One Track Mind: Ep 07. What Sports Technology Do We Wish Existed?
Sam Robertson: We talk a lot about technology on this show - how it's used, why it's used and the impact it has across all different types and levels of sport. Some of the key questions are the same as those we face in broader society. Are people adequately trained to use it? Where is the demand for new and better tech really coming from? And which parts of our jobs do we most need it to help with? We know that enormous amounts of time and money are spent developing tech that helps us track and train athletes, but it's certainly not perfect. So what's missing? And what are the holy grail technologies that sports scientists can only dream of? On this episode, we're joined by two of the most experienced sports scientists on the planet.
We'll discuss their own journeys in the tech side of sport, how it's changed over the past few decades and perhaps most importantly, and interestingly of all, where technology can and should go next. I'm Sam Robertson, and this is One Track Mind. Hello. and Welcome to One Track Mind, a podcast about the real issues, forces and innovations shaping the future of sport. I'm your host, Sam Robertson, and on this episode we’re asking what technology do we wish existed? My first guest is Dr.
David Martin. David has accumulated 35 years of experience working with Olympic and professional athletes, publishing over 110 scientific publications along the way in topics ranging from talent identification and competition analysis to altitude training, thermoregulation and fatigue management. Dr.
Martin was a mainstay in the halcyon days of the Australian Institute of Sport, where he held roles such as senior Physiologist, Director of performance for the AIS combat Centre, and as the national sports science coordinator for cycling, which won almost 30 Olympic medals including eight gold during his tenure. Most recently, David was the Director for Performance Research and Development at the Philadelphia 76ers, and is currently a professor at Australian Catholic University, as well as the chief scientist for APEIRON life, a Bay Area performance health science startup. David, thank you so much for joining us. David Martin: Nice to be here, Sam.
Good to catch up again. Sam Robertson: No, thank you. I appreciate you taking the time.
There's plenty to talk about with this particular topic. I know we could’ve had you on the show to talk about a whole range of different things, but I think very few people in sport would provide an informed insight into this question as well as yourself. So before we really talk about where we'd like to see technology go, let's start a bit with your own experiences with technology throughout your career, and particularly how not only the volume of technology has increased, but the quality of it as well over time and the uptake in sport as well.
Specifically, I'm quite interested in various stages throughout your career where you've identified a real need to measure something in a better way; and that's driven you to either seek out some new form of technology to assist with this, or indeed develop something yourself. David Martin: My career is one that was really full of university experiences. Although I was a competitive athlete in college - I was a downhill and cross country skier - as I moved into my Master's degree, I was an assistant coach for the cross country ski team and I was doing research in the lab. I was doing a Master's degree in Exercise Science.
So you learn about technology like a metabolic cart, you learn about how to draw blood, and your 23L lactate analyzer. You put in your little sodium fluoride Triton-X cocktail, and spin this down, lice the cells, pop it in, and you know. Even the heart rate monitor was really interesting to just get good clean heart rates during races and training.
This is for me in the mid eighties, this was still pretty exciting. The technology that we were using felt very much lab- based. If we went out into the field with it we felt like we were real pioneers. Like, oh my god, we're going out in the snow. We're going to take blood from skiers in the snow, bring them back to the lab and analyse them.
So for me, that really was lab based for a long time. When I went to the US Olympic training centre, I got to see, for the first time, power meters. I'd never thought of that, like onboard power meters for bicycles, where you could measure the cadence the power and the speed; and you could do this with instrument strain gauges. You could actually calibrate these devices.
They would hold up. and drift a little bit, but you can get an accurate measure of power in the field. That to me was really, wow, you can take stuff from the lab to the field. When I ended up doing my PhD, it still felt very much lab based.
I wasn't doing a lot of field based stuff. So the tech was all like, wow, you can measure hormones in the saliva. Wow. You can get high-fidelity measurements, a heart rate, heart rate variability through the night and in the morning. Wow.
It was kind of like, where was biochemistry and where were these different types of analyses going that gave you more fidelity with common tests? Like a blood test for hemoglobin or hematocrit. You can do more with these assays. When I got to the Australian Institute of Sport, in the lead up to the 1996 Olympic Games, it still felt lab based although we had all of these Australian Olympic athletes coming in, we would go out on the field rarely, but we were booked, we were clinicians. They would come for camps, we would do our tests, we provide our reports, and poof off they go. It really wasn't until I think the lead up to the 2000 Olympics where it started to feel like there was wearable tech that was starting to be the kind of stuff that you'd believe in enough to actually go into the field to try to get feedback from. Then the other thing that happened more quickly, and your question is a good one, like what's happening now.
Back in the old days, if you and I wanted to have a discussion about blood lactate measures in swimmers, football players, or cyclists, we could go to a conference and talk about lactate profiling and lactate drift, and carbohydrate utilisation and fatigue and lactate. No layman could have a conversation with us because no one else knew how to use the tech. Today, there are high schoolers coming in asking me, "Oh, I bought this little lactate analyzer. What does this mean? What happens if your lactate is high?" There's no barrier for entry anymore. Anyone can buy what used to be very sophisticated technology. And you'd have to take courses and classes and get certified.
Today, you just go buy it. You grab it. And as you said, people aren't talking about accuracy, reliability, Bland–Altman plots, intraclass correlation, coefficients. They didn't even know what a confidence interval is. They’re just buying equipment, and getting numbers. And the companies know that their job, if they want to sell a lot of products, is to just dumb it down and have beautiful infographics.
