Stop Fixing Symptoms: How to Think in Systems in Pro Sport (Scott McLean)

What Systems Thinking Actually Means in Sport Scott, for someone hearing systems thinking for the first time, what does it actually mean in plain English? In sports terms, it's. Speaker 2 A good question. I guess it's AI guess before you get to the systems thinking part, it's I guess you have to recognize that sport is, I guess characteristic of a complex system, right. So you've got all of these different parts that interact to create something like, you know, you call that talk about that as emergent. So there's this emergent behavioral property that comes out of the the interactions between all of those different components and those components can be human as well as non human sort of artifacts within the system. You know, so you've got, yeah, technologies like GPS and all the devices you measure stuff with so, but also, you know, game artifacts as well, so matching training facilities, all that stuff. So that all interacts with, you know, coaches and players and support stuff and all that sort of stuff. So I guess the first part of it is to understand that it's a complex system. All those parts interact and I guess then the system's thinking part of that is then I guess resisting that urge to break down those components on their own and look at them individually, which I think where sport is has been for a long, long time. So and then I tend to think about it as a bike. Let's think about a bicycle, for example, as a good, as a good analogy. I think everyone knows what a bike is, but so there's a lot of parts that are put together and yeah, and together they sort of make a bike. But I guess with a bike, for the example of the bike is it's, I talk about it as like a mechanistic system. So, you know, I push on the pedal, the chain moves, which makes the wheel move and it's very got very much like this linear sort of cause and effect. So, you know, I push here, this happens and that happens and it's got a very predictable linear outcome. I guess the difference with complex systems rather than like a complicated system like I would, I would classify a bike as a complicated sort of mechanistic system is the difference between that the nonlinearity of a complex system. So you know it, you can't, you can't take a complex system apart, understand the parts and put it back together. It just doesn't work the same as a bike because of this nonlinearity. So I guess systems thinking is trying to understand how it all fits together and not reducing down, but looking at the system as the unit of analysis rather than, you know, pulling it apart and it trying to, you know, it might be a broken part. You know, our passing this week was bad. So, you know, do we just start doing passing drills and then try and introduce that back into the system? It's probably not going to change a lot of the other stuff that was leading to the bad passing, for example. So I think reducing things down to its component parts doesn't quite work in conflict systems. And I mean the work that I've done, you know, and, and I'm sure you're familiar with it as well as the stuff in, in sport is trying to understand all of those factors together. I guess there's a quite a long answer to a simple question, sorry. Speaker 1 Well, to quote Meadows, we can't control systems or figure them out, but we can dance with them. Dancing with Complexity What does that mean for you? Speaker 2 Yeah, I really like that and and I've used that in some some writing that I've done. It's like, I don't think, you know, I don't think humans are capable of understanding the complexity of things. I mean, you know, take the human body for example. I mean we don't understand that. But then on its own, but then you interact the interactions with the human body and everything else that happens in sports, sleep and fatigue and load and travel and all these different things. I don't think we'll ever fully be under be able to understand, you know, the the inherent complexity of all those things. So I think what she's trying to say is that, and the way I take it is that we'll never understand complexity, but we need to be able to be adaptable and sort of learn from it on the fly. So I think, you know, the way my takeaways from that is that if we're really rigid in our approach to sport and how we understand sport and that rigidity and that sort of certainty that maybe data we think might give us something with that reductionist approach. I think it's, it's, it's, it's the wrong way to look at things. And I think what she's saying is we need to be adaptable. Listen to what the system's telling us, adjust, adapt. And yeah, that creates some resilience in there as well because of that adaptation. I think you know that that's the way I take that is that, you know, I guess you know, the dancing, the dancing component of that quote is like, you know, the music happens as the music happens and you adjust your dance moves accordingly. I guess is is is a good way to put it into sports terms. I mean, you don't want to see my dancing, but maybe maybe Meadows was a good dancer. So, you know, but listen to what the system's happening and just be adaptable. Don't be rigid I guess is my take away from that. Speaker 1 So if we were to say that you now dance with systems, So what is your, what is your current role? What does that look like and how did you get to what you're doing now and what it is you're interested? Can you explain a little bit about your journey? Speaker 2 Yeah, sure. So my background, my educational background was a sport and exercise science degree. I sort of got to the end of that and said what next? You know, I didn't feel like I had all the answers that I wanted to get. My goal was to go on via physio. I think that was my initial goal, was it to be a sports physio or something like that. Scott’s Academic Journey So I did a master's after the undergrad in exercise Physiology. So I was a master's by research and essentially we had these these devices that measured muscle oxygenation during exercise. And so we did, I used that and tried to work out, you know, recovery periods until your muscles re oxygenate, all that sort of stuff. So really at a quite a cellular level. Found that quite fascinating. Then I had a bit of a chance meeting with a professor at the University of the Sunshine Coast here, Professor Paul Salmon. And you know, we both had a love for football. You know, unfortunately he's a Manchester United supporter. But you know, we, we sort of hit it off around football. And he said, well, why? And he was a director at the time, he was a director of a sense of human factors and sociotechnical systems. So essentially plying a lot of human factors safety science, you know, some of these these system science methods to a lot of safety critical domains. So defence and road transport, you know, healthcare, AI, security and, and safety and all those types of areas. And so he said, and I said, you know, that's 1,000,000 miles away from where I was. And he said, he sort of said something along the lines of, you know, but once you start to see things from the systems level, you'll see things completely different. Anyway, I jumped in, did the PhD sort of at that time I had no real goal where I wanted to be. I just thought it was interesting. So I thought I had to go, which might be a good lesson for some young people thinking of career choices. Just follow what you think is interesting, I guess as a, as a side note. But yeah, so then I just did my PhD and I, my PhD was around football performance from that sort of systems perspective. You know, from there it sort of just evolved into all of these other projects along the way. So I mean, I was really lucky because you know, the centre, the research centre that I was in, they, we did, like I mentioned, work across all those different domains and I was able to, you know, work across those projects. And I guess my role, because I was the theme leader for sport and outdoor recreation. And I guess my role was then to sort of translate some of those methods and approaches and learnings from some of those sort of safety critical domains and bring them across to sport, which, you know, eventually it worked out actually quite good because, you know, a lot of those theories and methods and approaches applied really well to sports and some of the incident causation stuff around injury, sort of understanding the functions of systems and how they, you know, how the system creates behaviours and all those types of things. So it is. Yeah. And you know, 10 years later, I sort of had had enough of academia. That's a whole another podcast. We can, we can talk about that. But yeah, so the last sort of, I guess, yeah. Since May 2025, I've just been out of my own doing some