The art of sports science

There is a tendency in sports to treat athletes as machines, and to treat a team of athletes as a larger machine with each athlete acting like a cog in wheel. This isn’t unique to sports by any means and is common practice in many industries. However despite similarities, people are not machines and it is just as important to recognise the differences, which are pivotal to maximising human performance, as it is to accept the similarities.

This tendency to view people and their interactions as machine like is reflected in language used today, such as when referring to successful companies or sporting teams as working like ‘well oiled machines’ or complimenting an athletes performance by referring to them as ‘being a machine’. Simply using this analogy isn’t itself a problem, there are of course many similarities between successful performance in physical tasks and machine behaviour, however it is contributing to a disturbing, dangerous and restrictive trend which is seeing athletes actually being treated more and more like machines, rather than simply being described as such. To treat athletes, or to begin to actually see athletes essentially existing as machines, is to ignore vital aspects that are unique to the person.  As this article will present there are some significant negative impacts to athletes and team performance resulting from this perception, negative influences which go largely unrecognised. It’s not until we’re able to step back and see the paradigm we live in and that influences our perception that we are able to appreciate the benefits and limitations of the approach and therefor adapt our methods to improve outcomes.

What’s in a name?

Since the industrial revolution, it seems there’s been a growing worldview, often encouraged by science, that is to explain things in mechanistic ways. Since we are the creator of machines, we understand them very well – we had to understand what we were building before we built it. We started with the parts and then built the whole. As we are a part of nature, rather than the creator of it, we seek to understand nature and events within it over time by observation and testing. We start with the whole and over time seek to better understand the parts. Natural events or organisms are quite complex, interdependent on one another and therefor hard to entirely predict. In order to create a ‘working’ mental construct that allows us to move on without getting caught up in the details, we tend to simplify these events in nature to be more machine-like. This is not a problem and in fact serves a useful purpose, but issues do arise when we forget that these events or organisms are in fact not entirely machine like and downplay the aspects that are unique to natural organisms and events rather than machines.

There is a motivation for those in charge of athletes, sporting teams or any large business to view their program in machine like ways. All are chasing success and consistency, and running a team of machines would exemplify this. Provided consistent fuel, maintenance and instruction, machines would produce consistent outcomes. Improve the parts and the machine improves in an appropriate manner. Improve the machines in a team and the team benefits in an appropriate manner. Tighten nuts and bolts and you improve efficiency of the team. There would be a straightforward procedure for creating the perfect athlete or team for the respective sports. Coaches and Sports Scientists enjoy this analogy as it helps solve one of the biggest problems when measuring or researching inside sports, people. People are irrational, influenced by emotion, desires, ego and habits based on past experience – all things that can act as extraneous variables when you’re trying to get feedback on whether a training or recovery method you introduced was effective. But if athletes were truly machines, they would be predictable, either performing better or worse based on how effective their training and recovery methods are, and of course the fuel that they are being provided with. This is an utopian dream for those working in sports. But it would take what is as much an art as it is a science and turn it into a science as pure or hard as physics. It’s never going to occur and to place more stock in it that it deserves is to limit sporting performance and success while setting yourself up for failure. As will be presented, very often when we do attempt to control certain aspects of performance, our actions can have unintended consequence to other aspects of performance. We over-value the characteristics of performance that we can easily see, measure and quantify (more machine-like), and tend to under-value the more vague characteristics that we don’t recognize or are much harder to see and understand (unique to nature).

Scientific influence – The dark side

The negative trends discussed in this article result from three related errors that consistently arise inside modern science and are likely to have developed or to have been encouraged by the dominance of machines in modern life. As science uncovers more it seems these dogmas are becoming more and more flawed and are being openly challenged inside science itself. However they still heavily influence how we interact with each other and view athletic development and team management. The three errors are as follows.

  1. Mechanistic error: limitations resulting from treating people, teams or events as overly machine-like.

  2. Materialist error: limitations resulting from assumptions that matter is the only reality (explaining away consciousness or a non-physical realm/influence).

