Episode 13: Why Should Sport Embrace Complexity?
Friends, colleagues and systems thinking experts Professor Paul Salmon and Dr Scott McLean join us to tackle one sport’s most interesting and challenging questions.
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Just like the economy, the weather, or traffic, sport is deeply complex. And we don't just mean that it has lots of elements or that it's difficult to understand, we're talking specifically about what's called a complex system – have a listen to our mini episode on this topic for a bit of a primer! When you're dealing with a complex system, you've got a whole lotta moving parts, interacting with each other and their environments in unpredictable ways, and there isn't a clear and simple relationship between what one individual element does and what the system as a whole will do. It takes a special approach to tackle complex problems, so how and why should we embrace complex systems thinking in sport?
Today, host Professor Sam Robertson speaks to friends, colleagues and experts Professor Paul Salmon and Dr Scott McLean. And this time, they're all chatting together at once!
Paul is the Director of the Centre for Human Factors and Sociotechnical Systems at the University of the Sunshine Coast, where Scott is a Research Fellow right alongside him, leading the Centre's work on sport and outdoor recreation. Together these complex systems thinkers investigate complexity's rise in sport, the tools we can use to leverage it, and the risks of passing it up.
Full Episode Transcript
13. Why Should Sport Embrace Complexity?
Intro
[00:00:00] Sam Robertson: Experts have the ability to make the difficult seem simple. Whether it's Tiger Woods's tee shot on the 16th hole in the 2019 masters, or Lionel Messi's famous goal against Getafe in 2007, there's an example in every sport.
[00:00:14] The factors that have to come together to make something like that possible can be mind-bending. In ordinary language, we might describe it as being complex or complicated, often using those words interchangeably. But in science, complex and complicated are not one and the same.
[00:00:30] When we talk about complexity, we're talking specifically about what we call a complex system. We covered this in our very first mini episode a couple of weeks ago, so I recommend listening to that if you're not familiar, but in the most basic terms, a complex system is one that's made up of many moving parts, interacting with each other and responding to their environments in unpredictable ways.
[00:00:50] Of course, there's a lot more to it than that, but the key thing to note is that when you're dealing with a complex system, there isn't a clear and simple relationship between what one individual element does and what the system as a whole will do. That's why, even though things like computers or aeroplanes are quite complicated, they're not actually complex. There's a lot of elements, but we know how they work.
[00:01:11]But when we look at things like traffic, the economy, or the weather, and now you've got complexity. Systems where we can't just flick a switch and get a desired result. And complexity is undoubtedly on the rise in sport. It's not just the number of people involved, it's things like the effects of globalisation, more sophisticated technology, and the constant quest for improvement that are pushing sport further into this space.
[00:01:36] Faster computers and better analytical tools have rapidly improved our ability to measure all aspects of the sporting landscape, but the irony here is that the very tools we develop to help us make more sense of our environments are the same ones making things appear more complex. So with that in mind, is complexity actually something we want to encourage in sport? After all as Albert Einstein once said, "If you can't explain something simply, then you don't understand it well enough".
[00:02:03]On this episode of One Track Mind, we make a case for complexity's importance in sport and discuss some of the tools we can use in the field to help measure, analyse, and most importantly, leverage its benefits to improve performance. And equally importantly, we talk about some of the risks organisations face by choosing not to embrace it. I'm Sam Robertson, and this is One Track Mind.
Interview: Paul Salmon & Scott McLean
[00:02:31] Hello and welcome to One Track Mind - a podcast about the real issues, forces and innovations shaping the future of sport. On today's episode we're asking, "Why should sport embrace complexity?" My guests today, Professor Paul Salmon and Dr. Scott McLean.
[00:02:48] Paul is the Director of the Centre for Human Factors and Sociotechnical Systems at the University of the Sunshine Coast. He has over 20 years' experience of applied human factors and safety research in areas such as transport, defence, sport and outdoor recreation, healthcare, workplace safety, and cyber security.
[00:03:07] Scott is a Research Fellow also at the Centre for Human Factors and Sociotechnical Systems at the University of the Sunshine Coast, and leads the centre's work on sport and outdoor recreation. His research spans sports science, systems thinking and safety science, and he has worked as a football performance analyst in the A-League and in international football.
[00:03:26] Paul and Scott, thanks for joining me on the show!
[00:03:29] Scott McLean: Yeah, thanks for having us, Sam.
[00:03:30]Paul Salmon: Yeah, thanks. Great to be here.
[00:03:32] Sam Robertson: Well, this is something a little different for us here because it actually marks the first time on the show that we've had two guests on at the same time. So I'm looking forward to seeing how this goes. And before we get into some of the detail around this topic, I'd like to start with a bit of a general question, and an easier question perhaps, for you both, and that's why are we seeing so much increased interest in complexity in sporting circles? And perhaps not just complexity, but systems thinking, and even we're starting to see dynamical systems work its way into the popular vernacular.
[00:04:02] Scott McLean: I think for me, there's two main reasons. So I think firstly, that given that sports science is a relatively young discipline, I sort of think it was inevitable that theories and methods from other disciplines would transfer across. I mean, we saw in the early days of sports analytics where economists and mathematicians sort of began to apply their theories and methods, which worked well in sport. I think it's just the same thing is happening with complexity and theories and methods. And I hope our work has had a small helping hand here, but yeah, I think it's just an inevitable part of the evolution of a young discipline.
[00:04:31] Secondly, I think that, you know, some of these traditional sports science methods and theories, they're often viewed as a bit reductionist or quite linear in their thinking. So this, while it can give you some information, it can only give you information to a certain level. So measurements of isolated variables that don't take into account broader system components, and the non-linearity of complex systems can't be explained by this linear type thinking that we've traditionally had in sports science.