consulting work with, you know, some, some some football clubs and some anti doping bodies in those types of areas. But you know, I, I guess my work has really sort of tried to tackle these really wickedly complex issues that sports face. So, you know, things like injury, anti doping. What else have I done? Like sort of, you know, competition manipulation, match fixing, child safeguarding in sport, well-being, you know, player sort of player transitions in football, which hopefully we'll talk about. Yeah. So lots of different sort of areas across sports, which is I guess really shows the flexibility of these systems thinking methods as well. I mean, they can sort of, that's sort of generic enough to be applied to to any problems in sport, I guess. Speaker 1 Yeah, it's so interesting. And before we get into some of the projects, because I definitely want to speak about those, can you just explain a little bit about your PhD and how Paul, your supervisor brought in some of those? Was it safety critical domains analysis into your PhD? Speaker 2 Yeah, sure. So essentially what look, I was interested in football, soccer, football. So I wanted to sort of understand a bit more of how all the parts of it were connected. Communication as a System Variable I guess was this for sort of first aim? Because as I mentioned, you know, a lot of it had been sort of that reducing parts down to their individual components without sort of understanding how everything interacts. So I guess the first part was to use a a method called work domain analysis, which is a method that sort of understands like the functional structure of a system. You know, right through to the purpose of the system, how you measure it, if it's working all the tasks you need to do, but also that all the physical objects in there and how they sort of relate to to getting those functional purposes achieved. Yeah. So it's really fascinating to map out what what that was. And yeah, we we used a bunch of experts with that that had sort of international football experience in coaching and playing. You know, we just pretty so much sat down in a couple of meetings and mapped out, you know, all of the components of football, you know, what's the purpose of a game and how they all interact with one another. And then from there we sort of dug in like I guess one of the things that sort of came out of that and that was really highly connected was like communication within within a team and within a coaching sort of support stuff. So what the next sort of phases was of the PhD was I sort of really dug into those communication phases. So how teams communicated on the pitch, whether it was verbal, nonverbal, how that influenced performance and all that sort of stuff. And yeah, that was that was pretty much it across a few different studies. So really, really good. I sort of, I guess it really whet the appetite for because you know, as you, as you do some reading across all these, there's all these other methods and I was like, oh, I'd like to apply that one. I'd like to apply that one. And then, you know, that was sort of what the next 10 years was like, yes. Speaker 1 It's so, yeah, it's such a fascinating topic. And I think like where a lot of people get stuck when it comes to systems thinking is they most of the time they can understand the concept of it and then go, excellent, I want to apply systems thinking. But the first thing we go to do is we do try to quantify it. And you're saying, you know, you notice that communication was a big part of it. So of course you want to measure it. So, so one thing was, so you've quoted again, Meadows before saying pay attention to what is important and not what is quantifiable. So you obviously notice that communication was important, but was it quantifiable? And how did you then quantify it if it was? Speaker 2 Yeah, it's a good question. Yeah. So we developed a tool, we call it the inter team communication tool. And essentially what we did is we followed an A league team for a season and immediately post match. So we had like quite good access, which was, you know, thanks to the club for doing that. But you know, we had quite good access. So immediately post game we would go in and give the players a survey. You know, how did you interact with this play? Like, you know, how, what was the level of communication and then how did that influence your performance? Quantifying the Intangible And essentially we just built up, you know, like a full season of matches of this, of this data and then sort of analyzed it and sort of see who the the idea was to see who the sort of key communicators were in the team, the beneficial information as well as frequency. And then there's positions of those beneficial communicators. Yeah, I mean, I'm sure the tool has got its issues and it's probably flawed in some, some way or other, like most scientific methods are. But again, it's that it's that quote around, you know, all models are wrong, but some are useful. So I guess some of the findings was, you know, those sort of central sort of spine areas were the key positions for, I guess beneficial communication. So, you know, the central midfield and central defender positions, they were high in, she'd really test my memory here, but they were high in high in frequency of communication in those positions, but also high in beneficial communication. So you benefit to performance. So you know, information giving and those types of things. I mean, there's a bunch of sort of, I guess implications for talent ID and, you know, training, practice and all those types of things that could come out of sort of that knowledge. So, but again, yeah, it was like, you know, PhD level sort of science. You look back at it now and you go, I probably should have done there, so I should have done that. But I think at the time, you know, it's useful and I guess it advanced knowledge a little bit. But I guess in terms of the question of was it quantifiable, we made a tool to make it quantifiable. And I think, you know, my advice would be don't be scared to try and make things quantifiable. Obviously you need to have a bit of scientific rigour about that. But yeah, just talking like this reminds me of, you know, there's a story from the yeah, I don't know if you remember the Challenger disaster. So in 1986 where the Challenger space shuttle crashed, it had the teacher on board. So it was watched by millions and millions of people around the world. So they'd noticed in that some previous launches that there was some problems with these rubber O rings, which is like eventually with AI guess the final thing that failed in that because they had no data on those rubber O rings to say that they were failing. It was just the, it was just the, the engineers sort of, I guess, observations that, you know, there was some burn marks on these things and they didn't have the data. And, and NASA was very much at the time, it was data, data, data. If we don't have data, we're not doing it. So if they had to listen to the engineers who didn't have data, they had subjective observations, you know, that this disaster could have been avoided and, you know, saved everybody's life. So I mean, that's that's an example from safety science where, you know, sometimes you don't need data to actually understand a problem or if that makes any sense. I went a bit off topic there, but that's sort of the thoughts that came through my head as I was talking there. Speaker 1 Well, it's a good point and it goes back to, you know, just working in an everyday sporting environment week. We collect all the screening data in the morning as an athlete comes in. But sometimes the most valuable screening we can do is just ask the athlete how they're going. You know, they might say, oh, actually, I was up all night with the newborn or actually, you know, this is going on at home and, you know, with my missus. And then I'm going to put that down on a, on a Wellness questionnaire often. So like, I think I can completely understand what you're saying. And so I want to know because you said obviously it was 10 years ago and it was PhD science and which still has some merit. So what would you do differently, You know, if you were measuring that? Let's just say you identified that communication was the important factor within the system. So how would you measure it? How would you do something differently? Speaker 2 Yeah, I think, I think that the approach itself was fine. I think probably some more validation around the tool itself could have been done. I'm not sure how that would have been done because you know, you can't really test it on something because every game of football is completely different. So, but it may be some just more rigor around around the tool itself. Why Injury Rates Keep Rising So it was more sort