  3. Reductive error: limitations resulting from assumptions that wholes (such as an athlete or a team) can be entirely explained entirely by the sum of the smaller parts or characteristics.

In many ways we have begun to view things in mechanical, materialist and reductive constructs (or means of interpreting the world). The result of this approach is to research and look for answers in the parts that comprise the whole, assuming that we could fully understand the whole by the sum of the parts – as we can with machines we build. However we are not machines and we never will be. After all you can take a machine apart, learn about it’s components, put it back together and it works fine. But try to do the same to a person and you run into trouble. We are not machines no matter how often we tend to think of people, and athletes in particular, as such. We are influenced by emotions, intention, desires, ego and habits which tend to make people in many respects irrational, unpredictable beings. These cannot be separated from the aspects of the athlete which appear machine like, perhaps physical force or speed. We can attempt to measure these physical characteristics in isolation (a reductive approach which tends to assume that the the whole is simply the sum of the smaller characteristics) but in reality (outside of the sports science laboratory) they occur alongside a myriad of other characteristics and are always influenced by the immeasurable characteristics unique to the person – emotion, intention, desires, ego and habits.

So while we certainly benefit from measuring and exploring individual aspects of an athlete and their performance, it is important to not lose sight of the forest for the tree’s and remember that no amount of testing will paint a complete picture of that athlete. Anytime a characteristic of the athlete is tested or trained outside of a competitive game setting it loses a degree of relevance. Yes some tests or drills are more relevant than others but overall there are significant flaws and they simply provide the best option we have to practically test or develop these traits. When you consider the inter-dependance of these characteristics it becomes even harder to reduce players to simply being the sum of their individual characteristics. For example you might build a physically strong athlete in the gym, but unless their intent in competition is to play strong, or hold their ground, or impose a physical presence, they will not effectively transfer their gym specific strength to game moments. In this case, testing their strength in the gym will not provide an accurate reflection of how strong that athlete is when it matters. True perception of the athlete cannot be seen using reductive lenses (getting caught up on the smaller details – in this case testing a physical characteristic in a removed, less relevant, setting), but instead can only be seen by stepping back and viewing the person as a whole inside their environment.

The mechanistic view is that we essentially function as highly developed robots. The reductive nature of science has developed largely in response to it’s huge early success in medicine. By learning more about the functioning of the human body at smaller and more detailed levels, we have seen an enormous growth in medical success. It appeared for a long time that further increase of the magnification of the microscope was key to progress in medicine and science. This trend has permeated much of the sciences and it seems these days we spend more and more time learning about less and less with more specific areas of study and specialisation.

Progress traps

The reductive nature of science is now drawing criticism as ‘progress traps’ emerge. This is when time and money is spent investigating certain details, feeling as though much progress is being made along the way by research ‘break-throughs’, only to find out that the thing being investigated isn’t actually relevant when transferred back to the real world. Discoveries were being made along the way, but the error was at the top, in what was being investigated.

Progress traps are becoming apparent even in medicine, it now seems as though we are spending more time and money discovering less and less practical information than ever before. For example we are discovering more and more about genetics and their influence on obesity, or about how fat loss and fat gain work at cellular levels, and yet the obesity epidemic is gaining momentum rather than slowing down. It seems we’re investing ever more time and money searching for a super-pill which will solve our  problems, when really by stepping back and looking at general trends in society that contribute to obesity, inactivity and over-eating of poor food choices would be a better use of time and money. Technology is also seeing the same trend as medicine is. We are producing and consuming more ‘unnecessary’ products than ever before, feeding wants rather than needs. While I recognise there is still some debate over the occurance or impact of global warming, even sceptics would agree that we are too rapidly depleting the world of its natural recourses, such as fresh water and coal and are harming our atmosphere as a result. Rather than slowing our growth and reliance on new novel technological advances, we encourage it and speed it up, assuming that even if our current lifestyles and rate of growth is not sustainable, that technology will solve the problem before it becomes significant enough in the western world to be an immediate concern. Stepping back and looking at trends as a whole rather than specific details would present a more relevant picture of what needs to happen. We must consume less and alter our growth mindset to one that is much more sustainable.

