In the modern era of sports science, data is everywhere. With advancements in technology, teams and coaches have access to an overwhelming amount of metrics, from GPS tracking to heart rate variability. But as tempting as it is to collect every possible data point, the real challenge lies in using data effectively to drive performance improvements.
Setanta founder Dr Liam Hennessy speaks about finding the middle ground between the practitioner and scientist, “drawing both together such that we now call this mid-ground the craft of coaching in sport or in human performance – informed by both practice and science.”
Tech Should Solve a Problem, Not Create One
Before collecting any data, teams need to identify the problem they are trying to solve. Too often, the question starts with, “What can I measure?” when instead, it should be, “What do I need to measure?”
Consider the key performance challenges your team is facing:
- Based on a needs analysis of the sport, what kind of athlete profiles do you need and how can we inform that through testing?
- What information do we need to further inform the direction of the programme (speed, power, strength, fitness, etc)?
- Are there any injury concerns that may influence what we need to track?
The goal must always stay the goal—data should serve as a tool to improve performance, not an end in itself. Without a clear objective, data collection risks becoming a time-consuming distraction rather than a performance-enhancing tool.
Striking a Balance: Cost, Time, and Practicality
Once the key performance questions are defined, the next step is selecting the best method of measurement. This requires balancing several factors:
- Financial Cost: Does the technology justify the expense?
- Time Investment: Will data collection and analysis take away from actual training?
- Benefit vs. Harm: Could the technology disrupt or mislead the process?
For example, ice baths were once considered a recovery essential, yet research has shown they may not be the best use of time for many athletes. Just because something is widely used does not mean it is necessary.
Avoiding Data Overload
With new technologies emerging constantly, it’s easy to become lost in an array of data and lose sight of what really matters.
To prevent data overload:
- Be critical of what data you collect. Does it provide actionable insights?
- Use a filtering system. Not all data is useful—focus on the metrics that answer specific performance questions.
- Consider the context. What works for one team or sport may not apply to another.
Ultimately, data should be collected with a clear purpose. The most important question to ask before integrating any new technology or data system is: “How much is this going to inform the programme and improve performance?”
Testing vs. Monitoring: Understanding the Difference
Testing and monitoring are often mistakenly used interchangeably, but they serve distinct purposes:
- Testing: Conducted at specific times (e.g., pre-season) to establish a baseline for key performance metrics.
- Monitoring: Ongoing tracking throughout the season to assess changes over time, ensuring players are staying within optimal ranges.
For example, physiological and biomechanical tests help establish baseline data, which can then be used to monitor fluctuations in fatigue, workload, and injury risk.
Over-collecting data can be counter-productive, but so can doing nothing. The key is identifying trends—when a player’s metrics fall outside their normal range, it’s a strong indicator of fatigue or potential injury.
The Importance of Individualisation
One-size-fits-all approaches rarely work in sports science. Every athlete is unique, and their data should be interpreted within their own context.
- Normative values should be based on the individual, not just general benchmarks.
- Certain athletes may have higher tolerance for workload due to their physical structure and injury history.
- A good data system should allow for individualised interventions based on an athlete’s personal trends, rather than arbitrary cutoffs.
Looking Beyond the Numbers
Newell’s model of sports performance emphasizes a multidisciplinary approach. Performance isn’t just about numbers—it’s about integrating data with coaching experience & intuition, biomechanics, and psychology.
- Exercise-induced fatigue can be analysed in isolation, but a holistic view often provides deeper insights.
- Reductionist approaches—where data is analysed in isolation – often miss the bigger picture.
- The best coaches integrate human experience with data, rather than relying on technology alone.
Balancing Data and Athlete Relationships
One of the biggest risks of excessive data collection is that it can create a barrier between coaches and players. When athletes see data as a replacement for real coaching, it can become an “escape route”—an easy excuse for avoiding hard training.
Coaches need to:
- Maintain strong personal relationships with their athletes.
- Avoid over-reliance on data apps and monitoring tools.
- Use data as a tool, not as the sole decision-maker.
The most valuable insights often come from human interaction, not just numbers on a screen. A conversation with an athlete about how they feel can sometimes be more telling than any dataset.
Data as a Tool, Not a Crutch
Technology and data should support coaching, not replace it. While performance metrics can provide valuable insights, they must be used with purpose—not just for the sake of collecting numbers.
- Define clear goals before collecting data.
- Choose metrics that truly inform decision-making.
- Avoid overloading players and coaches with unnecessary data.
- Balance data with human intuition and coaching experience.
When used correctly, data can be a powerful tool for improving performance. But at the end of the day, it is the coaches, the players, and the relationships between them that truly make the difference.
Further Your Expertise
As technology increasingly shapes the landscape of sports science and performance, professionals are expected to possess advanced skills that extend beyond traditional expertise. Setanta’s MSc in Advanced Sports Technology is designed to equip coaches who are active in the field with the skills and knowledge necessary to excel in the rapidly evolving field of sports technology.