of valid and reliable, I guess would be the only thing. But yeah, I mean, the the the data stuff for me is fascinating. I mean, we're at a time in sport where I guess we've never ever had so much data. We've never had more support for players, you know, in terms of all the protocols around well-being and all that sort of stuff. But the the problems don't seem to be going away, right? If anything, they're probably intensifying, you know, the free. I was reading that Howard and injury index report that comes out of the UKI think, yeah, about the severity of injuries is increasing and all those types of things. And I read some stuff recently about rugby injuries haven't sort of decreased for about 20 years. So we're getting more and more and more data, but the problems are still there. So for me, that sort of tells me that we're potentially asking the wrong questions or we're looking in the wrong spaces. Yeah, I'm, I'm, I'm not sure the answer, but I mean, just a bit of a pattern that I see. If we got all this data, how are we using it or that type of thing? Speaker 1 So as you said, injury rates keep rising despite the fact that we have probably more specialized staff, more staff in general and more data, as you said. So like we're obviously missing something. Do you think we're, we're, like you said, not looking at the system correctly, we're not looking at the interactions correctly? Or do you think actually there's a function of the game potentially evolving and there's now more factors contributing to, let's just call it as a like the intensity of the game, for example? Speaker 2 Yeah, good question. I think I'll sort of answer that in two parts. I think. I think the first part is I definitely think we don't understand the interactions between the things that we're trying to measure. We tend to measure things in isolation. So I think that definitely is a part. I think also we're far too narrow, like you mentioned earlier, you know, we don't know if someone, you know, has had trouble at home or all these broader sort of sort of topics. You know, I'm doing a project at the moment around with the with the Premier League around hamstring injury occurrence. And essentially what we did on that project is we're just trying to do this really big broad map of all of the factors that might interact to create hamstring injuries. Essentially what we did is we spent a day in London. We invited people from, you know, all the Premier League clubs, yeah. We had all of the the usual sort of roles that you would see, you know, strength, conditioning, doctors, physios, psychologists, all of this stuff you would see in performance. So we had a really sort of diverse group of people in this room. And it's essentially we just sort of brain dumped a bunch of factors that we thought might at some point, not directly, but maybe sort of indirectly relate somehow to to hamstring injury occurrence. Drift, Load & System Degradation And I think in the sort of final model we had about 50 ish variables. You know, some of those are very related to the player, you know, bio mechanics of running hamstring strength, for example, all of these sort of usual suspects. But then there was a bunch of stuff around the club as well, sort of at a club level. There was stuff at the athlete support level, at the coaches level, even at the league level, but also the environment. So we were starting to see, you know, there's really a lot to this, to this problem of just one sort of soft tissue injury. So, you know, I think the narrowness that we currently sit at needs to expand and look broader. Yeah, and that and that can be done quite simply. I mean, if if I was just, you know, especially people in a club environment, I think and it doesn't need sophisticated tools. I think you can just sort of sit down brain dump across, you know, the multidisciplinary team. You know, what do we think is influencing this these these problems that we're having? I think as a first step, that's that's really a way to go. So the second part around, you know, is the game evolving? And I think definitely yes. And I think also I'll bring another, I'll bring another sort of safety science analogy into this. So there's this concept that Sydney Decker, who's like, you know, a prominent safety science expert and he talks about decrementalism. It's like how we sort of drift. There's these small little drifts over time that sort of degrade a system's resilience. Or, and he talks about in in one of his books called Drift into Failure, he talks about Alaska Airlines Flight 261, which crashed into the ocean and killed, you know, everyone on board. And the part that they essentially found that sort of failed in this aircraft. It was supposed to be lubricated sort of every 300 hours flying hours. And you know, over time, that sort of with deregulation and all this sort of stuff that happened in the industry, finance, the constraints, all this sort of stuff that got pushed out to 500 hours, then out to 750 hours and so on and so forth to ride out. Till at the time of the crash, it was out to 2550 hours when it was supposed to be every 300 hours when the plane was initially sort of was built. So, you know, he talks about that decrementalism over time. So they're not huge steps over time. They're these little increments over time that sort of degrade safety. And I sort of think about that in football, like European football, for example. Like, and I, I did a little bit digging around after I read that, that part of the book. And it was like the person who won the Balon door in 1995 played 4045 matches or something. And like last season, Luca Modrich played 74 games or something. I mean, you would never expect a jump from 40, 5 to 75 in, you know, across the space of season, you know, over 10 or 1520 years. That seems we get there anyway, right? So, and I think there's this, there's a systems delay part of this, which I'm still trying to process and think through at my home, spread my own thing. And sort of, I don't think that we've evolved enough. And I'm not like a, an evolutionary biologist by any means, but I don't think we've evolved enough. I think there's a lag between the intensity that we're currently playing at and where our and where humans can actually perform at. And yeah, that's, that's just some, some really sort of high level abstract thoughts. But I think there's a lag there somehow, like a delay in that system around intensity we're playing at, but the intensity we're capable of playing at, if that makes any sense at all. I just rambled on for a while. Well. Speaker 1 One first thing that I think of is feedback loops. So whether we're talking about reinforcing feedback loops or balancing feedback loops. And I think as you're saying, there's potentially that delay from say increase training load to potentially more acutely that injury happening. So and then you're talking about things degrading over time. So we could say that that's an athlete playing more and more games as the years go on. So for example, like just to go back to that study you were talking about, which sounded really interesting or the project sorry that you were doing with the EPL and you're looking in hamstring injuries and so on. How do you Was that something you considered looking at how certain things were degrading over time or those balancing or reinforcing feedback loops? Was that considered? Speaker 2 Yeah. So at the moment it was just like, OK, we've got this problem. The problem's been here forever. We've spent this much money on it over this many years and this much resources. The problem is still there and getting worse. And then, you know, I was fortunate enough to, you know, to come into the conversation because around the, you know, the work that I've done in systems thinking. And then I just sort of suggested, let's just map all of the possibilities out and how they interact. So yeah. And that model is, it's called causal loop diagram, which, you know, you you might be familiar with, but that's, that is just full of reinforcing and balancing feedback loops. So what's a good example? So, you know, just trying to think of a variable, you know, so something like recovery might have a balancing feedback loop. So it might sort of reduce fatigue, for example, whereas match intensity would have a reinforcing feedback onto I guess fatigue as you know. And it's a model that's sort of built around all those balancing and reinforcing feedbacks. Yeah, I probably shouldn't talk too much about because it's not sort of published and open to the public yet, but it will, it will be soon. Feedback Loops & Archetypes But I guess the thing to take away is that, you know, there's a lot of variables in there, like I mentioned about 50 odd. And then the areas cover like, you know, athletes, club, league support