Overrated and underrated GPS metrics: The view of 6 experts

We’ve brought in six experts to explore a key question in workload monitoring: What are the most overrated and underrated GPS metrics, and why? With diverse perspectives spanning different sports and contexts, they share insights on what these metrics really tell us, what they miss, and how they can be used effectively.

Measures of player load, typically quantified by the triaxial accelerometer GPS units, can be an overrated and overly relied upon metric.

Player load lacks the ability to provide context related to the sport itself. The term itself has become a colloquial way of describing how much activity an athlete or team has done, but this oversimplifies what is truly happening on the field.

Depending on the sport and position, player load metrics have strong relationships with distance, accelerations / decelerations, and time, making it a blunt marker of total volume. The relationship with time presents an issue in American football, as field conditioning sessions are typically one hour in duration, while practices and games can last 2.5 – 4.5 hours. Therefore, focusing on a single player load metric may under-represent the highly demanding movement patterns that occur during intense conditioning sessions.

One should also consider the differences in player load when the device is worn in different garments (vest, jersey with no pads, jersey with pads, and in pads), as these variations will produce different outputs based on how tightly the unit is secured.

Despite some issues with acceleration (to include deceleration) counts, these are useful measures for understanding the linear acceleration movement volumes within American collegiate football.

An important element of this sport is the ability to accelerate, decelerate, and change direction effectively to either gain separation or close gaps. Setting the appropriate thresholds for these measures allows practitioners to quantify each athlete’s exposures to these highly demanding manoeuvres. When preparing a team for the physical demands of the sport, building to the acceleration volumes each positional group will face in games can help mitigate the potential for injuries related to large jumps in volume.

The most important point is that acceleration counts are easy for performance practitioners and coaches to understand and apply. With a high level of context and understanding of the movement skills for each position group, these counts enable practitioners or coaches to design conditioning sessions and practice plans, as they can identify where these efforts may occur within their drills.

Mauro Mandorino & Mathieu Lacome

The real question, then, is do we need more data or less?

Take GPS analysis, for example. Data providers flood us with hundreds of metrics. But at the end of the day, what really matters is delivering quick, simple information to the coaching staff. Essential, clear, and concise — this is what football demands.

We often ask ourselves whether we’re really quantifying everything that happens on the pitch with these metrics. Football movement is inherently complex, and if we think about specific actions like shots, passes, and duels, the answer is no, we’re not fully capturing everything.

GPS tracking is currently the best tool in our arsenal. Without it, we risk missing important pieces of the puzzle. That’s why we spend so much time convincing players to wear these devices, even during matches. “But we have tracking data,” they often protest. I explain that, first, it’s about comparing apples to apples in terms of training and match data. Second, having a device on your body captures complex movements that cameras alone can’t detect.

This exemplifies the difference between an overrated and underrated variable: having 3D information vs. 2D.

The most overrated metric is total distance.

Every time a player asks me after a match, “How much did I run?” I want to reply, “Is that really all you care about?”

Total distance — the queen of volume data — can tell you everything or nothing, depending on the story you want to tell. “Wow, you ran a lot. You’re a beast!” or “You didn’t run much. You were super efficient!”

Total distance alone doesn’t tell the full story. It doesn’t capture true effort, the moments of high intensity, or how the load was distributed throughout the match. It’s too simplistic to stand on its own.

On the other hand, PlayerLoad has the potential to offer more valuable insights. It’s still underrated and often missing from daily reports, probably because it’s so closely linked to total distance. But tracking movements movement across all three axes gives us a fuller picture of body load, capturing complex actions like jumps, impacts, and tackles. It has its limitations, but when we combine these metrics, we get a more realistic view of what’s actually happening on the field.

Ultimately, football analysis isn’t about having more data — it’s about having the right data. And maybe, just maybe, one day we’ll find that perfect balance between what’s essential and what’s superfluous.

Emma Beanland

Volume, quantified objectively via distance, and player load are two staples of workload monitoring across team sports.

Distance is a familiar metric, easily understood by multiple stakeholders, including coaching staff, front office, athletes, and performance staff. Player load is an exclusive metric that is not available in all tracking systems, which may pose challenges for practitioners utilizing different game-day tracking technologies. Just about all systems measure volume, permitting easier comparisons and consistency between practice and game monitoring.

American football is dependent on multiple physical characteristics where the athlete’s top speed, braking ability, and eccentric strength are some of the key attributes of an elite athlete.

To fully understand both the metabolic and mechanical cost of game demands, practitioners should investigate acceleration and deceleration actions.

High intensity acceleration and deceleration (high >2.5 m/s², very high >3.5 m/s²) are key to understanding tissue stress, decay of neuromuscular capacities, and muscle damage ^[1–4]. Understanding braking capabilities helps us best quantify performance characteristics and investigate both individual and position specific demands.

Certainly, there is no one magic number for workload monitoring. We must consider multiple metrics and contextual factors in athlete management. American football is a game of finite play time with distinct physical characteristics based on down, distance, and duration. Acceleration and deceleration play a critical role in describing neural competencies and ensuring athletes are prepared for game day demands. These metrics also play a key role in influencing practice design and period selection.