[00:04:56]I mean, using methods to understand complexity provides much more detail around the interrelated components. That's a better understanding of how we can actually improve sport. So they're my two main reasons why I think we're seeing more and more of it.
[00:05:08] Paul Salmon: Yeah, I agree with the points Scott made. I think there are other things at play here as well, and certainly if I reflect on the other areas that we work in, things like safety science, I think there's a perception that the world or systems are becoming far more complex. And if you look at sports, for example, we've got increasing levels of technology insertions and things like VAR, DRS, Hawkeye, we've got big data and we've got new technological evolutions, such as artificial intelligence, and I think researchers and practitioners are really recognising that sport is changing and if there are new methods that can help to, kind of, understand that and ensure that these changes are used in a positive way, I think there's increasing interest in them.
[00:05:49] And I think what complexity science systems thinking does, is it really becomes quite attractive when you're trying to... it seems to offer something new and potentially something beyond what existing approaches can do. And so when there's that characteristic of a set of methods, they become really attractive.
[00:06:05] I think the second point that Scott mentioned is also important, and this is certainly happening in other areas as well. So there's a kind of thinking that the existing foundational methods within certain disciplines have taken people as far as they can to understanding problems, there's this idea, for example, in sports science, that the foundational methods have really taken us as far as we can get in terms of optimising performance or preventing sports injury. And then so we have these longstanding, intractable, potentially more complex issues that those methods can't cope with. And I think, again, complexity science systems thinking is very attractive because it suggests that if you apply these approaches, we can really get at these longstanding, intractable issues.
[00:06:47] And again, in our work in other areas, that's certainly the case in safety science and areas like road safety where you've had significant achievements in increasing safety, but things have kind of stalled. And, you know, there's this idea that, well, these methods and theories have taken us as far as we can go, we need a new approach. And I think complexity science systems thinking kind of fits very nicely into that new approach.
[00:07:11]Sam Robertson: I'd like to pick up something that you both mentioned then, at some point in this conversation, which is definitely around the notion of the traditional sports science disciplines taking us as far as perhaps we can go. And I do think that's one of the driving reasons for why we're seeing this increase.
[00:07:27] I guess to add to what you both said then, I mean, I feel quite strongly that a lot of this is to do with advancements in technology, which you both touched on. And I think that's kind of been associated with this concurrent recognition that there's only so much we can do with all this information that we're now starting to collect, and that the relationships between that information is beyond say the simple human comprehension, that paralysis by analysis, or that drowning in data phenomenon that people talk about so much.
[00:07:55] And something you both touched on a little bit as well, it's not always actually an increase in complexity of the environment, it's actually just us perceiving it, isn't it? Because we're starting to measure more. So it's all actually always been there, but that of course causes people to look for artifacts or frameworks or theories to help make sense of it all. And I think if you look at the research now, and I know you've both done some of this, we're starting to see people recognise this in those big questions that sport faces. So what makes a sporting team have success? Why do some talented athletes make it and others not? And even to revert back to a previous show, why do some athletes who are exposed to exactly the same type of training as another get injured and others not? So I think that's a good starting point.
[00:08:39] With all that in mind, the next question I really want to move on to is why is complexity even important to recognise in sport? And I think we all touched on that then, but yes there's a technology component and yes there's the limitations of sports science, but there could be a camp of people that say, We've worked particularly well, fine in the past, we've won medals, we've won championships, without subscribing to this. Do we think that's going to remain the case in the years to come, or do you think now it's reached that tipping point because of some of the reasons we've mentioned? That sport, which is constantly trying to evolve and improve, will teams and athletes continue to have success if they don't start to embrace this approach.
[00:09:17]Paul Salmon: I think the short answer to that really is that complexity's important to embrace because really you can't fully understand behaviour without doing so. If we take the example of injury prevention, for example, you can focus in on a small set of variables and really understand them in detail and try to optimise them to prevent injury, but if you're not acknowledging the fact that there's a more complex set of interactions going on here, and there are other factors which interact to create injury, which can be outside of training and matches in a club environment, then your efforts to prevent injury are really never going to be fully effective. So I think it's really important to actually embrace complexity for that very reason.
[00:09:55] The question about, you know, people have always won medals and we've always had really successful teams is a very interesting one. I don't fully know the answer to that, but my feeling around this is, I was talking to Scott about this earlier, I think perhaps some of the most successful sporting teams in history probably have had complexity or systems thinkers people at the helm. And I always refer back to the English Rugby World Cup winning side under Clive Woodward, and he would often talk in kind of systems thinking terms, even though nobody was really labelling it like that. So, you know, he would talk about having to think differently, question everything. And when he first came in, I remember he used to talk about how he was looking to change the way the team played on the field, but he was even more importantly looking to change the way they operated off the field. And so I wonder if those very successful teams actually have been doing systems thinking, it just hasn't been labeled that way. That's an interesting thing to look at, I think.
[00:10:52] Scott McLean: Yeah, I would agree with that, but also on the flip side of successful performance, I mean, if you don't understand the complexity of the system, you're not going to be able to identify the issues or problems or, you know, sub-optimal performance that will continually arise and occur. Often what happens in complex systems is that, sure, we're good at identifying when a problem occurs, but we don't understand the reasons why that's occurring.