personnel, coaches, the environment, all that sort of stuff. So I guess the the first sort of point to that is if we're just intervening at the athlete level. So if we're just trying to strengthen hamstrings, get running bio mechanics better, make them sleep better, we're going to miss all that broader stuff around the club and the support staff and all these other areas that are present in the model. So I guess that's that looking up and out rather than sort of more down and in, which is which is the way we tend to go in sport I think. Speaker 1 Can you just touch on that up and out concept because I've saw, I've seen that you've, you've written about that you've got your blog at the moment and you did write a really interesting blog post about looking up and out rather than than in as you said. Speaker 2 Yeah, I guess it's pretty much just what I've explained with that, with that Premier League model. It's like looking at all the factors sort of above and beyond the athlete. I think I, I think you know, at at that athlete level and at that, I think most clubs in the world, they're at that high level, like Premier League type level and equivalent. I think you've got really great people, obviously some of probably the best in the world in their positions. And so you've got this team of excellent people in this system and obviously very good at their jobs and very capable. And they want the best thing for for everybody and the best thing for players and, and the rest of it. But you know, what you tend to find is it's the structure of the system and the way the system is structured that creates these, these, I guess, adverse incidents that you might get. And I guess what sort of approach we're on taking now is that if we can sort of make these teams above the players perform a lot better, you know, with information sharing, you know, having this shared mental models, integration and coordination, I think, you know, that's where some really big gains can be. So I guess that's just shifting one level up from the player level to the support staff level. But then, you know, you can also start to advocate around, you know, I guess fixture congestion, scheduling of fixtures that's even those high levels up. So I think, you know, in that model that I talked about, all of those things are in there around, you know, the scheduling of fixtures, the density of fixtures, the travel, all those sort of things at a higher level. I think we sort of need to start to look at those a little bit as well. So that's sort of what I mean by, you know, at the athlete and then going up and out and what's influencing what's happening at that at that level. So it's at the athlete level where we see the symptoms, right? But it's the rest of the system that up and out piece what is what happens and what those and why those symptoms occur I guess is the message there. Speaker 1 We'll come back to something similar because there is another project I want you to discuss, but first thing I was going to ask was system archetypes. Could you explain a little bit what system archetypes are? Speaker 2 Yeah, I know. I love these. I love reading about. I encourage anyone to go and read about them and I probably won't the Meadows and the like good justice here, but I'll try anyway. So I guess the short answer is there's these reoccurring systems problems. So they're patterns within systems that you'll see over and over and over and over again. And I guess probably the most simple one and you know, one I've written a little bit about is one that's called Fixes that fail. It's essentially we, you have a problem symptom, you apply a quick fix to it, that problem symptom temporary relieves, but you don't address those underlying issues that are driving that problem symptom. But and you know, and they sort of they continue to get worse over time and they drive up those problem symptoms. So it's like, it's like you're constantly putting out fires because you're just you're just putting out that little spot fire, but you're not sort of putting out the furnace that's creating the spot fires, I guess. And, you know, the classic example in sport of fixtures that fail is these the coaches, the sacking of coaches, especially in, you know, European football. And there's like two more this week I saw in the same day at Spurs and Nottingham Forest. But yeah, and we wrote a little bit about this with Manchester United in the Conversation article. And you know, to me from the outside and just looking at the patterns and this, this fixes that fail archetype is quite apparent. I mean, they've had 10 or 11 coaches in in a decade. So you know, they'll have poor performance soccer coach bring a new coach in the performances temporarily increase. And that's, you know, that's scientifically shown in this thing called managerial bounce. So there's a bunch of studies that show when a new manager is appointed, you'll have this in this, I guess this brief improvement in performances. But over time, you know, you'll go back to exactly where where they were before because you don't solve all of the underlying processes. So, you know, at the time we wrote that that Ruben Xamarin had just been appointed at Manchester United and we sort of said, you know, if you know, don't fix these problems, these underlying problems, then this pattern is going to recur again 18 months later. Like only a few weeks ago it happened again and all of those sort of underlying issues came up again. So, you know, some recruitment stuff and I guess all this internal stuff from the club sort of came out as reasons why, you know, I think for a period of time Manchester not have been stuck in this fixes that failed cycle. Fixes That Fail So that's a really good example. There's another archetype around escalation. You know, your opponent does something, so you do something and they escalate and then you escalate. And I sort of see that in like transfer fees and player wages. You know, it's all because of fear of missing out, I guess, you know, so you have to up your game, but everyone ends up in the same place, just at a higher cost of entry, I guess, if that makes sense. And there's a few others around, you know, shifting the burden, which, you know, I'll let you guys go and have a read about those archetypes. But they're quite fascinating. I think once you can start to understand the dynamics of those archetypes, you can start to see really how these we have these recurring issues in in sport. Speaker 1 Yeah. And I think another one you've spoken about before is success to the successful. And I think you see that a lot in in grassroots sports and as players that show a little bit of talent then get selected more often, they're more likely to get better opportunities, better coaching, more attention and so on. And so they effectively become more successful over time. But in terms of say the the fixes that fail, like you said, Manchester have had 10 or 11 coaches in the last decade. So that's just about one a year. So why do you think they keep getting it wrong, even though that you'd think by now they would know better, or they would at least know that that that's not the answer? Speaker 2 Yeah, it's a good question. Obviously, I'm on the outside, you know, I don't understand what's happening internally. But I mean, from an outsider perspective, for me, I guess it's a lot of it's driven by there's this sort of notion that you have to do something, that you have to act within systems. And yeah, and that comes from obviously points table pressure. Media scrutiny in the UK is obviously really, really intense. So there's that as well. There's fans sort of disrupt, you know, there's all of these these pressures externally that that force that to happen. And I think it's the act of, you know, looking like you're trying to do something is what drives a lot of it. You know, obviously some managers might not be a good fit and they need to go. But I think, you know, I think I think giving someone time, you know, like Ange Pasta Koglu example just recently, like he was given what, 40 days or something crazy like that. I mean, what sort of what chance do you have? Right? I mean, and it's the thing I think in the thing in systems, I think especially in complex system, I think if you need to sometimes go a little bit slower to go faster. And I think that sport and the pressures and the intensity of of, you know, everything around it doesn't allow those those patterns to happen is my sort of take on that, I think. Speaker 1 Yeah. And then you wonder how the ones that do survive or potentially thrive get there. And is it a because of previous factors that have led the whole system to be more successful and then the coach is simply just the the cherry on top? Speaker 2 Yeah, I think, I think so. I mean, I just, I just not