Martin Buchheit

To maintain a leading edge in the dynamic world of sports science, professionals will need to evolve beyond simply adopting the latest technologies like wearables, AI, and analytics.

The essential elements are – and will remain – constructing and refining a strategic framework that aligns these technologies with the specific requirements of athletes and their training programs. Merely gathering data from top tech devices is not enough. It is crucial to apply this data intelligently within a context that addresses the key questions about training effectiveness and athlete responses.

Take the countermovement jump, for example. This versatile test can measure physical capabilities like jump height and also evaluate fatigue and readiness via metrics like the reactive strength index. It uses the same test and technology – vertical jump and force plate, respectively – but analyzes different variables for distinct purposes.

Similarly, we must understand the appropriate metrics and their correct applications. Heart rate variability (HRV), for instance, offers insights into an athlete’s training status (i.e., response to load) but is not a direct measure of load itself. This may necessitate exploring other measures and technologies if HRV is the sole variable tracked with tools like the Oura Ring.

Velocity based training illustrates how technology can dynamically adjust training loads during a session to target specific adaptations and manage acute fatigue. It also allows for profiling players (F-v profiles) and monitoring adaptations within an invisible monitoring framework. For example, practitioners can use consistent weight and speed as an approximate indicator of training status or performance changes.

The real significance lies not in the technology itself but in how we use it.

For sports scientists, mastering these tools is only the starting point. The enduring challenge, which is becoming increasingly complex with the continuous advancement of technology, is maintaining a framework that leverages technological data to provide actionable insights. This commitment to a strategic, framework-centric approach ensures that technology serves as a powerful tool in advancing sports science, rather than overwhelming it.

It’s not enough to adopt the latest tech like wearables and AI. We must align these tools with athlete training programs, ensuring data is used intelligently to answer key questions about training effectiveness and athlete responses - @mart1buch

Sian Allen

Two years ago, no one had any idea what ChatGPT was. Now we can use it to write code, format reports, refine training programmes, summarize research papers, analyze technique from images, and a million other things that can accelerate our practice almost exponentially if we leverage it the right way.

ChatGPT is just one example of the new tools and technologies that are growing faster than most of us reasonably have the time to make sense of and apply to our work. They offer the potential not only to accelerate athlete performance, but also help us work smarter and faster so we can spend more time in the important conversations with coaches and athletes.

I don’t think we necessarily need to use all these things ourselves and be experts in technology. But to stay ahead of the curve, we do need to develop “meta-knowledge” of what’s hitting the market, knowledge about what each tool can do, the potential pros and cons, and when and how you might apply them to support performance. This could look like building a network of experts who you can lean on to keep you up to speed, or it could look like understanding and applying robust tech evaluation processes like the Quality Framework for Sports Technologies.

The more things that become available, the harder it often is to find the signal in the noise, the tools that can actually help move the needle.

Knowing enough about technology to make good decisions about when and how to implement it in your practice can be the difference between creating a competitive advantage or just creating a huge distraction.

Two years ago, no one knew what ChatGPT was. Now it can write code, format reports, refine training programs, and more. Understanding new tools and how to apply them can create a competitive advantage or just a distraction - @drsianallen

Duncan French

In an effort not to mince my words, “the game has changed!” With the proliferation of artificial intelligence, advancements in machine learning, the ability to harness the power of big data, and a technology revolution that now allows accurate understanding of the most minute characteristics of human physiology, sport science has witnessed a monumental evolution in the past five years alone. The game has changed, and what were once considered fundamental skills and attributes for sports scientists 5-10 years ago may now be archaic and potentially redundant.

Yet all is not lost. Ironically, some fundamental skills and behaviors remain as relevant today as they were 50 years ago. Consequently, the next gen sport scientists must position themselves for success by ensuring they have a non-negotiable understanding of human physiology, training science, research methods, and data analysis, while also acquiring essential leading edge skills that differentiate them from others in their ability to bring added value to a team or organization.

Additionally, sports scientists must continue to excel in their ability to successfully navigate human interaction and consequently must also work to develop soft skills in order to truly succeed.

As we move deeper into the age of data and technology, “speed of insight and learning” will be the biggest competitive advantages within sport. Those athletes, teams, or organizations that can take the overwhelming amount of information available to us, process it, and make impactful decisions will ultimately be the ones who succeed.

For these reasons, I anticipate that sports scientists will be expected to perform more advanced data management, data analysis, and data visualization. Skills such as coding, software and app development, creating AI bots, using business intelligence tools, and managing cybersecurity will become more and more in demand. The future will require sport scientists to effectively integrate a vast number of peripheral technologies in order to automate and accelerate decision making.    

While the ability to learn and acquire these new skills will ensure sport scientists remain a valuable addition to any organization, I always say “we don’t work in a sport industry, we work in a people industry.”

While book smarts are important, there are true skills in building valuable inter-personal relationships, fostering respect and recognition, and, ultimately, communicating with teammates and colleagues throughout all areas of an organization. Learning how to communicate effectively, how to manage challenging conversations, how to present effectively, and building powerful communication styles are almost as critical as having knowledge of energy systems, GPS, coding, muscle physiology, and many other areas of sport science.