So I think we've shifted from the 'tech is sacred and only for the scientists with training'. I remember getting told not until the second year of my master's degree, will you run the metabolic cart. I remember the guy running it.
He's like, dude, don't touch my cart. This is my world. This is my PhD. This is what I do.
When you're a second year, I might let you run it for testing. Now there's little portable O2 meters you can wear on your backpack. You know, anyone can buy them, anyone can turn them on. So I feel like that's been a really big transition in just the accessibility of the technology. Now it is everywhere, and because of that, I think some of the competence and rationale about why do we even want to measure this is starting to be lost.
Sam Robertson: That's a tricky balancing act, isn't it? It's something I think about a lot in terms of technology which is complicated, but the way it works is hidden to the end user. I think of a GPS device, for example, like that. I'm not sure how many people putting GPS devices on athletes in team sport environments would have any real idea about if they took the thing apart. They don't know how it works. You also got me thinking there about something specific like heart rate as an example of maybe something, I think Martin Buchheit mentioned this in the last season, as a form of technology that hasn't actually evolved that much. You know, it's something that's been around a long time, and yes, we know that it can probably be measured in the field a little bit better than it used to be.
But the heart rate strap is kind of unchanged somewhat for a long period of time now. So, I've got a question in that. You got me thinking about it when you mentioned strain gauges. How were those things originating? How were they coming into sport? Was it as simple as someone asking a bigger question, or was it someone coming from an engineering background and saying, Hey, we need to bring this thing over, or was it a bit of all of that? David Martin: I think the power meter is a really interesting story. When the wall came down between East Germany and West Germany, there were some East German technicians, Elise Schober was one of them, and there were grants that would allow some of these very innovative, tech- minded individuals who were basically working in elite sport academies, and elite sports systems, to take a product that was really just reserved for trying to give the national athletes a competitive advantage. And they've said, Hey, why don't we try to commercialise this? We'll give you a chance to grow it up.
And it really was one of the really big success stories. Inductive coupling was not really done. And to get the strain gauge signals in a spinning disc to go to a pickup and to not require any wires, to do that across a gap, was not easy to do. He worked out how to do it and then how to get the batteries in there. They were big, they were clunky, but you know, German engineering, they were actually quite accurate. So that's an example of elite sport having a need - I wish we had power out in the field, let's make a product with some engineers, and then an environment opening up where they could commercialise that product.
The commercialisation went global, which means even in the US and Australia, we could buy that product. So that's kind of how we got it. The catapult story is, well you know catapult very well. I give tons of credit to Alan Hahn, who's kind of like an unsung hero in that story. That cooperative research centre was again like the Australian Institute of Sport, with a bunch of sport scientists saying, wow, we can probably move into the field like they do with cycling, and in a lot of team sports. Look at where the wearable tech is going and gyroscopes and magnetometers and accelerometers.
And again, that was almost like an elite sport-led product development that then went global. So there are some cases of, essentially, build your own for your own intrinsic needs and maybe even competitive advantage needs. When it catches fire, it goes big. Then they make it easier to use, decrease the barriers to start using it, and then everybody's using it.
Then you get a lot of people going, Hey, how do you use this stuff? And why do we even have it? And how does it make you better? Kind of goes full circle. Sam Robertson: It does. I don't know if you would agree with this or not. I assume that you would. I think it is accelerating now. I mean, it's, gone through incredible change already.
You mentioned even 25 years ago around Atlanta, yet it’s not until Sydney that you really start to see things move out in the field. I think a lot of younger sports scientists and people working in high-performance sport now wouldn't remember those days or weren't around in those days. So it's part and parcel.
Now that it's pervasive, if it's around you, you turn on a button and you've got a piece of technology and that's only going to get more and more common. David Martin: I think you brought up a really interesting point that if you've got doctoral students, I've supervised doctoral students, and you think about the experience they have. My experience was I'm using technology and mostly lab-based. So before I do a test, I've got to go to my senior, or I've got to go to the department head, and they're going to say, so what are you doing? I say, oh, I'm going to do lactate curves or VO2 max tests and try to use those.
They'd be like, what technique are you using? D-max, or log transfer? Or what are we doing here? And you're like, oh, I was going to use D-max. Are you going to take them all the way to max five minute protocol, or three minute protocol? Which one are you going to use? Have you talked to people about this? Let me bring some people in. There's always a discussion before you start.
And the question is, are you doing something meaningful and are you doing something that's contemporary? Have you read your literature and have you done your homework? Now think about it when you go out into the field. What are the conversations like? They go, Hey mate, how are you getting on with the coach? Hey, how's it going? Does he like it? I heard he might get fired. Are you getting fired too? Like what's going on? It's more about the relationship and how are the players going, do they like the little thing you're sticking on them? I heard a couple of guys arked up. We got to think about this, man. They're not talking about what to do with the GPS data, they're talking about your relationship with the coaching, whether the footy players are frustrated with you putting these little bras on them on the high intensity days before a game. It's really funny how the conversation shifts.
And I think one of the things Australia has done well is someone like you and others in that really unique genre of helping elite athletes, but also doing sport science, we'll pull the students back and say, Hey, I'm still talking about quality questions. I'm still talking about how is the data confirming or discounting this working hypothesis? Do we think that there's an error in the data? What's the feedback we're going to get? I think that's super important because otherwise you're just a dude in a gym with some tech trying to be cool with the guys you're hanging out with. It's a very different feeling. Sam Robertson: Yeah and I think what we just talked about before is part of the reason why you're seeing things shift to those conversations.