The differing demands of various team periods heavily impacts the weekly schedule and periodization. For example, the acceleration and deceleration demand of a red zone team period are vastly different from third down actions due to field position and playing space. With forces greater than six times athletes body weight occurring during sprinting, the high impact and loading required to both accelerate, cut, and decelerate highlights the importance of these measures.

The balance of preparation and risk is the art of optimal preparation and performance. Metric selection based on game demands, simplicity of communication, and contextual factors are crucial for sports scientists to add value to the coaching and performance staff.

Shaun McLaren

In rugby, acceleration magnitude is important because there is a lot of high intensity linear movement occurring in confined spaces, often at low velocities. You can link the ability to better accelerate with key performance moments: being able to come onto the ball at pace, maximising collision momentum, or getting off the line quickly in defence, reducing the opposition’s decision-making time and momentum gain.

The traditional approach of counting acceleration efforts in discrete ‘bins’ can be problematic because you might incorrectly miss a high intensity acceleration simply because it fell marginally short of an arbitrary threshold.

Average acceleration (AvAcc) is the mean of instantaneous acceleration and absolute deceleration values over a given period. It might be a better way of quantifying the acceleration intensity of a drill, training session, or competition. But, just like distance per minute, the stop-start nature of the game means AvAcc can underestimate the true intensity of actual movement performed.

Acceleration density index (ADI) is an underrated metric that overcomes this issue. ADI expresses the accumulation of instantaneous acceleration and absolute deceleration per 10 m of distance travelled, as opposed to time. You can quantify the intensity of change in speed during locomotion, rather than over an entire period. This can be useful for positions like wingers, who typically stand still (or move with minimal acceleration) for long periods between otherwise very explosive efforts.

We’ve had some success in using ADI to differentiate between drill types, athletes with distinctly different movement profiles or physical qualities, and phases of play, where other GPS metrics have fallen short.

I’ve always struggled with the concept of “metabolic power” (MP). It’s calculated from velocity and acceleration measured with GPS (or any other tracking system), on the assumption that accelerated running on flat terrain is biomechanically equivalent to running at a constant speed on an inclined treadmill.

Despite the name, you’re not actually measuring anything metabolic at all – a notion supported by the lack of agreement between MP derived from GPS and that which is estimated from VO₂ using indirect calorimetry during team sport specific activity.

There could be a lot of reasons for this. The energy cost of constant speed running is an integral part of the MP equation, and it has some crucial limitations: its intra- and inter-individual variability, the fact it differs between surface types, and that it only applies to constant speed running on flat terrain.

MP is still often mistaken as a measure of internal training load, which is confusing and problematic. It’s a measure of external training load, but not a very useful one since it’s a black box approach.

If you want to interpret or manipulate MP (e.g., training evaluation, training prescription, athlete management), look to one of its two primary components: velocity or acceleration. Why not cut out the middleman and simply monitor one of those?! They are easier to understand, easier to interpret, and easier to affect.

That’s all a build up to the one metabolic power metric that I just can’t get my head around: high metabolic load distance (HMLD). This is the total distance covered when metabolic power is greater than 25.5 W/kg.

As well as the limitations of MP, an extra caveat is at play: the threshold of 25.5 W/kg. All the typical drawbacks of a fixed arbitrary threshold apply, but the rationale for 25.5 W/kg is particularly unclear. Some say it’s equivalent to VO₂max (presenting drawbacks of its own, given how much this varies within and between athletes), while others simply associate it to a running speed of 5.5 m/s (again, why not monitor high-speed running distance?).

The mystery around this metric only grows stronger when you realise an athlete’s body mass isn’t used in HMLD calculations.

Jesse Green

To make sense of the plethora of data available, sport scientists and performance analysts must have a rigorous process for metric selection, taking into account core scientific principles (validity and reliability), as well as deep consideration of sport demands. Combining these factors together can be challenging, especially when working in a new sport or when research is scarce.

Take ice hockey, for example, a sport played indoors, on ice, and at high speeds. When we consider the very low friction coefficient between the skate and the ice, and the fact that movement speed can be maintained (glide) with minimal to no energy expended, we see that a metric such as total distance does not provide an accurate depiction of overall volume. Total distance is an overrated metric for ice hockey.

Digging deeper into the demands of ice hockey, the confines of the rink rarely allow players to reach true top speed. There’s simply not enough space. Monitoring acceleration may therefore be more useful, as now we can start to understand the “speed change” activity that the sport demands of its players.

Not all acceleration is the same, though. A hard back check versus a small reposition on a power play clearly differ in magnitude, and we should account for that when quantifying demands.

A useful metric in this case is high intensity minutes (HIMs). HIMs describes the volume accumulated in higher acceleration / deceleration zones as a function of time, and can also be calculated using accelerometer based bands. When acceleration is more relevant, HIMs is underrated in its ability to quantify high intensity activity in a way that is easy to communicate and understand.