long ago read that. There's the book called Astro Ball. I'm not sure if you read it. It's about the Houston Astros. I don't know if you know that story. Speaker 1 Better better than money ball. Speaker 2 Yeah. So and that's sort of that that as you're talking there made me think about that is that, you know, they had this process and they had time and they knew they were going to be crap for quite a long time. But it was, you know, trusting the process and, you know, having these sort of indicators of, you know, how you're going to get to this goal. I think, you know, that they went slow, they took it slow and they were proven, you know, to be successful at the end of the day. But but it also there's a piece there around, I think feeding back your strategy, I guess, to the fans and to the media. Like to, I mean, the, the Astros was a good example. They had, you know, I think they had, I was reading the book, they had the T-shirts made-up trust the process. So the fans knew that they were in a process. The fans and the media knew that they were on this path. And I don't know if that's often the case, if, if that's sort of shared with the public more generally. And I guess in European football, it's like maybe if that was shared and you know, that was open and there was feedback to the to the to the community that maybe they'll go, OK, maybe we'll layoff a bit and then in five years we can see where we are type thing. I don't know. But that's sort of what I've sort of pulled out of that Astro Ball book anyway. Speaker 1 Yeah, I think Philadelphia when I was with them had a similar mantra. And when they drafted Joel Embiid, they actually called him Joel the Process Embiid. So and that was supposed to help with the, I guess the fans understanding that it is a process and that they're doing something about it. So yeah, it's interesting because I think, like you said, oftentimes fan engagement, I mean, bums on seats and winning games, that's kind of the bottom line. So you often need to look like you're doing something, whether or not it's the right decision in the long term. I just want to go back to what we were talking about before and a project that you did during COVID with an AFL team that we don't need to name. And we were talked about. You mentioned that the project that you're doing with the EPL players, there's a lot of experts coming in, people who sound like they're really nation, what they do, experts in the area and so on. What was this project you did during COVID when a lot of teams had to go into bubbles? Speaker 2 Yeah, that's it. That was a really cool project actually. I really enjoyed that one. Essentially the club, don't think it's any secret if you read the authors on the paper who it was and their affiliations. But essentially sort of it was, it was right at the start of COVID and, you know, every, everything was uncertain. Nobody knew it was going to last, you know, two months, five years, whatever, you know, But I think they were sort of worried about, you know, OK, we can't have people in stadiums. We're not, you know, maybe then I guess their economic side was going to slide and they were a bit concerned about that. And it was sort of a roundabout. OK. How can we sort of redesign our performance department to sort of cope with this sort of unknownness, I guess. Trusting the Process vs Acting Fast So essentially what we did is we used that method, what I talked about earlier, which was that work domain analysis to sort of model the system as it currently was. Now, what's the purpose of it? How do you measure, you know, what are all the measures and KPI's that you have? What are all the tasks that you need to do all those types of things? And then we sort of assigned all the performance stuff, actors or personnel actors is like a very systems Y term, but all the, I guess all the people within that system, you know, so who does what, who measures what, who's responsible for what, all of those types of things for the system. And I guess it was it, it, it showed some really sort of interesting things, especially like one of the things that was the first things that I remember from that is that it came out as this really highly specialized group of, of people. So, you know, you pretty much had a specialist for every area of, of the, of the, of the football department, you know, and there was all these other things around, you know, some conflicts between tasks in the system. And there was things that, you know, they thought were really important in the system, but they never had measurements for them. And so it prompted like these areas where you can go and take new measurements or do all these sorts of things. But I think the thing for me that really stood out from this project was that that that specialist, that sort of high density of specialist roles. And I guess essentially what happened and you know, everyone probably knows now, but at that time, clubs then went into their little sort of covert bubbles where they would, you know, go and spend the time and that that would be it. So with that, with that bubble, they could only take like this skeleton staff, I guess, you know, they couldn't take all 70 people that were in the performance department. So, you know, one of the things we argued in that paper was that, you know, in a football club environment, you need these more, these generalists rather than specialists or not more, but a good balance, you know, the right balance. You know that there's that book arranged by David Epstein has come out recently. So this is sort of sort of front and centre for a lot of people, this specialist first generalist debate. And we sort of wrote about, you know, because that that sort of hyper specialization it creates. I can create silos within an organization or within a department, you know, where there's might be not information, not be, might not be shared and all these sorts of things. That the other thing with specialists is they're often quite protective of their area as well. So, you know, I'm an expert in this area. COVID Bubbles & Specialist Silos So to me, this is the most important area and you know, which can create those, those silos and those, those knowledge transfer gaps as well. Specialists also bring their own, I guess, language as well that might not be translatable across other, other domains. So there might be specific medical language that, you know, the development staff don't sort of understand. So I think too many specialists within a performance department can I guess disrupt it and create silos. Silos. I mean, obviously we need specialists because they bring very, you know, specialist expert knowledge to a topic. But I think that the balance is having, you know, general, I'd see it as jigsaw puzzle type sort of analogies. So you've got the specialists, they're making the jigsaw pieces, but you need someone to put all those pieces together, right? So you need these generalists in the system. So essentially what happened with the with the AFL teams, They went in there bubble like it only takes, you know, a handful of stuff with them and what it forced them to do was it forced people within that that support stuff to become generalists. People were having to fulfill multiple roles across, you know, what they wouldn't typically outside what they would normally do. And, and some of the feedback we got was it it was great. I mean, there was one story that the CEO was out, you know, picking up footballs and things like that at training and all these sorts of things that, you know, jobs that people wouldn't do before. So become very. Sort of it created, it forced them into having this more generalist sort of, I guess, approach to, to, to, to their roles, you know, And I think, you know, I can't attribute it to, to, to that, but you know, they said it was very enjoyable firstly, but they also had their best season in like 15 years or so. I think they finished fourth or fifth or something, you know, when they'd normally been down towards the bottom. So I mean, obviously, you know, something, something worked out of that, that approach. But yeah, there's loads of studies around, especially, you know, early on studies from 60s and 70s around. So they Scandinavian car factories around how more generalists, you know, within a, within a manufacturing plant, you know, reduces injuries, increases workplace satisfaction, all these benefits to having generalists, you know, So instead of me going in and making the, I don't know, seatbelts every day in a car factory, I was trained to make seatbelts, steering wheels, bumpers, tires, all these different things. So I had these general skills across and you know, yeah, loads of benefits from that. But yeah, have a read of the range book. I found it quite an interesting book if you haven't already. But