[00:11:12] A good example is if we lose a game or if someone is injured, we're quick to try and point a finger for that broken component that caused that loss, but more likely there's a myriad of systemic factors that influenced this, I guess, adverse event. Our reaction to point to that one broken component is because we don't understand how the whole system functions. And I guess this comes back to the goals of the system. So, to you understand systemic issues and systemic performance, you need to understand what the actual goals of that system is. How you progress towards these goals and also what you need to actually do to achieve these goals.
[00:11:45] And I guess a good example here is injury prevention and training load. In my opinion, there's an excessive amount of monitoring of training load these days. And for me, that's symptomatic of a poorly performing system, which is driven by poor goals, and stick with me, say we looked at a European football league. I mean, look at the stakeholders at the top of that system, at the high levels of that system, you know, we've got TV broadcasters, we've got multinational corporations with sponsorship and advertising, and that goal of them is to make money, right? So if a goal of the system is to make money, this means that players are playing 60 matches a year. So it becomes important to monitor load. Whereas, you know, if the goal of that system changed to be player welfare or player wellbeing, there'd be less need for games and we probably would need less load monitoring.
[00:12:28] But you know, on the flip side of that, coaches could also be doing more coaching rather than just preparing players for games as well. So complex systems are counterintuitive, so I guess a counterintuitive of that would be that playing less games you would actually get a better product, good players will be playing, probably the better players would be playing every match, and the stakeholders would still make money.
[00:12:46] So I guess what I'm trying to say is, if you push the system in a certain direction and you push hard on a system, it will eventually push back a little bit harder somewhere else. And the comment that Paul made, that the goals of the system influences the behaviour and that that system influences actually down to the players' and the athletes' performance. So looking at what can go wrong I guess also, as well as what can go right with the system.
[00:13:07] And I think just quickly on that injury prevention stuff, and Paul mentioned this as well, that we're continually looking down and in at the athlete and the environment, I think, and I honestly believe that we will understand more about injury and injury prevention if we look up and out towards the system. The road safety stuff that Paul does is a great example where, Paul you can jump in, you know this better than me, but the road safety efforts we're focused on education to drivers enforcement by police, and engineering of vehicles, but now we're starting to look at these broader systemic things to try and bring that down.
[00:13:38] Paul Salmon: Yeah, I mean, it's often a good example to use because everybody knows it quite well. You know, for decades in road safety, the whole response to road toll and road crashes was to basically try and fix the drivers, stop the drivers doing silly things, and I think there's been a shift really in the last, kind of, decade in road safety where road safety practitioners really now understand that actually there's a lot of these levers that you can pull elsewhere that will actually influence driver behaviour for the good.
[00:14:05] And the good example there is you have accident black spots. And so, you know, an accident, black spot, you can't be telling me that every single driver makes the same mistake in one place because of nothing, just something internal to them. And so it's this idea that there are other levers to pull as well, and I think the same thinking exactly applies in sport. We can try and fix individuals and understand individual behaviour as much as we want. And now, you know, that is useful, don't get me wrong, but the real power is in trying to understand what are those other influences across the system that actually drive that behaviour.
[00:14:39] Sam Robertson: That's a great example and I think there's obviously so much that sport can learn from other disciplines and other fields, and that's a real theme that crops up a lot on this show.
[00:14:48] There's a few things in your responses that I want to comment on and perhaps pick up on before we start to talk about some of the tools that we might be able to use practically. The first one was around that recognition, I think you used the example of the Rugby World Cup, Paul, around this not being new and it not even being newly adopted, it's perhaps hasn't been explicitly stated in the past, and that's a positive, but also a potential risk here, isn't it?
[00:15:13] I think we've seen in sport, perhaps more than in other areas even, that there is a tendency for there to be a flavour of the month and certain people pick up certain ideas and unfortunately not always implement them in a way that's true to that particular idea. And that can sometimes mean that the idea doesn't take hold or it's not sustainable in sport, and I think this is a real risk for the complexity and the systems thinking area as well, I would say. In fact, I might stop there. I mean, do you agree with that? Is that something that you've seen already? You guys are doing a lot of this work, not just in sport, but in other areas. Have you run into that problem already?
[00:15:46] Paul Salmon: Yeah, I think absolutely that is a problem and a risk, and I think one of the key things that are linked to that, which is a challenge that we've had both in sport and other areas, is people want evidence that the complexity approach or the systems thinking approach actually brings you a benefit. And, you know, we're all researchers, to actually tease out the direct benefit of taking a complex systems approach is extremely difficult. So my big concern is that people latch onto it, but then there are really not many studies that actually try and identify the direct benefits of it. And so people start to kind of forget, or even criticise it and say, well, there's no direct evidence of a benefit here so we're not actually going to use it anymore. So that's my big concern with it, becoming a buzzword, lack of evidence, and then it just dying away.
[00:16:34] Scott McLean: You're already seeing papers that they'll start off by acknowledging that things are complex, but then they'll reduce it down to one or two variables and you think, well, that's not what complexity is. You can't reduce it down to one or two variables, but I mean, that might be direction from reviewers or whatever, you don't know, but yeah, it definitely has the potential to be misused and sort of misunderstood. But yeah, we're definitely seeing it.
[00:16:55] Sam Robertson: It does tie into the next topic I wanted to talk to you about, which are the tools that people in practice can adopt to help embrace and then leverage complexity. And of course, some of those require things to be reduced down into something that is more simple or more easily understandable, but it's a fine line. And sometimes it's not a fine line between completely changing what a complex systems approach is, or a systems thinking approach is, and making it more usable.
[00:17:19] The other comment I would make at this point would be that it's certainly, we are seeing it be adopted more in practice. I think it's self-evident. You know, a lot of organisations are now starting to recognise that there's realised, and in some cases unrealised, influences on athletes and teams everywhere. I think in particular, the acceptance of this impact of sociocultural influences on athletes and teams. So there is a step in the right way, and even if it's not always explicitly stated or completely understood.