It's almost too easy. Now, the tech, you don't need to objectively question, you can still turn it on. I mean, of course you should be questioning those things.
You also talked about things that I personally love talking about a lot - how well people understand reliability, validity, uncertainty. Moving on to the future, which is really what we wanted to speak about for most of today. Last season, we talked about the potential pitfalls of having too much technology and what that might do for the coach-athlete relationship, which you kind of alluded to there a little bit. My mind with this question turns to constructs of human performance that we aren't measuring particularly well now.
You'd think that they’re the areas that are most ripe for the picking in terms of improving our understanding of human performance. I tend to think of the mental side a lot, the psychological components of performance and communication, these types of areas. But I think also there's that 24/7 ubiquitous monitoring as well, which we know that camera systems are able to do now for athletes. I'll give you a couple of examples to get us started. When I think about injury prediction, how tech could help with that, which is only one way in which it could, I think of embedded intramuscular sensors under the body, with some kind of warning system built in that sends an alarm off to someone when the athlete's about to experience a soft tissue injury. That all sounds very far-fetched, but that's kind of where my mind goes in terms of where it could go one day.
And then the mental side, which I just mentioned, I don't really have any great answer on, but things like decision-making, intent, communication. That's the type of tech I'd love to see, but that sounds like a very tricky problem. And I'm not sure where that would go. Do you have thoughts on that? They’re two kinds of far-fetched ideas I've got. David Martin: I've always been kind of fascinated. I think a lot of physiologists the way we're trained,I think we like models.
I think we like a performance model. We've all seen the performance model for golf is all broken down. We made one up for skeleton. I remember me and Angus Ross when we were talking about skeleton, we have this big argument about what's the easiest sport in the world to win a gold medal in. The criteria was you had to never have done the sport, take up the sport in the shortest period of time, and become a gold medalist. What is that sport? Start it over a beer and work it out.
You've got to think about a lot of stuff, but one of the things you have to think about is how do you break down the performance of the sport skeleton? What underpins success in that sport? Then of every one of those components, do you have the technology to measure it? How do you bring that together and build up your model? So you can say there's a concept of sim-morphosis, you know, optimal design. It's used a lot in the animal kingdom. There's no part of the oxygen uptake system that's overbuilt. You don't have a trachea that's huge, that'd be a waste of space. You don't have a heart that's overbuilt.
You don't have muscles with way too much mitochondria. Everything. The hemoglobin mass mitochondria, electron transport chain, your lung size, all of it is built with this kind of efficiency of design.
You don't overbuild one thing. So if you take that to sport, you get into this really interesting construct of saying, is there something overbuilt? You're faster than you need to be to win a gold medal in skeleton. You're more aerodynamic than you need to win a gold medal in skeleton. You are smart enough and you have a good enough memory and you have good enough vision. You know, you just keep going until what is holding you back? And as one thing goes up and it's no longer a rate-limiting step, then something else becomes the rate limiting step.
In marathon runners, it's a trick question in graduate school, isn't it? Like you got your top 10 marathon runners, which of the following variables is best to predict performance? You always throw VO2 max in there and a lot of them bite at it, but they're all normalised on VO2 max. So the defining characteristic is like their 800 metre time. Something more anaerobic will be the differentiator.
And I think as we go into the future, we'll see more sophisticated models and that the technology will become very much like an F1 race car. It just seems intuitively appealing that we'd be able to look at our dashboard and say, Hey, Jim, out there playing this position, we're starting to see that weakness expose itself again. He's got a fatigue resistant problem. The dude, he can kick, he's smart, he's doing everything right. He's tough, he's strong, he doesn't need any more power. He is not basically holding up.
His fatigue resistance is the problem. So in training, we can top up other areas, but that is not the rate limiting stuff. I think in the future it will become more sophisticated. It has with cars. So why wouldn't it with humans? And I think some people talk like they kind of are working in that space, but I don't think they're really working in that space.
I mean, we build out just quickly a model in cycling and we would say, I am going to,basically, through DEXA, figure out how much muscle mass you have from the iliac crest down, how much muscle mass do you have? With that muscle mass, I can put you on a bicycle that's not even moving and just say, how much power do you generate? If I know the power that's being produced per kilogram muscle, there's ranges, there's high amounts of power, low amounts of power. And I can see if there's things that might need to be done to optimise that. Once I know whether you have the power for the muscle, then I have to say, how heavy is the body? Maybe we've got to lose some weight to get the power to weight, but that's not enough because now I've got to see what your aerodynamics is. Then as you go out from there, I can say you're aerodynamically fine, your power prediction is fine, you can make a bike really fast.
Now the question is, can you do it on the right day? Can you hold the line? Do you have the technical capacities? It kind of seems simple. Like these people need this, these people need this. It started to make sense, but I don't think we see a lot of those scenarios, especially in skill sports where everybody's just like, oh my god, it all goes out the window. I think that's going to be an interesting part of the future. The people that kind of start to meaningfully unravel... I mean, you know Warren Young and there's a lot of people who've done it in sprinting and there are people working up these models, but I think they're kind of unsung heroes and they're not really celebrated that much.
Those papers don't get a lot of citations. It's interesting. Sam Robertson: Yeah, I would agree.
