end number being the important number. If I have a player who is regularly exposed to 500 metres of HSR in a match and I only observe that, I could miss information about how many efforts it took him to accumulate this volume; or I could neglect the fact that he once played 70 minutes with more HSR metres per minute.

The inputs to the end number are just as important as the end number.

Misconception 2: External load tells me what I need

Measuring “work done” only provides some of the information we need. Outputs don’t always match up equally with a player’s input.

Tracking an internal metric like sRPE-TL can provide a long term, cumulative overview of the athlete’s perceived demand. However, this has its own complications as it does not account for the exercise modality.

Another internal measure is heart rate, which provides an objective understanding of the cost of the exercise. However, HR has its own issues when you consider the different TRIMP calculations, or zone models that are available and commonly used.

The idea that we can manage or monitor load using just external metrics is naïve.

Misconception 3: Spikes in load are evil

Whilst it is nice to have consistency in training, there are times in a season when you cannot avoid peaks and troughs in training frequency and demands. Short turnarounds, additional cup matches, or limited player availability mean the workload gets passed around fewer players.

These are not a guaranteed precursor to injury. Being ill prepared to handle spikes in load can increase the likelihood of injury risk, but well structured preseason and in-season training can help prevent this.

How we prepare for, and react to, spikes in training load are more important than the spikes themselves.

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Mathieu Lacome

Performance Director, Paris Saint-Germain

Misconception 1: Volume of high speed running is a measure of training intensity

Which sports scientist hasn’t heard or said, “We did 500m of high speed running—it was a very intense session today”? The volume of high speed running often doubles as a proxy for session intensity in many football clubs. While this might be understandable under certain conditions, it’s a misconception.

Intensity is the amount of work performed per unit of time ^[1]. When training duration and density are constant, the volume of high speed running or mechanical work can provide a rough indication of intensity. The problem arises when those other variables change, particularly duration and density. For example, two metabolic oriented sessions may both result in 800-1000m of high speed running but involve very different intensities and internal loads (e.g., heart rate).

That’s why I always recommend monitoring internal load—even if players sometimes complain. This helps quantify the physiological impact of the session. It’s also useful to track metrics such as 3-5 minute peak game demands to contextualize the session intensity ^[2].

Misconception 2: Game running activity is directly related to fitness

“The team isn’t running enough—we need to train more and improve fitness.” This is a common belief in many team sport environments. Fitness is important to compete at the elite level. That’s not in question. Improved football fitness often reduces internal relative load and may enhance decision making.

However, you cannot infer fitness levels solely from game running data ^[3]. We recently showed that match context—tactics, scoreline, and playing style—has a greater impact on running output than fitness or freshness ^[4]. In practice, this becomes obvious when a team changes its coach and thus it playing style, and suddenly runs significantly more within just one week. You can’t meaningfully increase fitness in four sessions.

Misconception 3: Within-week loading determines game day physical performance

Tactical periodisation is now widely used across football ^[5]. In this model, a high intensity, metabolic oriented session is often scheduled midweek. Proper loading at this point is important to develop fitness and robustness.

However, some fitness coaches mistakenly believe missing this midweek metabolic session will reduce the potential match day physical performance. In reality, match day output results from two opposing forces: fitness (positive) and fatigue (negative, or inverse readiness). Readiness fluctuates daily and can be adjusted quickly. Fitness, in contrast, is built and decays over a longer timeline.

So yes, consistency in training is key for long term development. But if you need to unload the team to aid recovery, skipping a metabolic session won’t harm match day performance ^[6]. It will likely help.

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Seppe Torfs

Physical Performance Coach, Lommel SK

Misconception 1: There is only one road to Rome

This misconception isn’t limited to load monitoring. It’s pervasive across many areas of strength & conditioning and sports science in professional sport.

Early in my career, I believed that you could copy and paste successful processes from top environments and automatically expect success. I quickly learned that without a deep understanding of your own environment, this approach falls short.