[00:17:49] What other point I wanted to make to add to what we just talked about, about why we're seeing this perhaps grow, at least the demand for it grow, is in data resolution. We certainly talked about the increase in technology, but you know an example I give a lot can be from scouting or talent ID in sport, for example. If we go back, not that long ago, the way you would evaluate an athlete's running technique, for example, would be by eye or from a static camera, which may or may not be directly perpendicular to the athlete. We're now moving into being able to do that in 3D analysis in labs, and now of course, almost marker-less motion capture out in the field.
[00:18:27] This is not only increasing the resolution of the data, but also its complexity in many cases. We're able to look at these things continuously, and of course we need to find analysis tools that help us with it. So I think the technology is driving us there through the types of data that it brings out, and that's where it does become a necessity. If organisations aren't picking up tools that can handle that data, they simply won't be able to use it anymore. So I think that's another consideration.
[00:18:52] And so that probably provides a nice segue onto tools, full stop. What tools can people typically call on to handle complexity? And when I talk about complexity, I don't just mean handling it, but I mean, firstly, probably recognising that a situation is complex or a complex systems approach is suitable, and then of course being able to measure that, embrace it, and of course, like we always want to do in sport, leverage that to create a competitive advantage.
[00:19:17] So when I talk about tools, you know, that could be an artifact, a theory, a framework. I know you've done a lot of work with cognitive work analysis in some of your papers applied to sport. What are some of the things that you've had success in, in sport already, or you'd like to address in future?
[00:19:32] Scott McLean: Firstly, like, complexity science is massive. There's a brilliant map of complexity by Castellani, which demonstrates all the different theories, methods, analyses, models, and then their evolution across time. So I'd suggest people have a look at that. But yeah within that, I think there's over 50 or 60 different of these subdisciplines within complexity science. So it's huge.
[00:19:50]We typically use methods from systems ergonomics and we use this for a number of purposes. So for design, redesign, risk assessment, behaviour of systems, But again, a major focus of these is on those connections between the components. So you mentioned there cognitive work analysis, particularly the first phase of that, which is called work domain analysis, we've published a few papers in, which sort of gives us a map of the functional structure of what a system is. So within that, you'll include the goals of the system, how you measure those goals or how you're achieving those goals. All of the functions that need to be completed or performed to achieve those goals, right through to the physical objects in the system, what they do within the system as well.
[00:20:30]We've used that quite a bit with a few different sporting teams. So with netball, AFL, para-sport, at the individual level, in talent identification, performance in a football match, we've applied this, we actually call it the hammer cause you can just apply it to everything. It's just a big sledgehammer.
[00:20:46] But I think one of the other, and Paul can probably talk more about that in a minute, but I think one of the great things about systems thinking methods is that, they can be really basic using a pen and paper, or they can be extremely complex using computation and modelling. But I think whatever method you choose, you're going to actually get some insights into the behaviour of the system or the structure of the system. So, yeah, I guess in terms of choosing a tool it would depend on your expertise and your budgets and all that sort of thing, but just jump in and get into systems would be my advice.
[00:21:15]Paul Salmon: For me, you know, the key tools are these modelling tools or methods that we use. And really it's quite interesting because the methods, and indeed the theories, are a risk to complexity science in sports science, or a weakness of it, I don't know which one's the best way to say this, but there are a variety of tools available. So we have a different set of tools that we can apply based on project needs. So, you know, causal loop diagrams where you're modelling feedback loops and interactive loops within a system that influenced behaviour. We have systems analysis tools like work domain analysis that Scott talked about. There's STAMP systems, theoretic accident modelling and processes tools, which looks at the hierarchy in a system and all of the different controls that exist around behaviour. And then there are computational modelling techniques, like system dynamics, agent-based modelling, more tools that I don't really understand, the complex mathematical modelling tools that kind of have a role to play in complexity science as well.
[00:22:10] But I think the key thing here, and it's really interesting and it's something certainly we're interested in in the work we do here in the centre, is there's a big research practice gap with these theories and these methods. So what you have is a set of academics who are well across these theories and who are applying these methods and modelling tools in various areas of sport, and much less use of these tools in practice, and that's for various reasons.
[00:22:33] Practitioners don't have good access to the tools, they don't have access to training, things that are behind firewalls and all of those barriers that kind of limit research translation. And so what you can, and I've seen this before in other areas, particularly in safety, you get this idea that, well, it's just these boffins in their ivory tower applying these methods. They mean nothing for practice because nobody's using them. And I think that is a really big threat to complexity in sports science, is that really there's not a lot of expertise or use of the methods in practice.
[00:23:02] And actually we saw this in a webinar that we run last year, which I think had about 120 people turn up to the webinar where we presented on some of the principles of complexity and so on. There was just a massive demand after that webinar for training in the methods. You know, people kind of, we really want this approach, we really think it's really interesting, we want to apply it, but what methods are there and how do we actually use them? Where's the training for these methods? So I think there's lots of tools available, but I think there's definitely work to be done in terms of, I think it's on us as well, the research is actually helping to translate these methods in practice.