And I think with those multidisciplinary topics or topics that maybe are a little bit abstract or people don't understand very well. I'm not sure if you're referring to agility there, but agility is kind of one of those, isn't it? You can have all these pieces of technology that we say measure agility, but is it really measuring agility? I think of Warren's work there, Sophia Nimphius’ work, even Damien Farrow’s work as well. Your response was interesting then, because I gave you a couple examples of measuring things that maybe we don't measure at all with technology right now, like communication, we rely on coach evaluation, or observer evaluation. But you talked a lot about maximising gains in some respects and rate limiting - that's not where my head went.
I actually do think you're right, particularly in skill sports. Things like If we had technology that we already have now, but we are able to increase the resolution of that technology, so to speak, or the quality, that would potentially have more of a gain than just measuring something new altogether. I do think skill is a good example of that in sports.
I don't think we know that much about skill development in athletes. Once they enter professional sports, we do all this work when they're coming through the ranks and then we kind of get them to the top level and, yeah, we develop it, but do, we really measure it longitudinally and know what's causing an improvement? I'm not so sure. I know I'm generalising, but I think that's an area as well. David Martin: Computer vision is just really changing the landscape. There's a small company with some ex engineers that came out of Apple and they now have a startup company called HomeCourt.
HomeCourt is basically for your iPhone or iPad. I have no commercial affiliation with them at all so I'm not giving them a plug, I just love how their brains worked and how they brought technology into a unique solution space. What you do is you just put your phone up or your iPad and you start shooting. You just start shooting baskets, like say free throws, just start shooting them. You're going to have makes, and you're going to have misses. It automatically detects the ball, does all the pixel resolution stuff and it tracks the directory of the ball.
But they're also doing, as you know is becoming more and more ubiquitous to see, these pose estimation models. And some of them are getting pretty good. They're probably still not VICON accurate, but what you can do with basketball with HomeCourt is you can get the ankle flexion and knee flexion, you can get the hip flexion. You can see when they make their shot, if their feet come off the ground, how long was their airtime? So you can get a lot of different aspects of the trajectory of the ball, the movement of the lower limbs, and you can count shot after shot, after shot, after shot. So what you can do after like a thousand shots over multiple days is start to compile and they haven't taken it here yet.
They're only just preparing to go there, but your question was about what will we measure in the future. With machine learning you can go through now and you can say, Hey, Sam, for you, when you miss shots, what we tend to see is your shoulder comes forward, your elbow goes out, the lower body stays pretty similar, but it's an upper body manifestation of how you generate the shot as we.start to.see a difference. Dave, you're very different. It seems to be your left leg and the way you dip. And, it feels like with someone like Damien Farrow or Derek Panchuk, you could start to with a good skill acquisition specialist or a good coach, you could say, Hey just little mental cues, no paralysis through analysis.
Let's just think, I'm a straight spring, I'm a slingshot, I'm a... whatever, whatever helps you do your thing, but I can tune this to you based on really interesting new technologies being applied in a new way that let me know what you tend to do when you miss pots. what you tend to do when you miss.
And that's very different than just a skill coach sitting there going, Hey, come here, and they just have to make something up and give you your confidence back. Sam Robertson: It comes back to the models you talked about earlier, doesn't it? If you look at that example you're giving now, other pieces of the puzzle over time are going to provide a more complete picture about why that athlete's improving or not improving. So, what's going on in their life? What's their fatigue levels,? All those things that you see in a high performance environment being measured. I tend to think, like probably a lot of us, that technology is a piece of hardware or a piece of software, but maybe it's more those really comprehensive solutions that we see in the future. Maybe that's a more enhanced type of technology that we see moving forward.
Something like a HomeCourt that actually starts to pull in information from other parts of that athlete to really optimise that learning experience. That's just a thought. I know that is out there at the moment in terms of athlete management systems and things like that, but something that really pulls that together with the goal of improving an athlete's skill or something like that would be something I'd love to see.
David Martin: I'm using a product with some eye-tracking and I know, the quiet eye has been around for a long time and Derek and Damien and others have looked at where does the gaze settle before the shot executes? So I just talked about an example of shooting baskets and just looking at the kinematics of the shot. But what if you were wearing an EEG array and you were looking at where the eyes were going. And so like you said, you're like, wow, this guy, man you've gone way left brain on me. I've never seen this much activity when you're doing shooting, and I'm really interested. Your eye gaze is now, you're swinging through the target and you're way less consistent.
Maybe you're losing attentiveness, maybe you're tired, maybe you're, maybe you're, maybe you're. But the whole idea of doing it is, one, enhance understanding, but still the translation piece is the fun piece of saying, I'm seeing something and it's given me a clue on how to treat this or help you better. And I find it amazing, like in medicine, Sam, you fall down, you break your arm, you come to me, I'm your orthopedic surgeon. I take a look. I feel it. I'm like, you know what, Sam, I'm going to put you in and we're going to get an MRI.
And you go, what's an MRI? Well, it just gives me detailed clarity on what's going on in that elbow. I think you might have a hairline fracture, but I'm not sure. I just want to take a look because my diagnosis and my follow through with you will be dependent on what I see. And you have no problem, do you? In fact, you would be pissed if I didn't go get an MRI. You're like, dude, you better do your job, use existing technology to help me and you make your diagnosis with it. That means you're smart.
You know what you're doing and let's go. But when it comes to sports science, people are like, you’re not putting that shit on me. Are you kidding me? What do you want to measure? Turn that camera off.