My experience with City Football Group has made it clear that periodization strategies, and the load monitoring that supports them, vary significantly between teams. For example, Lommel SK in Belgium’s second tier faces very different challenges compared to New York City FC, where extensive travel plays a big role; or Manchester City, which competes at the highest level across multiple competitions.

Each environment requires a tailored approach to periodization and, with that, a contextualized approach to load monitoring.

Misconception 2: Higher load means better performance

When external load data first started gaining attention in football, the English Premier League stood out as the most physically demanding league. At the time, I mistakenly used those load metrics as benchmarks, pushing my own teams to chase similar numbers, thinking this would better prepare them. In hindsight, I now see how misguided that was.

There isn’t a direct relationship between higher loads and higher preparedness. Context is everything. The internal and external loads must make sense for the demands placed on players within their environment. That’s why we now use an approach based on game load, linking both acute and chronic loads to each player’s highest intensity games. This keeps the load relevant to the individual, the team’s tactical approach, the competition format, and the player’s developmental stage.

Top European benchmarks can still serve as useful reference points for a player’s development. But the path to reach those levels must be individualized and grounded in context.

Misconception 3: The “correct” load will fix everything

It’s naïve to think load alone is the key to solving issues like fitness or injury. Performance and injury risk are multifactorial—load is just one piece of a much larger puzzle. That doesn’t mean load monitoring isn’t valuable; on the contrary, it’s a foundational piece of a well-structured, individualized approach to performance and injury reduction.

What matters is how load is used. A solid framework that integrates both internal and external load, considers volume and intensity, and contextualizes data to the individual and environment is essential. But more importantly, data should inform decision making, not dictate it.

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Mitch Cholewinski

Coordinator of Football Sports Science, Nebraska Football

Misconception 1: Load monitoring is backward-facing

Load management includes the planning or periodization of conditioning, resistance training, and tactical preparation. If you plan well enough and have the discipline to stick to that plan, you can handle days with unplanned excessive or low loading.

Volume is not the only variable that needs to be managed in an athlete’s training load. If we neglect intensity (both sport- and position specific) and density, we do the athlete a disservice. Changes in any of these variables can significantly impact the athlete’s fitness-fatigue status.

To help athletes perform at the highest level, we must plan, evaluate, and monitor all three variables. Failing to prepare for competition-level intensities and densities not only increases the risk of injury but also limits performance.

Misconception 2: Load monitoring is just about in-game or training adjustments

At the end of the day, our job is to put athletes in the best position to succeed in their sport, as healthily as possible. Regardless of the sport, the season will beat up and wear down your athletes. We must accept that and plan for it.

The crucial part of setting athletes up for success is ensuring they can participate in tactical preparation as much as possible. It’s our responsibility as performance professionals to support their skill development in every way we can.

Before removing a player from tactical participation, I evaluate three steps: specific guided recovery and nutritional interventions, collaboration with the S&C staff to limit lifting volume, and reduced tactical participation.

Misconception 3: Unplanned high loads are always bad

One of the hardest lessons I’ve had to learn is that every sharp increase in an athlete’s load isn’t necessarily a cause for alarm. The athletes we work with are elite because they’re genetically equipped to handle demands that most others simply cannot. Allowing an athlete to experience high load days, weeks, or even months—planned or not—will significantly contribute to their long term development.

More time practicing means more reps; more reps lead to greater familiarity with the system; and more experience in the system (theoretically) results in higher performance. Holding an athlete back and limiting their training load is a decision that must be carefully considered, as it carries the risk of hindering their long term development.

A simple conversation with your athlete, seeing how they feel, talk, and act will give you an incredible amount of insight and help guide you on what to do after a high training load period.