[00:23:37] Scott McLean: Just to add to that, the approach that we take is we build models with the organisations or the club or whoever it might be, and we use them as the experts. So they're sort of involved in building their own system model. And they get really good buy-in from that as well. They're actually often quite blown away that when we point out to them like, okay, this is the goal of your system, but you've got nothing, you're performing no functions to achieve this goal, but you still think this is a goal of your system, or, you know, this is a goal of your system, but you're not actually measuring this goal in any way so how do you know if you're achieving this goal? And when the experts and the stakeholders of the system see that they take a step back and go, right, we need to change this and redesign our football program, which is what we did earlier this year, last year, I get confused with years of through COVID, but with one of the AFL football clubs, we did a project with them and yeah, they went away and changed their whole structure of their system based on this analysis or, you know, parts of the system based on this analysis.
[00:24:31]Sam Robertson: What was coming to mind as you were speaking was the diversity of this, and you used the term the hammer, which I liked, but the diversity being such a strength that just about any problem that someone's coming to you with, or an organisation's coming to you with, you can actually provide a tool. As you were giving that last example, Scott, my mind went to this notion of mapping someone's mental model of an area, which is similar to the example you gave.
[00:24:53] It also made me think a little bit about the workforce in sport, but also in academia. And it's a topic we've spoken about ad nauseam on this particular show, but I feel like I think academics get a lot of stick and a lot of it's quite rightly justified for sitting in the ivory towers, but I also think the training has let us down in sport. We are still very discipline-heavy in the way that we train our sports scientists, and I think there's massive gaps and this area is one of them. But again, that's not just limited to sport, as we know.
[00:25:22] And of course that's the same in sporting circles and I don't know which area will improve quicker, whether it'll be academia, or professional or high-level sport. But I feel like they're both lagging behind a little bit. And again, they're not the only ones as I say, but they certainly are.
[00:25:37]It might be worth at this point talking about your own journeys just briefly in terms of, how did you arrive getting involved in this in sport? I mean, was it something you were driving towards or did he see the gap or was it through demands?
[00:25:49] Scott McLean: I'll start. Like, I did a Bachelor of Sport and Exercise Science and then a Master's where I was looking at muscle oxygenation in thigh muscles. And so, I mean, you can't get more in the weeds than that. And I happened to get introduced to Paul and we talked about doing a PhD together and he introduced me to this system stuff. And because I'm also a coach and a bit of a practitioner in sport as well. So going from this narrow, focused, in-the-weeds type thing to this systems thinking, I was quite blown away with it and the power of it that you can have over, so that, as I mentioned earlier, that looking up and out rather than down and in, has really sort of helped me along as an academic, but also as a coach, yeah.
[00:26:28] Paul Salmon: Yeah, my journey is an interesting one. So I'm actually a failed sports scientist at heart. So I did an undergraduate degree in sports science.
[00:26:34] Sam Robertson: What does that mean, Paul?
[00:26:37] Paul Salmon: It means I did a degree in it, but then really, and I guess it points to some of what you're saying, I remember being called into a lecture room and the lecturers kind of say, look, you've got your degree in sports science, but you're not specialised in anything so you need to go and do something else. And about that time, a master's degree course in applied ergonomics came up and I knew about applied ergonomics cause in the sport science degree we'd looked at football boot design and anthropometrics. So I thought, well, I have got nothing better to do so I'll go and do this master's degree.
[00:27:03] And on the master's degree, there was a module on basically accident analysis and investigation, and systems thinking was a part of that and I was just completely blown away by, you know, these broader kind of theories about how people behave as they do in certain situations. And so I completed a master's degree, I did a PhD in human factors and then spent a few years working, you know, looking in safety and optimising systems, but I was always thinking these methods could be used in sport. Like we're understanding the broader influences on why people behave as they do, why aren't people using them in sport science.
[00:27:36] And so I wrote a book in 2009 - 'Human Factors and Ergonomics Methods in Sports Science'. Nobody bought it, unfortunately, but I was always thinking like that. And I think I was always looking to connect with people, but I had too much work going on. And then when I met Scott, he was kind of the first person who I'd connected with who understood sport. So I had somebody who understood sport who could actually help me, rather than me just trying to understand sport from a different discipline, if you see what I mean.
[00:28:03] And I think from there it's just skyrocketed. We've just been able to kind of use methods and theories from complexity science that are used for other purposes, but we can really see that they have real power in applying them into sports science. So I think it's a beautiful meeting of minds between the two of us in 2016, I think.
[00:28:21] Scott McLean: And Paul always claims that, cause you know the pioneer Tom Riley was an ergonomist as well. So Paul thinks there's something in being an ergonomist and then going into sports science.
[00:28:30] Paul Salmon: That's it, that's it.
[00:28:33] Sam Robertson: In all seriousness, it does seem like there is a relationship between generalists, or people with multidisciplinary backgrounds, and finding their way to this space. There's no question in my mind about that. Which does beg the question then, how do we ensure that these people with these viewpoints or with this way of thinking are making their way into academia and sport? And I don't have all the answers there, and I know we're not going to solve the problems of sports science accreditation in Australia, or indeed the world, but do you have any thoughts on that?
[00:29:03] I mean, is it as simple as ensuring we're providing platforms such as this or conferences for people to come together? I know there's a complex systems in sport conference due in September in Germany, which unfortunately won't be taking place in person obviously, but even that is a sign, and that's not a new conference, but even that is a sign that there's opportunities now for us to get together in this area.
[00:29:25] Scott McLean: Yeah, definitely. This conference is great. I think a lot of the time I find that I do my reading and stuff, and watching these sort of webinars and conferences, is that the complexity they talk about is quite different to the work we do. So, I mean, we look at systems complexity within that higher level. So the club, the organisation, so the football association, for example.