If you can’t communicate well, create powerful and authentic relationships, and have an awareness of your social and professional status within an organizational hierarchy, what you know is almost irrelevant.

These are skills that we need to learn and evaluate on a regular basis. They can be the difference between being successful or being dispensable.          

The game has changed with AI, big data, and technology revolutionizing sports science. To succeed, sports scientists must excel in data analysis, coding, and integrating technologies while mastering human interaction and communication - @duncanfrench

Darren Burgess

To stay ahead in the high performance game, sports scientists need to hone or broaden their skills in several key areas. First off, getting a handle on data analytics is a must. Being able to collect, crunch, and make sense of large datasets from multiple sources can offer valuable insights into performance, injury risk, and game strategies.

Traditionally, Microsoft Excel has been the vehicle for this. Today, learning to code in languages like Python and R is a must, as is understanding how advanced statistical methods can help make informed, data driven decisions.

Another skill that sports scientists should improve is data visualisation, ideally using multiple platforms like Excel, Keynote and Powerpoint, because coaches and athletes might prefer more simple presentation methods. However, the future proof sports scientist will be able to use a range of interactive visualisation tools such as Shiny, Tableau and PowerBI for more advanced, live data presentation.

Understanding the strengths and limitations of new performance and recovery technologies is crucial in this field. Performance assessment technologies, wearables, virtual reality (VR), AI, and the recovery space are changing constantly. Players are regularly exposed to these technologies, and the scientists’ abilities to understand and implement them, where appropriate, are becoming increasingly important

Finally, understanding research practices to effectively review research is a skill sports scientists should learn and develop. Too often, “applied” research is published with conclusions that are not particularly applied or relevant to every practical domain. The ability to analyse which research is relevant and which is not has never been more important to a high performance program.

Sports scientists must master data analytics and visualization, using tools like Python, R, Shiny, and PowerBI. Understanding new performance and recovery technologies and discerning relevant research is crucial for high performance - @darrenburgess25

Ian McKeown

Having curiosity, a strong desire to know something and how that something can be leveraged within your unique environment.

The world around us is changing, growing, and innovating at a breakneck pace. This inevitably leads to advancements in technology and methodologies across all areas of sport. As practitioners, our areas of practice and specific knowledge must keep pace with these advancements. While it is crucial to keep pace with what is going in the innovation space, we must not skip the rudimentary and foundational skills nor theoretical knowledge. Staying ahead of the curve is only important if what you are working on is effective and additive to your performance environment.

Too often, the desire to stay ahead of the curve is at the expense of the fragile equilibriums established within performance programs. I believe that the key discriminator for elite practices is the intention to always be curious. 

This may appear boring and cliché, but couple the mastery of the fundamentals and the ability to keep pace with innovation with a relentless curiosity within your own environment. Forge a clear path of impactful practices – don’t keep up with the Joneses.

Whereas some practitioners may be early adopters to some technologies, they may not be effectively impacting their performance queries. Be fast to learn and inquire about innovation, but take your time to query their effectiveness within your performance environment.

Curiosity drives elite practices. Balancing mastery of fundamentals with innovation is key. Be quick to learn about new technologies but deliberate in assessing their effectiveness within your performance environment  - @ianmackers

Jack Nayler

I began this look forwards by reflecting back. The field has changed a lot in the last 16 years. I have always seen our role as sports scientists as sitting between and across other departments in clubs, drawing out common purpose and insight to positively affect performance. That hasn’t changed.

The advent and democratisation of technology and increased finance in football has led to greater specialisation but also a blurring of boundaries between roles. Areas that were previously solely the domain of the sports scientist have now diffused.

Testing equipment now provides information directly to the S&C coaches on the gym floor. GPS data goes live to the physio or rehab conditioning coach’s wrist as they carry out a rehab session on the grass. Data science departments now help manage and draw insight from the much greater array of data available to us as practitioners. The players, as well, are now much more data savvy and aware of how they can leverage their own data to enhance their careers.

With this evolution, our ability to work effectively with others, have honest conversations, and educate and inform those around us has never been more important. We need to be able to speak the language of everyone from the head coach / manager through to the physios, data scientists and S&C coaches.

As technology has become cheaper, smaller, quicker and easier to use, and a small number of companies have come to dominate the market, there is less chance that it can provide a performance benefit over our rivals. Rather, it is in the efficient and insightful use of this technology and our ability to create knowledge across the organisation that will give us greater success.

That said, the sports science department is still the gateway into clubs for many new technologies. A critical eye and ability to fairly evaluate the validity and reliability of any new tech is important in deciding whether it can provide an impact or not.

With more staff and more data comes greater complexity. Cutting through noise to provide insight and clear messaging is a vital skill, but this must be balanced with an ability to critically make collective decisions that involve input from multiple different disciplines and practitioners.

The irony is that with greater diversification in roles, we may need to be more specialized and have deeper knowledge in one area (S&C, biomechanics, recovery, rehabilitation, etc). But to work effectively as part of a multi-disciplinary team, we need to have an understanding and appreciation of all of these disciplines.

The role of sports scientists spans across departments, drawing common purpose and insight. As technology democratizes and roles blur, the ability to communicate effectively and create knowledge across the organization is crucial for success - Jack Nayler