that was that was good, good case for general service specialists. Speaker 1 Yeah, I'm. Speaker 2 Not saying get rid of, I'm not saying get rid of the specialist you need them. I think it's it's understanding the balance. Getting the right balance is I guess the key. Speaker 1 I did read Range back in 2020 I think when it had first just come out. But yeah it has been a while. I wonder though, if potentially with too many specialists, does it also have this system reliance? So say for example, if I'm just thinking a performance environment in team sport where there are a number of specialists and there's only one person who can do a specific job and another person who can do a specific job. And so as you're talking about the Swedish manufacturers, if that one person wasn't there, then you know the whole production line stops because they could be the first of the downstream effect of creating, making the car because they are the seat belt manufacturer. Speaker 2 Yeah, it's a good point. It's a very good point. Yes, I think, yeah, it builds some sort of redundancy into the system, right. So you can have these fall backs as well if you've got people that are sort of more generally trained, I guess. Yeah, good point. Speaker 1 I just want to pull out another quote for something that you've written before and then that leads on to my next question is something really interesting. I, I would like you to expand on athlete health will be athlete. Athlete health will be optimized through an understanding of how, where, and when to intervene within the broader sports system that contributes and influences health issues. So can you just expand a bit on leverage points and where small changes create big system shifts? Speaker 2 Sure. Yeah, leverage points, another fascinating concept in systems thinking. And you know, it's like the archetypes and all of these other things. Once you start to, once you know them and you can see them, you just see them everywhere. So it actually changes the way that you just view the entire world rather than just sport. But yeah, so leverage points are, I guess there's these places where you can intervene within the system to sort of have some impact on that system. And I guess, you know, the closer you are to the system, the less the less impact that can have on the system. So for example, you know, by simply just increasing something like funding in a club, that sort of doesn't necessarily mean you're going to change the system. I mean, and that's very close, very close to the system level, but right at the far end of the system is changing the mental models around, I guess, how you understand that system. So I guess some examples of one of the ways I've explained this before, which I think went went down really well, is like you think about the plumbing system. Say, you know, a low leverage point would be changing the tap on your bathroom sink. You know, a sort of mid range leverage point would be, you know, changing the I guess the the whole entire vanity. Other one up from that would be changing the the plumbing in the entire house to get better. And then a sort of a mental model change would be like I'll just swim in the ocean instead of having a a bath type thing. So it's like changing, I don't know if that makes any sense, but that's how I tried to explain it to like a young group of kids once. So yeah, the further away from the system, the more sort of, I guess you can leverage, you can have on that system. So changing mental models, changing the structure of the system, those things. So, so examples in support of that, like changing the structure of a system would be something like, you know, the introduction of WADA, for example, was a structural change to the system, which had a big impact on the system. Whereas, you know, changing a, you know, a piece of equipment, for example, would be at a lower level. I mean, it would have some change in the system, but it's not going to have systemic change. It might have benefits at at a very low level, say an athlete, for example, but it's not going to change the entire system. And I think, you know, based on the some of the discussions that we've had already around having to go up and out, I think the further we can sort of intervene away from the system is where we're going to have the most change. Leverage Points Explained You know, I think of something like like like the enhanced games, for example, that's like a that's that's going to change people's mental models around what sport is right. And I think I don't know if people are taking it seriously enough because if it gets legs and you can change people's mental models, that's going to have a massive impact on how things change in that sporting system as we go. Yeah, I mean there's there's a couple of examples. I mean, I probably haven't explained them great, but I'm, I guess they're places where you can intervene and the most, I mean, we've done a project just recently in Rd. safety around drug driving and where, where to intervene to sort of reduce. Because in Queensland here where I am, you know, there's some concern that once cannabis is legalised, there's going to be more people on the road under the influence of, you know, of drugs and that sort of thing. So the transfer department up here got quite concerned and we did a project in the research centre about that. And I guess what we sort of found in that when we sort of simulated some behaviors over time and when we sort of got the biggest buck, bang for our buck, I guess, is where we had interventions at multiple levels of the system. So at, you know, in A at the driver level, at the sort of policing level, but also at a societal level as well. So, you know, intervening across these sort of narrow to broader parts of the system has the, you know, the best sort of outcomes for the interventions, I guess. So, yeah. I, I guess if you want to change a sports system, you're not going to do it at the athlete level. You're going to do it at this either the structural level or at that sort of mental models at perceptions level. Speaker 1 It's so it's so interesting and I, I know you've been, you mentioned WADA before and you've done some work with them. And I think one of the projects you're working on is, is understanding why an athlete would choose to dope. And can you just talk a little bit about what you found with that and where potentially, you know, it's not necessarily always the athletes solely their fault. I want to say I don't because I don't want to remove most of the blame from them because. Speaker 2 Yeah, yeah. Speaker 1 You know they are an actor in the system. Speaker 2 Yeah, it's a good question. And I guess that's sort of the way that we've always thought about I guess, I guess these things is like to try and find and you know, to quote sort of Sydney Decker again is to try and find the broken component. So we always try and, and it's again, it's reducing things down to that root cause, you know, but when you sort of understand systems and the interactions between everything, there's absolutely no such thing as a root cause. I mean, we've done loads and loads of analysis over the years and you know, every, every sort of adverse incident or even success has a number of contributing factors that sort of all interact. So there's no such thing as a root cause. But we still tend to try and isolate root causes and say, OK, this person was the problem. But I guess in the doping context, you know, you know, we've, we've modeled the entire anti doping system in Australia and there's hundreds and hundreds of people in this system. All these controls, you know, policies and best practices and guidelines and all of these things, peer interactions, coach attitudes, all of these different things from across the system, which all sort of nudge the athletes behaviours. I guess when you see these really complex models and the athlete at the very bottom and all of these other things influencing, it's, it's hard to sort of imagine that we can sort of single out an athlete for doping when, you know, the system is all but nudging them into doping in a lot of cases. I mean, you think of like a, yeah, obviously I'm not. People need to be held accountable for their actions. But I think if we're actually going to learn from anything, we need to understand what influenced the decisions and actions of everyone within that system. I mean, a good example would be, you know, like that sort of 92,000 cycling era, you know, when Lance Armstrong was around and that doping was pervasive rights. You can imagine a young kid coming into that system, every intention to be clean, but they weren't going to have a job, they were going to finish last. All these sort of pressures and all these things push that athlete down this path of doping. So