While it’s not something I’ll go into too much in this article, if you’ve read some of the others on this site you might have recognised the approach of reducing inactivity and poor food intake, or consumerism and waste, as an example of the ‘via negativa’ approach to improvement. The safest, most assured way of seeing improvement is by removing things you know cause harm, rather than adding more variables (such as a super-pill for weight loss) and assuming there are no negative influences from them. In these cases we would arguably see better real world benefit from reducing funding of research at the microscopic level to increase funding of social action aimed at reducing inactivity, reducing access to poor food choices, and reducing wasteful consumption of products and ultimately the Earths natural recourses. Returning to sports, the safest way to see improvement in performance is by removing aspects of the athletes training or lifestyle that we know hurt performance, rather than isolating components of performance, developing them, and hoping they transfer back to competition performance improvements without any negative influence.

Research in motor learning and skill development is beginning to show the risk of chasing benefits by addition (via positiva) and the progress traps they can bring with them. For example we might choose to improve an athletes competition performance in a particular skill by designing a drill to include in their training program. Research is showing that the more we isolate the skill and the more verbal cues and technical details we include, the better the athlete will perform in that drill. We tend to assume that improvements in this drill will equate to improved competition performance. However very often the opposite is true and the better the athlete performs in this drill setting the worse they perform in a game given some unintended negative learning effects. So all the improvement seen inside that drill at training had the illusion of progress, but really it wasn’t relevant to competition and we’ve run into a progress trap. A similar occurrence could be seen in focusing too much on improving stability, strength, power or speed as measured by gym specific exercises. While some exercises are known to transfer better or worse to competition performance, none are truly specific and caution must be placed in getting too carried away with gym based performance improvements.

Sometimes it isn’t just progress traps which emerge, but we get carried away in new research forgetting that they are only a small part of a bigger picture. Very often, we lose sight of the forest for the tree’s too quickly making changes and throwing out tried and tested training methods to make way for a new one as recommended by current research. There are many trends in research that create similar focuses for sports scientists or strength and conditioning coaches, I’ll use as a hypothetical example the importance of muscle fibre specific training for athletic development. In reality, getting carried away investigating the muscle fibre type of an athlete will tell you nothing about their intent, habits, decision making ability, movement patterns or emotional tendencies during moments in which they need to actually be fast. Muscle fibre types might play a role in physical performance, and there is value in learning more about the physiology of athletes at this level, but it is far from the most important of area’s and to consider basing a strength program around targeting changes at this level over addressing movement patterns or habits at a motor learning level would be a mistake. The same could be said of hormonal responses to strength training or quantifying training loads in the gym. If we manipulate factors to improve these qualities we risk benefiting them at the expense of other perhaps more important variables that we might not even be aware of, perhaps exerting an unintended negative impact on sport specific skill expression through changes in coordination while selecting exercises that provided a better hormonal response.

The general trend in science and research is reductive, to explain things by looking deeper and at greater levels of complexity. This is a materialistic view which assumes that we are the sum of our parts and that by better understanding the components of the whole, we will better understand the whole itself. There is value in this, but it is dangerous when taken too far as I hope I’ve already began to indicate. Athletes are complex organisms influenced by countless physical and psychological aspects which are co-dependent  and cannot be looked at in isolation, at least when desiring relevant transfer back to a game situation or real world settings.

Alternate view

An opposing view put forward is that everything exists as a whole within a whole, and that each whole is greater than the wholes which comprise it. That is that a organ is greater than simply the cells which make it up, and an organism is greater than simply the organs and other parts that make it up. To take this further and more relevant to sports, a group of people, or a team, would be greater than simply the sum of the individuals that make it up. I think this is something that people involved with sporting teams can relate to, the ability of a group of individuals to work together is often the key to winning or losing, or winning a single championship and building a lasting dynasty. This is summed up nicely in this well known quote “A champion team beats a team of champions”.