What are you? So why is it different in sport if you really wanted to get better? Versus medicine, if you really want to try to heal someone. I think part of it is because it's getting really sloppy and really messy out there with medicine. I had an NBA guy tell me, he goes, you're trying to measure this, and he pointed out himself and he told me, this is a piece of art. This is a work of art. He goes, you should just sit down and watch me do my thing. And let me enjoy myself.
Sam Robertson: I might guess who that player might be, but I don't think I'll do that on air. David Martin: It's like you can't measure this, you know? And so the script flips. I think all athletes ultimately want to be better. They want to be more competitive, but what they don't know is somebody who's a bit disconnected from the scene using advanced technologies in spurious ways, and either making mistakes in their follow through, or just potentially telling everybody that this athletes is not as good as you think. I'm seeing all these weaknesses in here.
And so you're de-valuing a player. And so the industry we work in is great when we're doing a research project, cause they all sign up, let's do it, let's learn. But in an applied setting, all of these advanced technologies, they come as a double-edged sword because they're worried. People are scared about what you might see.
It's a challenge. There's definitely a challenge. Some of the new tech companies building technologies, they haven't done what you've done. They haven't worked where you've worked. So they just think it's as easy as, this is great it'll make you perform better.
And you're like, wow. Sam Robertson: That actually is a nice segue into something I wanted to ask, which is almost where the responsibility lies in making sure that this space doesn't go wild, and you could argue maybe parts of it has already. But that we don't get a situation like that athlete you referred to who just flatly refuses to do anything in the future, because there's just so much that they're exposed to and they throw their hands up and a league or an organisation just bans the whole lot. I mentioned earlier that this space is accelerating, and you mentioned some companies that are doing various things, but it seems like it can’t just lie with them to make sure that their tech is delivering on its promises, because of the reasons you just said.
I mean, they don't know what they don't know sometimes. So is it everyone? Is it the leagues? Is it the clubs? We know that people in the clubs are pretty busy, rightly or wrongly, with their day jobs. So who's going to pick that up. David Martin: I was on the sport science committee with the NBA and there's lots of discussions about what tech do we allow in, they even do call-outs for tender. They put up these projects and technologies that are being used, they have them evaluated.
Are they accurate? Are they safe? Are they reliable? Do they at least give us what we think they are? To try to stem some of those criticisms. I think, especially in professional sport where it's very much a business, that you're going to see just more and more surveillance tech, I think is the term used by some people. You don't have to wear anything, it's just surveillance tech. And there's another technique and I'm really waiting for some people that kick off with this.
It's a simple idea and it's been done in a couple settings, but I haven't seen it used that often, where you tether physiological responses to surrogates. So you say, look, you've got to wear a heart rate monitor, you've got to wear these insoles, you've got to wear this and that, I know it's a little bit much, but we're only going to do it for a week. I'm building up some patterns and relationships.
What you do is you say, for these movement patterns, I know your heart rate, for these movement patterns, I know your ground reaction forces, and I know your sweat rates, and I know your whatever. I needed to kind of instrument you in order to get you. But now, I get you. Now all I need to do is see you run around. I can just do it from television, or whatever, and I get great insight into how your system is being loaded and how it might adapt into the future.
You might start seeing these hybrid models where the athletes are more comfortable. So instead of saying, we can't measure important stuff, it's too invasive, the athletes will never let us do it. I think they would do it for a time.
Just to say, this is pre-season camp, let's get this stuff, and then in the future, I can tell you the heart rates. For distance runners, we've been doing it forever, you build up a VO2 max, you figure out the powers, you can pretty much guess within about five beats what the heart rate is. So there's going to be some techniques that, to get to the question, that the sports are probably going to regulate it a little bit, they're going to be kind of like the bad cop in the clubs. They're going to go, you know, people are there for a short time and a fast time, and they're just going to, you're not going to tell me what to do, I do whatever helps me keep my job. But then the other thing that's going to happen is you might start to see these systems where with accurate equipment, you start seeing really cool surrogates.
So you get more longitudinal continuity of care without having to instrument the person so much. So you use accurate equipment, tag it and then monitor it. I mean, we're going to see a bunch of fun stuff emerging in the future. You think of all the stuff we've seen in the last 20 years. Sam Robertson: I like that idea you raised then.
My mind was turning to building that understanding in training, in simulated competition, again, away from prying eyes as well. As you mentioned, then the utility comes out in competition or when people are actually watching. But my mind also went to this notion of when tech stops being a legal and fair advantage. Once it's away from prying eyes and people don't know about it, it's always subject to manipulation as well. I know that's a topic beyond today, but that's where my mind went as well.
Like, how much is too much? And we know that once we start doing things covertly or that people don't understand, or they don't see in competition, I think that's where like tracking devices have been fine or even optical tracking, because you can see the cameras in a stadium, you can see the devices. So that's a very complex issue, as we know. David Martin: There was a big hoo-ha I believe in F1. For a long time, drivers said there's no way you're putting a camera in the cockpit of an F1 driver during competition.
You're not getting...You're gonna see how I shift, you're going to see where my hands go, there's no way. And they were like, well, ew're going to bring this much more revenue into the sport, and we're going to bring in this many more fans, and this many more sponsors. And if you don't want to drive with a camera in the cockpit, you can go drive in another league, because in F1 we're going to have cameras in the cockpit. And all the drivers were like, well, I never said I wasn't going to drive without a camera. There are financial incentives.