I guess it's, it's understanding again, it's the up and out piece. And I'll probably keep saying as we go through, but we need to look at all the influences on behavior, not just the behavior itself. Otherwise we just learn nothing. We can't sort of focus on fixing 1 broken component. I mean, you back to that, that cycle case. If you pulled Lance Armstrong out of that cycling system in that era, could somebody have done what he did? And the answer is yes, because the system enabled that to happen. You know, there was cover ups, alleged cover ups from, you know, a whole heap of different bodies in in that system and coaches and doctors and family members and all this sort of thing. So yes, the system sort of enabled those behaviours to happen. Speaker 1 So with the work that you've done with WADA, have you identified leverage points or places that you could intervene that could potentially influence that system downstream that ultimately influences that athlete to make that decision? Speaker 2 Yeah, I guess in a roundabout way, I think some of the initial work is just has been around showing the complexity of the system as a first sort of step and you know, by showing all the interactions and why these things happen as being a sort of a first step. Doping as a System Outcome But again, it's the same sort of it's the same sort of thing that we talked about before with the leverage points. It's not, it's not by identifying, you know, a single leverage point or finding the silver bullet. It's multiple different interventions at multiple different levels of the system, I guess is sort of what we've sort of identified there. Speaker 1 So I'm just thinking there's kind of a lot of sport practitioners listening and they're thinking great, like, I love this idea. There's so many really cool concepts here, but I want to know how I can start thinking systematically tomorrow in terms of what does my department look like and what should I actually be looking at? So have you got a couple of questions that maybe a practitioner could ask themselves before implementing interventions? Speaker 2 Yes. And I mean people are probably not going to have much success on their own. I think it needs to be a sort of shared, I guess a shared vision of of, you know, the department or, you know, whatever sort of the area they're in. But certainly as a, as a sort of individual practitioner, I think you can definitely understand at least. Yeah. But by starting just to sort of try and map out even, it's just like very sort of unsophisticated pen paper sort of analysis on, you know, OK, here's my problem. I guess the question would be, you know, if I had a athlete come to me with a hamstring injury, you know, the first, the first sort of, I guess the first place you start is you start to treat the injury or the athlete. And then I guess that's sort of, you know, you rehab them, they get them back into sport where, you know, I'm not sure how far questions beyond that would be asked. I mean, that's what I would probably start. It'd be, you know, like, OK, what this is the third hamstring I've had in the last six weeks. OK, what's driving this hamstring? And then you start to understand a lot more about why these things may occur. I mean, that's an injury example. Performance could be quite similar. There needs to be some sort of shared understanding of, you know, coming together to maybe at the end of a match, for example, and saying, OK, we had this result. Why did our system enable us to have this result? Or what in the system force us to have this result? So it's sort of again, instead of looking up and out piece, but you know, with the multidisciplinary team, I think, yeah. But yeah, as an individual on your own, I think it's difficult. I think you need to advocate for, for this approach. And so that's that's where I've that's where I've sort of seen it grow. I think in some of the organizations I work with, there might be one or two people that go, oh, this is great. And then they share it with someone and then they say, oh, yeah, that's good. And it just sort of organically builds like that is is what I've found. Sort of takes one or two people to bring the idea to the group, show how it might be useful, how it might work, and then it sort of expands and then next thing you know, you're doing projects around complexity and systems thinking. That's how I've seen it evolve, anyway. Speaker 1 So it's almost as if you need to sit down potentially with your department or with the entire football department and say like, Hey, let's let's map this out. And it doesn't necessarily need to be a causal loop diagram or work domain analysis, but it sounds like there needs to be a lot of communication. I mean, there's something just keeps coming up in this podcast is oftentimes with influencing athlete behaviour. There is it does require a lot of communication, a lot of trust and then relationships as well. So it sounds like the better your relationship is with your with your staff in this sense, maybe the better questions you can ask and the better interventions you could put at the right levels. But let's just say I were to sit down with my staff if I had a department under me and say, OK, let's let's do all this. How would I go about it without overwhelming them with this introduction to, to systems thinking? You know, like, because I feel, I feel like I've come across quite a few people who you ask them what systems thinking was, they wouldn't be able to explain it. But how they act every day and practically how they run a department is exactly that. And they understand it intuitively more than more than they could actually explicitly explain. Speaker 2 Yeah, exactly. Think like humans innately are systems thinkers. I mean, you know, you get up in the morning and you start to think about all of these connected things that you've got to do. You've got to, you know, have your breakfast, make your kids lunch, get them to school, then do this at work and pick them up. How to Implement Systems Thinking Tomorrow And you start to connect all these things that are going to happen to you in your day. And then for some reason we get to our workplaces and then we get given this, you know, this this single line of focus and say, OK, this is your job, Just do this job, right. So I think our whole society sort of trains system thinking out of us in some to some extent, Yeah. So I mean, that's a whole another side. But I think what was what did you say at the start of that? Sorry, I've just sort of thrown myself off. Speaker 1 How do you avoid overwhelming staff if you're trying to implement the systems? Speaker 2 OK, cool. Yeah. So I think what I would, what I would start is OK, you know, you have a, you have your multiple, multiple disciplinary team meeting and we go, we got this problem, OK, We've and it's all about noticing patterns over time. I think the systems thing as well. So, you know, we've got this problem, we've got this pattern of whatever it is that's occurring. Instead of, you know, trying to immediately treat that, that symptom, I guess you would call it is, you know, you'd ask the question from all of the different disciplines, OK, what's influencing this? You know, and then you find that sort of a next level. And then it'd be like, OK, well, what's influencing that? OK. And then you've got a next level and then you go, what's influencing that? And I think that's a that's a more sort of an easier way to get into it. I mean, because people are going to have opinions about what's influencing things. There's no question about that. People are going to come with biases and all sorts of stuff. And, you know, that's you've got to manage all that sort of stuff as well. But I think and then this whole piece of psychological safety and departments all comes, comes about as well as, you know, are people comfortable about speaking up? And so I mean, there's a really a lot to it. It's complex in itself that process. But the questions I would ask is, OK, what's the problem? What's influencing it? What's influencing those? You know, what's influencing those? You do have to draw a boundary around it somewhere and you can sort of make that up as your own maybe what you're in control of or what your department sort of remit is, that type of thing. But that's where I'd start. I just sort of what are the influences to the influences to the influences, I guess. And it's and you'd be surprised how quickly that can grow. And that becomes quite complex. And then, you know, you might get somewhere, you're happy with it. And then you start to go, OK, well, this part here is interesting. You know, this, this little loop over here or, you know, this connection over this side is something we probably haven't understood very well. Let's have a little look bit of a look at