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Ben McKay

Sport Science Coordinator, University of Oregon

Misconception 1: Load monitoring is separate from load planning

Load monitoring has become a widely discussed concept, often carrying negative connotations. Excessive focus on load monitoring can lead to unnecessary participation restrictions—resting athletes simply due to a previously “high” workloads. Without a well structured plan across performance and coaching departments, load monitoring can come to be seen as a reactive action that restricts athletes.

Misconception 2: External load measures reflect internal response

External load measurements from wearable technologies like GPS, accelerometers, and IMU provide valuable insights, but they do not account for an athlete’s internal response to exercise. A meaningful change in external workload does not necessarily indicate a negative adaptation or a significant increase in fatigue; nor does it necessitate an immediate modification to training or competition.

For effective load management, external measures should be complemented by assessments that account for the internal response to exercise.

Misconception 3: All metrics are good metrics

Relying on unvalidated metrics can lead to flawed decision making during load monitoring. Many metrics find their way onto load monitoring reports without accurately representing what they claim to measure. This can create overconfidence in data driven inferences, resulting in misguided load adjustments that may hinder athlete or team performance.

High performance teams and coaching staff must prioritize validated metrics that are scientifically supported and relevant to the demands of their sport.

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Cedric Leduc

Sport Scientist

Misconception 1: Internal load is a measure of response

The concept of training load has evolved significantly since the foundational work of Banister and Calvert. Starting in the early 2000s, new conceptual models introduced a clearer distinction between training load (external and internal) and its effects (positive/negative, acute/chronic). These constructs reflect the biological principle of dose-response. Yet in practice, there is a frequent confusion between internal load and response.

Variables like RPE or heart rate are often used interchangeably to represent both load and response, which is a conceptual mistake.

Internal load is the stress the body experiences. Response is the reaction to that stress.

Why is this distinction important? Consider two athletes who both report the same internal load (e.g., RPE 6/10). The next day, one is recovered and ready; the other is fatigued and sore. If you mistakenly treat RPE (or any other internal load markers) as an indicator of response, you might assume both athletes should continue training as planned—potentially putting one at risk.

This may seem anecdotal, but it has real consequences. Misunderstanding key concepts leads to flawed monitoring systems and poor decision making.

Misconception 2: Post-match monitoring is not to be disputed

At conferences or on social media, we often see polished presentations of post-match monitoring practices: “When a deviation from baseline is detected, we follow our decision making flow chart…”

We all know the reality is more complex. There are two uncomfortable truths here: First, the logistics and management structures in elite sport often prevent practitioners from fully acting on the data. Player resistance and lack of coach buy-in can weaken both the integration and impact of monitoring systems.

Second, the science itself isn’t bulletproof. Even with reasonable construct and face validity, the direct link between monitoring measures and higher level outcomes like performance or injury remains poorly understood.

Does this mean we should stop monitoring? Absolutely not. But we do need to shift our expectations. Monitoring should not be about making instant decisions from daily data (which might happen once or twice a season). Instead, focus on identifying adaptation patterns over a week (e.g., how should I plan my training according to player’s status?) or spotting long term trends that inform your broader performance strategy (e.g., periodization, training adaptation, injury prevention).

Misconception 3: Data is sport science, sport science is data

Over the past decade, the role of the sport scientist has changed dramatically, increasingly blending with data analyst or data scientist roles. As a result, many practitioners are developing stronger skills in coding and statistics than in physiology or biomechanics. This shift has consequences.

In some organizations, there’s no longer a gatekeeper for sport science knowledge. We collect data but lack the biological and contextual understanding to interpret it meaningfully.

Data without knowledge is just data decorating dashboards—not driving decisions.

We’re at a crossroads. The rise of AI and other large language models is already transforming how high performance sport operates. However, the more we embrace these tools, the further we risk drifting from core sport science principles. Many “advanced features” now being sold into elite environments are scientific nonsense, wrapped in sleek user interfaces.

This isn’t a call to resist to change. It is a reminder to balance technological opportunities with the fundamentals of human training theory, and sport context. Sport science must evolve, but not at the cost of becoming irrelevant.