The evolution of science, technology, and data in elite sport has led to the production and collection of massive troves of information. While proper application of this data can provide an unmistakable competitive edge, there remains a distinct lack of understanding of what this information means and how we can maximize our use of it.

One of the outcomes of this has been that many coaches have a love/hate relationship with sport science. Most coaches can see the value of gathering information on the rigor of a player’s training or recovery, but that data alone isn’t valuable enough for a coach to micromanage every rep in the weight room or participate in an injured player’s physical therapy.

Simply put, a coach’s responsibility is to maximize performance. So while data can be used to inform decision making, coaches need to know their decisions are having demonstrable effects on performance. And with this in mind, it is blatantly obvious that the vast majority of coaches still have difficulty understanding how the data and science meaningfully impact what they care about.

A consistent message we hear from coaches is that if the data they collect does not impact performance, then it does not matter. I think in principle most performance scientists or sport scientists would agree with that statement. However, the feedback from many coaches is that the way in which data is used in their environments is not aligned closely enough to what they care about. For this reason, it is not uncommon to hear a coach say that they do not care if an athlete has had an increase in training workload or that an athlete has recovered poorly and has not been sleeping well and is feeling tired.

If however, as a result of that athlete’s poor sleep, they arrive at a match fatigued and unable to perform up to the demands of professional competition, jeopardizing team success, that information is not just relevant, it’s critical. Coaches do not just want to know what has happened, they want to know what it means and how that relates to the things they care about, namely how it affects performance? They want to know if their decisions and strategies in training affect the on-field performance, or if it is going to threaten someone’s ability to perform at the level they want. Coaches don’t have an interest in constantly studying player data, but if data analytics can answer these questions in a digestible manner, coaches can make better-informed decisions.

Thus, in order to deliver an effective high-performance program that focuses only on what really impacts performance, performance science staff need to understand very clearly what the head coach or manager sees as ideal performance.

My belief after spending so much time in the industry working with numerous coaches and now having worked with teams across multiples of sports, countries, and leagues is that EVERYTHING STARTS WITH PERFORMANCE. The single most important thing that any practitioner delivering a high-performance program can do is to work with their coach to understand their view of performance. By understanding how the coach views the perfect game and the performance traits he/she wants from each position and player, performance staff can tailor a program that maximizes a team’s ability to perform the way their coach wants them to… Similarly, a clearly-defined performance ideal helps provide a framework for meaningful data collection and analysis that links all of the metrics. This way, coaches aren’t flooded with unnecessary information; they’re informed by the data that they care about.

In my early days as a practitioner, my number one priority with regards to sport science was injury risk management. I was extremely focused on looking at how I could use data to reduce injury risk at all costs. What I now realise is that I had this backward. Focusing on injury management in isolation to performance was a mistake. What I have learned in time is that even if I could identify the main risk factors for specific injury and then leveraged these insights for decision making, that doesn’t mean we would have a positive impact on performance. We could be healthier for sure, but we want to perform and win.

During the latter portion of my career, the idea of “worst-case scenario” planning became commonplace in sport science and the idea of looking at the toughest games and ensuring we were capable of coping with those demands was a sensible approach. However, even now I look back on this and think that it doesn’t accurately encompass what we really needed. Just because a game is physically tough doesn’t mean we are performing at the level the coach wants or needs. The reality is that if we don’t know what the perfect performance looks like, we can’t help to put together a performance model to support it.

It’s not just about being able to cope with the toughest demands, it’s about being able to perform at the highest level. And if we don’t understand what this requires and how this impacts risk, then we can’t maximise our ability to impact both performance and health.

As I have stated above, my belief now is that EVERYTHING STARTS WITH PERFORMANCE. It is so important that we, as practitioners start with a focus on building athletes that can, first and foremost deliver consistently at the level the coach requires and display the physical traits to implement the game plan. It is then possible to build an injury risk mitigation plan that is aligned with this view of performance development.

All roads must lead to performance for our industry to flourish and we are excited to unveil the tools, processes and analytical capabilities we have designed to help be part of the solution and drive this industry forward.