When the sport tech becomes business tech and entertainment tech, and they have hybrid roles, there might be a lot more acceptance to some of the information and some of the data. There is some really interesting technologies we haven't talked about that might be fun in the future, and that's starting to capitalise on the human intellect within teams. We all have our brains and we have our eyes and we have our opinions.
This has been done a little bit, but there's probably a lot more sophisticated approaches to understanding the wisdom of the crowd around the athlete, for things that are really hard to measure, like, is he tired or not? Can he do more or should he do less? Is he contributing to the team or is he not contributing to the team? So right now we go after it with these analytics solutions, but this professor at UPenn, Damon Centola, is doing some really fun stuff with smaller groups and iterative polling to gain signals on the wisdom of a crowd. So we can just say, how tired at the end of the day we are. All around these players, you, me, we all vote.
How tired was this athlete, little Likert scale, we pick it, but then you don't stop there. What you do is you get a view. I don't know what you said. I know what I said.
I don't know your score, but I know the average of our collective group. And then we can have a little discussion and we vote again. And then we have a little discussion and we vote again. He’s shown by the end of three iterative votes, with even small groups, you can predict how many jelly beans in the jar, how many calories in a meal, what's the price of a car, what's Google's stock going to be on Friday.
What it reminds me is that an experienced coach, an experienced support staff member, they have a very good feel of where the athlete is. And so you can use software technology and kind of innovative methodology to potentially gain insights into questions you would really struggle with just hard tech. And the other thing is the conversation becomes real easy because I can say, Hey Sam, you just finished your workout today, we all talked about you, that's how this place works, and your average score on fatigue was super high. A lot of people think you're looking really tired right now. Maybe you're not, but I just want you to know that's how you're coming up. That's how we're all perceiving you right now.
And guess what? Tired players don't get a lot of play time. Tired players piss coaches off. Tired players sometimes get confused as being unmotivated players. So I'm just letting you know, a heads up, we might have a problem here.
So that's just an innovative twist on not relying on an accelerometer for everything. There's other signals we can tap into. Sam Robertson: That leads to all sorts of great things, which is tying that subjective wisdom to the individual models, or mental models, of each of those raters themselves, the model that the athlete might have with themselves, of course validating that against the tech. But it also gets me thinking a little bit about the question we were focusing on today, which is moving away from just looking at tech as a piece of hardware or software, it has that model underpinning it there as well, or it's a methodology even, which is kind of what you're talking about there.
I was also thinking of, I think it might've been Ray Dalio's dot collector is something that’s similar to that, which is that wisdom of the masses where different individuals in an organisation have different levels of reliability and validity, which is another take on what you said, but a dangerous one, a very dangerous one within organisations. David Martin: It's like, three times you've told me what you think we should do and every time we did it, it didn't work out. Your value is dropping in our organisation. It does get back to something we kind of started with - how important mentorship and leadership and comradeship is for this world that we're in. I think a lot of, sports scientists working in elite sport, trying to embrace technology, get isolated.
It becomes a very isolating experience and they come under a lot of heat and they hide behind their laptops. And everybody's like, what do we got over there, doc? You're like, sorry, I'm busy. And they're like, don't piss him off, he's busy, he's working on stuff.
But they don't know what you're working on. They have no idea what you're working on, you might not know what you're working on! You know, it's this funny little game of look at all the technology around me, look at it, this is an amazing system and I built it and I run it, and nobody wants to have those hard questions like what are we doing here? You know, what are we doing here? What are the questions we're trying to answer? And how is all this tech contributing and helping? I know it costs a lot, but I'm just saying. Cause you're not doing any research projects. It's funny, we call it sports science because the process of scientific inquiry is up for peer review.
That's a massive component of science and the scientific process. And if you're isolated on your own collecting massive amounts of data to give your team competitive advantage, and there's no one in the team to question what you're doing or even understands what you're doing. You don't have peer review, you're in a little, isolated juggernaut and you're just trying to be the Wizard of Oz.
And you're just hoping no one pulls the curtain back and figures you out. Sam Robertson: As I say regularly actually, it's generally the only role in a high performance or professional sporting club, for example, that has the term science in the title of the role, a lot of the time. It is incumbent on them to lead the way in that. As we've talked about, it's a deep and complex issue about how we keep up to date with that and whose responsibility it is. A lot of people that I've heard say that it's incumbent on universities to train their undergraduates better.
I think that is part of it, but it's moving too quick even for that, I mean, universities are not fast moving places. So, it's only part of the puzzle, I think. David Martin: Yeah, it's true. I hope Australia stays connected. I think that universities, you know, VU , ACU Edith Cowan, like there's some great professors who are maintaining a critical eye and they're mentoring and guiding the young emerging scientists that are finding a lot of enjoyment working within these elite sport teams. I think in the US I don't see as much mentorship.
I don't see as much, you know, universities don't really play in that space as much. So the young strength coach or the young athletic trainer, or the young sport scientists, are really left on their own. It's really up to you, you do it on your own. And then they can't collaborate much because that would be giving away the team secrets, and they can't go to conferences because they're so busy, and they're not writing papers or reviewing papers because that's not really their remit anymore.
So they become data collectors and infographics producers, and they try to have this small fraternity of athletes and connect with them in ways that it feels meaningful. So a different game is emerging. It's not, like you said, how did I start with science? It was nothing like that. It's morphed into something that's completely different to what I started out in.
Sam Robertson: That's happened very quickly and it's worth pausing and considering all of that. I must let you go. It's been a pleasure to talk to you about this.