[00:29:45] But I think there's a lot of complexity stuff that is still at that individual level, which I'm not saying is bad, it's fine, and then dyads and triads and all that types of things in team sports. And like we mentioned earlier, I think having that broader perspective of how the overall system, like that societal system, impacts performance, for me, I think has got much more, you're able to just draw a lot more from that I think then at that individual level, or that sort of sub-individual level.
[00:30:11] Paul Salmon: I think there's something interesting about how open and how embracing sports science is to other perspectives. I think some of the earlier work that I was certainly involved in, I kind of felt this reticence, and I'm talking academic journals here I think I should clarify, there's a kind of reticence to publish work from other areas that was using other methods that weren't recognised as the sport science type approach. And I think actually working with Scott and another guy who's core supervisor, Dr. Colin Solomon, I think they really taught me that you have to write in a certain way to get published in sports science journals and you have to acknowledge a certain set of literature and things like that. So I think there could be perhaps something around how open the discipline is to other perspectives and, you know, certainly in my discipline, which is human factors and ergonomics, it's actually seen as a really good thing to actually bring in other perspectives, and the journals certainly are very excited about that. They potentially see that as more publishable and interesting than the old kind of stuff. Is that the case in sports science? I'm not sure.
[00:31:14] Sam Robertson: Moving on, I wanted to talk about some applications that either you've had success with now, you mentioned injury, you mentioned already the design of high-performance teams, which is a topic we've covered on this show as well. What do you see as the next big area to impact on? Or is it continuing to be those areas? I guess that's one part of the question, but what's going to need this area more than others? Scott, your example then about the big picture of sport, the socio-cultural influences, looking at it from a very high level, that's always going to be of importance to the organisation, the general manager, to truly capture that state.
[00:31:49] And of course, the other example you gave that the practitioner at times may need to look at coordinative behaviours between limbs on athletes, and it's very much more down at that individual level. So, very broad question I know, but where's the real opportunities coming from, considering all the things we've spoken about already today?
[00:32:06] Scott McLean: For me, and the one that we're going to tackle next is, doping in sport. So we're about to undertake a project funded by WADA on the systemic influences of doping on athletes. And athletes, and we've already talked about this today, but athletes don't perform or don't operate in this societal vacuum. They have all of these external things going on. Our argument and the theory that we're going to use and Paul mentioned before, it's called STAMP, which looks at the controls across all of the levels of the system. So we're going to hopefully demonstrate that you can't just blame an athlete for doping, or the coach for providing them with a substance, there's failures across the entire system and all the actors in the system, and that's coming from WADA, down to governments in Australia to, say, Athletics Australia or Football Federation Australia, there's failures at all those levels until it gets down to the athlete. And hopefully we're going to be able to provide some recommendations to stop that.
[00:32:58] And also the other big one, and Paul might want to talk about this a bit more, is that the sexual abuses in sports or some of these real big issue topics. I think racism in sport can be tackled from a systemic level that we sort of look at. And then there's the impending doom of artificial intelligence on sport, where we just recently wrote a commentary around how advanced AI, the influence it's going to have on football, that might even change football to be unrecognisable to what we know it today. So there's some of the bigger issues that we're about to tackle.
[00:33:27] Paul Salmon: Yeah and I think all those areas that Scott's mentioned are very interesting to us, and we'll certainly be applying methods to try and understand and prevent some of those issues.
[00:33:36] I think for me, I think it's money where your mouth is time, for complexity in sports science. So what I'm really keen to do is, which you touched on, is to kind of do some of the modelling that really teases out these broader systemic influences on performance. We published a paper recently where we showed how you could take a complex systems approach at a football match level, you can do it at a football club level, you can do it at a football league level, but I guess I'm interested in even broader, in as you mentioned, the societal level and what those factors are that kind of influence game performance effectively.
[00:34:08] So I think there's modelling work to be done there, and I think then what I'm really interested in is, and we haven't really touched on this yet, but the Donella Meadows kind of view that there are leverage points in systems where minor changes can have dramatic effects on behaviour. And the really interesting thing is nobody's really looked at where these leverage points are within sport. And so for me, there's a big challenge there to actually say, well let's model bigger, broader sports systems, and then what are these leverage points? Are all of the leverage points within a football club to improve football performance? Probably not, but I think, yeah, it's money where our mouth is time because we have to actually explain what these leverage points are, where they exist and how we can pull them. And I think that's very challenging, really exciting, really interesting work. And I think that's what we're trying to do basically over the next few years.
[00:34:53] Sam Robertson: Sounds like you've got a busy time ahead of you both as well as your team, tackling some of the big ones there and that's fantastic, and I think if you can have success in those areas, whatever success means, that's certainly going to help this area.
[00:35:04] And Scott, the interesting point you made then on athlete's not existing in a vacuum, and I think that's a great example there. I think social media has insights, almost pulled back the curtain on athletes in that perspective there and allowed people to realise that they are living in the same society as us, so they're facing the same challenges a lot of the time.
[00:35:24] I wanted to pick up on that point, Paul, around certain elements of complexity perhaps not getting picked up yet as well, either in popular culture or in the research full-stop or in the sports research. And you mentioned the notion of levers and hubs being one of them. I wonder whether there's others that are not getting prioriti sed, either because they're just not getting prioritised or they're not as well understood.
[00:35:48] I think in my own experience, one of the frustrating elements of complexity or a complex system that isn't well-recognised in general terms is a simple notion of change over time. I think sport makes a lot of decisions for the short term and sometimes that's well justified and other times it's not. I mean, it's actually a debatable question about what success looks like for organisations in sport. Is one championship win followed by 10 years of horror a success? I mean, it's actually a philosophical question in and of itself. Do you have a comment on that? I mean, that's one for me that I find is really overlooked.