that. Speaker 1 And it's, it's such a fascinating, even the exercise in itself would probably, even even if if let's just say nothing came about, you know, in terms of a tangible outcome, it would probably be a really effective exercise to go through that with you, with your team, as you're saying, and then understand, OK, well, what is it that we can actually influence exactly? Look, I'm really conscious of your time and we've just ticked over the hour, but I'd love it if you could just chat a little bit about the project. You mentioned before offline that we were chatting about with players that come from, say, the Academy up into the first team because it's it sounds like a a really fascinating project and a problem that many, many teams have. Speaker 2 Yeah, sure. So that project was with West Bromwich Albion in in the UK. So they're playing the Championship level. Yeah. So what they were seeing with their transition, so that's eighteens to 21's, the first team and they were seeing, you know, and again, this is what I talked about. It's like seeing patterns. So they were seeing this pattern of players that were transitioning across those those squads to getting injured and, you know, suffering injuries. And you know, I, I know one of the guys that works there and he sort of said, what's this, what's this, you know, what's the problem? What's causing this type thing? And I sort of, we thought about it a little bit. The research team, it sounds like this is this, this communication sort of issue, I think. And you know that. So what we threw at it this theory called distributed situation awareness. So distributed situation awareness is this concept that like no individual has access to all the relevant information. You know, each member of a performance staff will have, you know, this sort of partial knowledge or perspective of how that systems function. And I guess DSA is about how you connect all of those different pieces to have this sort of systems awareness, I guess. But yeah, we recently wrote an editorial in BJSM about distributed situation awareness, which is just like a couple of pages, which is a nice easy read that gives you some background on the concept. It's called football clubs in their hive mind if you want to go find it. But and that's sort of a nice, nice sort of basic overview of what DSA is. But yeah, so we know with these transitions, for example, that that they're often quite reactive. So, you know, a player might get assessed in the morning from a knock they had the previous day and they'll be, you know, ruled out of training. So a coach would go, OK, we need a replacement. Let's just get someone from the 20 ones, bring them into training. That sort of happens quite fast in the morning of a training session. You know, it normally involves quite a few different staff as well. So I guess we wanted to sort of understand that that process of how transitions in the club occur. So we applied a method which is called the Event Analysis of Systemic Teamwork or EAST is the acronym for that. And it's really a nice measure of teamwork and distributed situation awareness. So essentially what it does is it breaks down all the tasks that need to happen in a transition, I guess system, the actors that are involved and the information that needs to be shared between those actors. For each of those tasks, and you break it down to that and you run a bunch of fancy network analysis metrics, Essentially what it can do is it can tell you sort of what are the key tasks, who are the key actors, and what are the key bits of information that need to be transferred. So essentially the process as it was, is that there was not a lot of information going with the transitioning players. So there wasn't information on the their sort of, you know, their chronic exercise levels or, you know, previous injuries or there was all this information missing that could sort of influence them having injury. So essentially what we did is we identified all that stuff. And I guess what what you know, what the recommendations to the club was that to have some process of, I guess this key information that needs to go with the player when they transfer. Sorry, traction. So that's, you know, I've for around, you know, their internal external load markers, their previous volumes and intensities, you know, what's the session design, the gym loads, you know, all that sort of stuff that needs to be taken with them. And I guess they can sort of inform, you know, decisions on transitions. I mean, there's an example where I think it was the 20 ones player played in a cup match the night before and the first team coach was unaware and they asked if that player could come in and it was at the hardest training day of the week for that club for the first team. Player Transitions & Shared Awareness So you know, that's a disaster way to happen, right, just because of this lack of shared awareness of how all those different parts of the system. So I mean, that's really it's a really cool approach and it's really flexible approach as well. You know, we did on another project with with the guy who manages loan players on loans, that's where the clubs. So his job is to sort of he's the manager of all the loans that this Premier League club has. You know, players go out to all clubs around the world on loan. His job is the manager of that. And so, you know, he's obviously dealing with a lot of tasks, heaps of different actors and lots of information that needs to be shared. So that was a really sort of cool project as well, you know, so there's loads of applications for this and I think, you know, could it be like recruitment and, you know, all that sort of stuff. So the shared it's, it's this concept of the shared awareness. And I guess the, the, the key sort of premise of it is that, you know, it's the concept is it's about ensuring that the right actors have the right information at the right time, rather than having all of the information available. So it's not about information being available, it's that who knows what at the right time, I guess, you know, to inform these sort of decision making under like we've talked about today, these high pressure, fast-paced nature of sport, of elite sport. Speaker 1 Absolute gold. And I will link to that that paper in the show notes. And I actually had a conversation. So I think episode 4 will be with Simon Rice, who's the VP of athlete care at the 76ers. And it's almost as if verbatim you're saying what what he said in terms of having, you know, certain people should have information. Certain people don't need information and when they have it is important and so on. Sorry, that's just really interesting. That is, that's exactly what you found. It also sounds like it's almost come back 360 to your PhD where communication seems to be one of the vital components within the systems. Yeah. So potentially that was your foundational knowledge you needed to to get to this project ultimately. Speaker 2 So that that actual, that actual paper should be published in the next couple of weeks on that on that specific project. So the other one, the other one I mentioned before was like an editorial mainly around the concept of distributed situation. But this is the actual paper where we applied the method. So that should be out very soon, I think. So keep an eye out. Speaker 1 Excellent. Well, I will mention it again and if it's not out, I'll follow it up later. And when it's out, I'll put a link there. Scott, conscious of your time, really appreciate it if you have time. I just want to say a big thank you for coming on the podcast. I mentioned this to you offline, but I referenced you about 600 times in my PhD thesis. It was actually, as you said, one of your papers from your PhD, which was titled What's in a game? And you did a work domain analysis and yeah, so indefinitely influenced my thinking in my PhD. And so this has been an honor to actually to meet you virtually and to have you on the podcast. So massive thank you and really appreciate it. Speaker 2 Yeah, no problem. I really enjoy it. It's a good conversation. And yeah, hopefully this type of thinking considered be more embedded in sports. I think, you know, like we've spoken about today, it's that looking up and out piece of the broader system rather than sort of digging further into the weeds, which is where we seem to be going. So hopefully it resonates with some. And yeah, get in touch if if you need anything from me. Speaker 1 Yeah. And I'll, I'll, I'll also mention your blog, which is quite interesting in that the show notes as well. And yeah, as you said, I think it'll resonate with a lot of people or potentially give them some ideas. So lots of value in this conversation. Thanks, Scott. Speaker 2 Excellent. Thanks for having me. Have a good day too.