I'm not sure we've solved everything, but I think we've provided a few good ideas and potential ways forward for the future. So, David, thank you so much for joining us. David Martin: Thank you, Sam. Always fun to hear your perspective.
Love it. Sam Robertson: Our next guest is Dr. Darren Burgess. Darren is currently the High-Performance manager at Melbourne football club in the Australian football league.
Prior to this, he was a Director of High Performance at Arsenal Football Club, and he's also held roles as a High Performance Manager at Port Adelaide Football Club, Head of Sports Science for Football Federation Australia, and Head of fitness and Conditioning at Liverpool Football Club. Darren has also worked as a lecturer in exercise science at Australian Catholic University Sydney, and completed his PhD in the movement analysis of AFL and soccer in 2012. Darren, thanks so much for joining me on the show. Darren Burgess: Pleasure, Sam. Thanks for having me.
Sam Robertson: Now to kick things off and before we start to talk a little bit about where you might like to see technology head in your particular sports, perhaps we can set the scene a little bit by discussing some of your many experiences to date. A few things in particular come to mind, the first being how your use as a practitioner has changed over time. And I don't mean just wearable devices and these types of technologies that often come to mind first, but all sorts of types, from computers to full blown virtual reality setups. Darren Burgess: My initial exposure to technology was using the old track performance software Neil Craig and Kevin Norton brought in. So I did over a thousand tracks.
So the listeners might not be aware of what that looks like, but it's a big drawing tablet and a scaled version of the oval that you're about to track the player on and you've got a graphic design pen and you're basically following the player from an elevated position. It takes about 100 tracks to get your reliability down. What I enjoyed about that process is it really did give me some perspective on the limitations a lot in technology because the reliability and the validity wasn't perfect, the reliability in the end got okay, it was acceptable at least. I did become a bit obsessed with the data.
I did start thinking that, you know, this player is no good because he doesn't run. So the technology put a different lens on what I would normally think because I sort of was blinded a bit to the technical side of things and we just became sort of obsessed with the physical side of things in the data. So that probably continued in my early career as one of the early adopters of GPS units in 2004. When that first sort of came out you had to take them out of the bra to have a look at the distance on them and put them back in again. So it was a bit different. And again, that combined with me learning some spreadsheet skills, I thought I'd cured cancer and just thought that I was able to predict injuries, to show coaches the best graphs ever.
So I really did probably go wayward there for a bit in my early career with Port Adelaide where I was a bit obsessed with the data in 2004 and 2005 and even with the Swans before that in the late 90s and early 2000s. So yeah, that was probably my early exposure to technology through my PhD, which was looking at the application of technology to talent development in team sports. I think I became a bit more balanced and that was a great experience for me, trawling through the information and trying to predict things like career success in AFL based on technology in games plus draft combine, which is again, using technology to assess athletes - realising the futility of it. It probably gave me a nice perspective on exactly what matters in performance and talent ID and what doesn't. So moving into where I was involved in some more wealthier clubs in Liverpool and Arsenal and we had things like virtual reality and the virtual reality set up that we had at Arsenal, for example, allowed us to put a game into the system and players to be whichever player they wanted to be during that game. So we might play Liverpool at the Emirates on a Tuesday night, on Wednesday morning I could have an injured or a young player be Mesut Ozil for the game and see what he sees.
And whilst that sounds great, the uptake for the expense was poor and the graphics were so poor. On tours, you'd show people and they go, oh, that's amazing, that's incredible. But I've probably learned to really have a balance on what technology I trust and believe in and think can help through trial, and error and significant trial and error, to those that I've just learned to sort of let go. And even if the Joneses have got it, not so much worry about what other people have got or what my players think - oh but Collingwood have got this or Essendon have got this - learn to trust my own judgment and keep it simple, I guess.
Sam Robertson: It's funny, you mentioned those old GPS units, my little fellow found one in my office the other day and it's still got the screen on it. And it's not that long ago, is it? It has come a long way as one piece of technology, as have some of the other things you've mentioned, virtual reality and computing, and just in general. The first example you gave then, there's a lot to do with the time investment that you put into that as well. I mean, no doubt you've become more experienced over your career and you've probably learned to be...like a lot of people that come
from physical performance, they get more perspective as they go through their careers, they realise it's not just about running further - at least not in team sports anyway. Because things were so manual, you almost felt like you were investing so much time that it had to be important and otherwise it wasn't worth your time. I think there's a part of that with it as well, isn't there? Darren Burgess: People always ask, well how can I get in the industry? How can I get better? What courses can I do to learn? Well get hold of a truckload of, in this case we're talking about GPS data and the vision that's associated with that data and the outcome, and start to understand what movement elicits what objective information, heart rate, GPS, and just understand their impact on performance. Every time I get frustrated at those hours spent in front of an Excel spreadsheet, trying to delineate between midfielders who'd run a thousand meters between 15 and 17 kilometers an hour using a one hertz system, and those who hadn't, thinking what a waste of time that was.
But I've no doubt that it was subconsciously, or even somewhat consciously, helping me understand movement a bit more, understand what impacts success and what impacts performance and what matters and what doesn't. So, I worry for people who sit in front of a computer and don't go out and watch training and be exposed to that. I'm sure, listening to your podcast, some pretty experienced campaigners have said similar things. Sam Robertson: Yeah and you just got me thinking then with the one Hertz GPS, as an example of where we've come to now, I wonder what we're using now that's analogous to that. What other pieces of technology we're using, which are going to be in a similar boat? We might sit here in 10-15 years' time and be laughing at how poor that was as well.