[00:36:23] Paul Salmon: No, I think I totally agree. I think there are other things that are overlooked. That is one thing that's overlooked. I think that whole, like what you mentioned about success and one period of success followed by a period of non-success is really interesting in its complex systems. It's a system behaving in a certain way, the system responding, and so on and so forth. So I think that aspect of behaviour over time's interesting.
[00:36:44] Another one I'm really interested in is feedback mechanisms, which again is very simple, but it's a key kind of tenant of systems thinking, complexity, but we know that in most sports systems the feedback mechanisms are not particularly great. And the most obvious example is injury reporting systems. How do you gather data around injuries, aggregate that data, identify trends and so on. We've been, I think, quite surprised where there'll be sports systems that just don't have them at this kind of system level. So I think there are all sorts of different aspects that have not received attention, can be very powerful if we do some good research around them and start to tease them out. So I think, you know, the future is certainly bright for this as a research area in sport. Definitely, absolutely.
[00:37:27] Sam Robertson: Yeah the example that comes to mind from my experience working in sport there is around training design. When you talk about feedback, I think I'm probably considering the word evaluation as well, but yeah, when we talk about feedback, I think we do a reasonable job at looking at how the athlete responded, but evaluating whether a session or a training or a practice session actually went how it was planned, for example, and reevaluating it and refining it from there is something that's absent a lot more than I perhaps thought it might be, in some sports.
[00:37:56] Coming back to the notion of tools, and you gave some examples in the last response about practical tools that you've used in sport, or you will use in sport, for different problems. An issue that I've grappled with in my own research is the notion of when you make something so simple, whether it's a tool or a report or anything. that it actually ceases to capture the complexity in that system. And this is a very tricky question I think. It's essentially, by dumbing something down, which is essentially what we're doing, do we cease to actually capture its true state?
[00:38:28] So the example might be, if we want to characterise the key reasons as why an athlete has transitioned from an eight year old taking up the sport for the first time through to becoming a world-class performer. The small, seemingly meaningless occurrences along that journey, if we remove them from the story, do they end up in that same place? Do they end up being a world champion or a high-level performer?
[00:38:52] And I guess to provide another example that's actually from my own work and research, if we look at the example of skill, which is an interest of mine, let's look at the example about how an athlete passes or shoots or kicks the ball in a team sport. We know that things like the pressure they're under, their fatigue, the number of passing options they have available, the time they have, these are all things that are really important, and to characterise those and to provide a report into the insights or the influence they have on that performer is pretty easy to do, and we can even look at the relationships between them. But the point is, there's an everlasting, an endless laundry list of other things that are somewhat influential, maybe not as influential, but if we look at a team sport kicking example, the wind, the surface, the rain, the weather, did they sleep properly? All these things matter. How deep do we have to go before it ceases to capture the state? I don't know if there's an answer to this question. It's a tricky one.
[00:39:45] Scott McLean: For me. I think it's about defining the boundaries. And I was listening to one of the earlier episodes and one of the other guests was talking about, you know, a cell is a complex system, an individual is, a team is, an organisation is, and so on. I think if you can identify what the boundary is as the limit to what you're trying to look at, otherwise, like you say, there's people out there that think you need to go all the way back to the big bang to understand all of the systemic influences of how we got here. But I think when you're trying to, we do it in there in our research centre, we'll explicitly state in our methods sections that the boundary of this analysis was X, Y, Z. But I think it would be the same for coaching as well. Make clear boundaries of what you're trying to achieve and then don't try and look too far outside of those boundaries or stay within those boundaries, would be my advice there.
[00:40:30] Paul Salmon: Yeah, I think to add to that, I'm a firm believer really that the best approach is to really embrace complexity, and you know, the second that you try and reduce complexity down to a set of manageable variables or factors, the second you do that, you're no longer considering complexity. So I think it's definitely important not to try and reduce things down. Safety again is a good example about the fallacy of the root causes. It's been shown quite clearly that there's really no such thing as a root cause when you're looking at accident causation, for example, and I firmly believe the same is in sports performance.
[00:41:02] And so I think you have a boundary and you should be modelling everything within that boundary as far as you can. I think the big challenge though, and again, this is more research for us to do, and a really big challenge is we need to start weighting those interactions between things. So we need to start to understand, and I've mentioned leverage points, which out of those 27 factors that influence behaviour, which are the really strong leverage points that you pull that can actually have a massive effect on behaviour. And I think that's a challenge for the science. There are methods that try and do that with things like system dynamics modelling, agent-based modelling, but yeah, I think that there's a big challenge around that. And certainly we've been wrestling with that in our models about, well, yeah look we understand that there's 75 things here that will influence an athlete's performance, but can we weight them in some way to actually tease out which are the most stronger ones to focus on?
[00:41:52] And of course the bigger problem in translation there is that often going to an organisation and saying this is a very complex problem, there's 73 factors that you need to tackle, they can't tackle them all. So they need to know where their best investment is made, and I think, yeah, that's a big challenge for the science.
[00:42:08] Sam Robertson: I get into trouble from my producer every time I mentioned the term interdisciplinarity, she tells me to keep editing it out cause we mention it every episode, but I think this is a great example of it. My mind turns to things like Bayesian networks and statistics machine learning as opportunities to build parsimonious models, or models that fit and generalise well over time. And of course, you know, the more elements we add to a model, the less likely in general terms it is to do that.
[00:42:33] But then again, reporting it back to your industry or to the applied area, it's elements of cognition there, there's psychophysics of visualisation, there's all sorts of different fields that can contribute to that and that's exciting, but it also means we've better get ourselves together. And as you said, Paul, it's put the money where the mouth is time, I think, and got to practice what we preach a little bit.