This whole within a whole approach assumes that there is an immeasurable characteristic of the athlete, a synergy of their individual characteristics, and a synergy of the team beyond the sum of their individual characteristics. Machines do not have this quality, they are simply the sum of the parts. A machine has a very definite cap in it’s performance capacity. Individual athletes seem to be able to transcend, at least on occasion, what they seem to be capable of and produce extraordinary performances. Two machines working together is simply twice as efficient as one machine. To treat a team of 10 athletes as simply being the sum of the 10 athletes is to miss out on the collective synergistic potential of that group. To reduce an athlete to simply being the sum of their individual characteristics (strength, speed, sporting skills ability etc) is a restrictive mindset which limits the aspect of that person to achieve goals that are beyond their current ‘assessed’ ability. Frequently the power of the mind to defy physics or logic or expectations has proved remarkable. Science supports this. For example, rats have been thrown into buckets of water and timed to the point they exhaust, this was found to be on average 15 minutes. However if the rats were briefly removed around the 15 minute mark and then put back in, the time to exhaustion extended to a phenomenal 60 hours. Even accounting for the intermittent nature of this exercise and the brief rest periods, the extended time to exhaustion makes no sense based on the physiological capacity of the rats. Athletes can relate to this, very often they thrive of those around them believing in them. They draw energy off the faith that others place in them. It’s in some ways the power of the placebo effect in action, but the result is no less real despite our inability to explain or quantify it.

My concern is that by treating athletes and teams as machine like, we have the unintended effect of capping their potential for individual greatness or team synergy. The longing for athletes and teams to be machine like actually becomes a self-fulfilling prophecy in some ways, but with some largely unforeseen and potentially disastrous consequences. When you consider that wholes might have elements that are not measurable or testable, or simply the incredibly complex nature of something like a person, or team of people with countless elements that are interdependent on one another, then it becomes vital to consider the art of strength and conditioning or coaching and not just the science.

Summary

Despite people, coaches and even athletes commonly associating with them, of course athletes will never be machines. Even the most motivated athlete is still subject to their feelings and other traits specific to humans rather than machines, which at one point or another will impact their performance in a way that wouldn’t occur were an athletes actions and interactions truly constant and machine like. To make the mistake of thinking that athletes are machines is to set yourself up for failure. Collective human potential is far greater than that of a collection of machines and to treat people as machines is to reduce or cap the collective synergistic potential that group has. It also leaves athletes lacking in many areas. If they don’t feel emotionally connected, invested and supported then you’ll find their motivation or work rate might lag over time or perhaps more rapidly after a slump in performance or bad loss when they’re more vulnerable to these feelings arising. Very often it seems to be the athletes that ignore and bury these feelings and human characteristics that suffer the greatest when they build up to a level which ‘breaks the surface’ and result in a severe performance detriment or social mishap that awards them a place on the back pages of a paper for all the wrong reasons. They are encouraged to work hard and achieve their goal despite all else and as such they ignore the distractions of their human nature, such as emotions, motivation or ego. They haven’t built up any resilience or coping strategies by dealing with smaller fluctuations in these areas (they don’t allow them to occur by ignoring their value) and as a result suffer to a greater extent when they are exposed. These characteristics must be catered for and should not be downplayed as a secondary priority to any characteristics you might associate with a machine such as training regimes (physiology & physics)  or fuel (physiology & chemistry).

The scientific method is a powerful tool of enquiry, but in many ways it has transitioned from simply being a tool to help explain physical events occurring in the world, to a worldview which often explains away or de-values any non-physical events or events that are difficult to measure and quantify. It is important to recognise the limitations of such a view, and it’s influence over how we view and interpret events around us. We must appreciate both the science and the art of athletic development.

Part 2

In part two, the limitations that this machine like view has on how we manage teams, design strength programs and structure performance testing is explored using real world examples. Following this, a compromise between the arts vs science approach to athletic development is discussed providing a solution to some of the limitations of both views to ultimately refine how we approach athletic development.