[00:42:51] Now, before I let you both go, I wanted to finish as I normally do on a little bit of a future question. We've probably touched on this throughout to some extent, but where's the future of this area go? You've got some exciting projects in the short term coming up ahead. Is it a world where we're breaking down the sport science disciplines and we're not teaching through the lens we're teaching now? Is it a reimagination of roles in professional codes? Where would you like to see this head and where do you think it might head?
[00:43:18] Scott McLean: For me one of the things I think is under-done in sports science or in sport performance is risk assessment, like formal and proactive risk assessment. I'm lucky enough to be in Paul's centre, which, you know, we do also research in road safety obviously we've talked about, but also military cyber security, what else would we do, Paul? Anyway, so we've got these broad, I guess we could call them safety critical domains a lot of them, and within safety critical domains there's this huge focus on risk assessment. I think sport doesn't really value what formal risk assessment is. I mean, I've been in video rooms with coaches where they've talked about opposition tactics, and it's like, this guy's fast we need to be aware of that, and that's their risk assessment. That's probably about sometimes the depth it goes to.
[00:44:01] Obviously you will get coaches that'll go to more depth, but, you know I don't like to pump his tires up too much, but Paul was one of the world's leading risk assessors in the work that he's done across all of these safety critical domains. Yeah, like I said, I'm fortunate to be in this research centre where I can just sort of listen and learn from all these others, what they're doing in these other domains, and I can think, well, that would work in sport, or why aren't we doing this? And some things that come to mind, transfers at football clubs, how often do we see them go wrong? And they would look at the surface risks, but I don't think they would be delving into the sort of risks that would happen, you know, in a formal risk assessment that would happen in say a safety critical domain. So that's one thing where I think sport performance can really advance itself.
[00:44:40] Paul Salmon: I mean, what I would like to see, and I guess there's a difference between what I would like to see and what is actually gonna be happening, but I think it would be really great if we saw some way of having much more transdisciplinary research programs, where you have these different thinkers all connected on sports science issues. And a big challenge we have, and something I'm really excited about in our research, is yes the systems thinking and, you know, we think big and we think about all this other stuff, but that doesn't mean the kind of sharp and reductionist stuff is useless. And actually, surely it's more powerful if that's all integrated.
[00:45:14] So I think there's a real interesting dimension there where we can see really transdisciplinary research teams on sports science problems, where you have all of these different thinkers working together rather than as a kind of 'we're better than you' or 'we know more than you' type approach. So I think that's one thing I'd like to see, and I'm not sure how that's facilitated.
[00:45:32] I think the other is what I mentioned a bit earlier, is around evidence. We need to be developing rigorous research programs that clearly communicate the benefits of a complex systems approach. And again, that's very challenging, but I think that's needed. And so I think a very exciting research area there.
[00:45:48] And then the final thing, in the kind of longer term, wouldn't it be great if sports organisations had a complexity scientist or a systems thinker within their own teams, you know, that's kind of driving this kind of work at the coalface, and that would be extremely exciting. A long way away, of course. But I think the things around evidence and actually demonstrating the benefits is one of the things that needs to happen to get to that.
[00:46:10] Sam Robertson: I think they're all great suggestions from both of you and I'd be happy to see some of those come to fruition. And Paul, you've even gone one better than interdisciplinarity there, you've gone to transdisciplinarity. So you take the award for this particular episode. But thank you both for joining me on the show, Professor Paul Salmon and Dr Scott McLean, it's been a real pleasure.
[00:46:28] Scott McLean: Yeah, thanks for having us, Sam. It was great.
[00:46:30] Paul Salmon: Yeah, thank you, that was a great discussion. Really enjoyed it.
Final Thoughts
[00:46:38] Sam Robertson: And now some final thoughts on today's question. It's clear that the adoption of complexity science and practice to sport is at a crucial juncture. Yes, there's a growing recognition that it's now more viable than ever before, but whether or not it experiences a lasting uptake is dependent on a number of factors.
[00:46:57] Perhaps most notable will be whether key decision makers and organisations can see its value. This will be difficult to prove on multiple levels - the traditional cause and effect way of thinking that we so often subscribe to, is indirect opposition to the inherent nature of complex systems. Also, as we've discussed in this episode, pseudo-complexity has already worked its way into academic publishing and sporting practice. This presents a risk for complexity being 'tarred with the same brush' as many other recently failed ideas in sports performance. Consequently, it's paramount that the true nature of complexity is upheld by those looking to increase its uptake in sport, if we truly want it to take root for the long haul.
[00:47:40] For those proponents that do manage to gain traction with these ideas in their research or practice, it will typically be accompanied by some period of stakeholder upskilling, and in some cases, a complete transformation of the philosophies of an organisation. However, these potential risks to embracing complexity in sport, also present opportunities, the sheer breadth and diversity of the area mean that it's far more accessible than many might think, with a range of readily available tools to suit any skill level - even if these still require further PR work to illustrate the directly translatable benefits.
[00:48:14]With a growing recognition that discipline-based sports science has taken us as far as we can go, adoption of complexity science to sport could be one of the stimuli to take us to never before seen levels of performance.
[00:48:26] I'm Sam Robertson, and this has been One Track Mind. Join us next episode, where we'll be asking: Life after sport - how can we help athletes transition?
Outro
[00:48:38] Lara Chan-Baker: One Track Mind is brought to you by Track and Victoria University. Our host is Professor Sam Robertson and our Producer is Lara Chan-Baker - that's me!
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