I'm trying to rack my brain, but I'm sure there's a couple of things that are there. Maybe we, if we think of them, we can come back to them. Picking up also on what you mentioned around virtual reality. I think that's just one example, but what that reminded me of there is, and I think you even said it, kind of keeping up with the Joneses or fear of missing out if we don't stay up to date with the latest and greatest gear. I'm not picking on that particular area as one, because I think there is merit in that. You've worked in mainly Australian football and football , those being your two big sports, are there differences across those? You obviously mentioned some are more resource rich or resource heavy than others, not so much in what they take up, but just their approach to it.
Or is it across the board? Everyone's just really trying to keep up with the Joneses rather than dictate where the tech goes itself. And is that even the role of clubs and organisations? Darren Burgess: As a philosophy, if I compare the resources that I had available at say Arsenal, to the early resources at Port Adelaide in 2013. We had 20 GPS for 45 players at Port Adelaide, no assessment of force production in terms of a force plate or anything like that. When I moved there from Liverpool, they said, okay, what technology do you want? I said, No, I just want the ability to choose my own strength coach and I want to bring a GPS system from the UK because I could get one for every player. I thought that was pretty important. And what we did is invested in people and a philosophy and because we had limited people, each one of those staff members then has also a limited, sort of, scope to introduce new technology.
So if we go to Arsenal, and there were 17 full-time employees for the first team of which there's only 25 or 26 players, and so each one of those people then says, well, in my area I need a bone stimulator, in my area I need DEXA, in my area I need a 3D analysis tool. So each one of those thinks well I'm only bringing in one piece of technology, but then it just grew. And it was extraordinary some of the things that we had there that were just collecting dust, or were poorly used or not assessed properly. I think that's one of the real issues with keeping up with the Joneses and growing the department.
Over there it's a competitive advantage because you're recruiting players and they see Tottenham in the morning and Arsenal in the afternoon. But undoubtedly we were more successful relatively, and probably absolutely, at Port Adelaide because we kept it really simple and we were forced only to use the limited amount of technology that we truly believed would impact performance, because we just didn't have the finances. So I think that's one of the big problems with the resource rich clubs, is that probably just through wealth and they don't probably do their due diligence enough on, is this going to impact performance? Of course, in those countries you have, 'in Spain, we had this and when I was playing in Brazil, we had this, and why don't you bring that in?' So there's a whole bunch of other things that perhaps led to the complexity. But I think that's one of the problems with the keeping up the Joneses model iss that even when you think, oh, I want to invest in more people, you just have to make sure that those people then don't want to introduce their own technology.
And what that also does is, when you get the new, sexy technology, whatever that might be, virtual reality or whatever it might be, it's almost like you relegate some other technology which has been proven to impact performance, because it's just not as sexy. So I did that with heart rate for a long time. Now I think I rely on heart rate heavily now and have done for the last seven, eight years, but I went away from it because GPS was so good and with so much information, but now heart rate, which has been around forever and barely changed in terms of the essence of what it does. I think heart rate is pure gold in what it offers in terms of a performance metric. But because I had so many other things I went away from that for a bit.
Sam Robertson: This raises a topic that I find myself having a lot of conversations about at the moment, which is how we actually evaluate technology. We know that we get taught that in university, concepts like validity and reliability, but again, it's more than that. It's the uptake. It is a tricky thing to evaluate. It's a bit more of a soft skill than a hard number, isn't it? Like is this thing still going to get used in two years time? And it is tricky to tell sometimes because obviously, particularly in a sport like football, you could change managers pretty quickly, and again, that might mean a whole heap of things you've invested in become redundant.
Then of course, sometimes technology just improves so much that it renders something completely redundant anyway, or at least out of date. But you also mentioned a couple of pitfalls there as well and that's what I wanted to ask you about. What are some of the other pitfalls of technology? You mentioned one there, which was, we get distracted by the shiny new lights and we go away from the things that are tried and true. But I think another one comes back to something you said right at the start, is we particularly with new technology that's quite refined and packaged up with a nice dashboard or software interface, we don't really learn enough about how it actually works.
And that's sometimes okay, but sometimes that means if it goes wrong or we want to dig a little bit deeper, we can't. So that's another pitfall I think of. On the horizon shortly is literally, not so much a pitfall, but a challenge, which is, do we replace a human staff member with this piece of technology? That's probably one that's on the radar coming pretty soon.
Darren Burgess: If I give you maybe two practical examples in my world, which is more the applied world, and one of them would be dear to your heart. The first one is, let's say something like a NordBord, which was introduced and despite the insistence of those guys - you know your Dave Opars and Ryan Timmins of the world who are unbelievably skilled researchers and really good at marrying up the lab-based stuff with how can this affect performance - every time I've spoken to them, and I consider them both close mates hopefully they'd have the same thing to say about me, they would say, listen, this is not to predict injuries. What we're doing is we're assessing hamstring strength in this plane.
That's what we're doing. And yep, we've done some pretty good research that suggests if you are low in this, your risk goes up. And despite that, practitioners all around the world, use that technology to say if you are below 356 Newtons, or whatever their cutoff was, even though they would look them blue in the face and say, no, it's not a cut off point that says if, you’re… and only now we're just starting to emerge, the value of spring training and some other aspects of strength and strength in different planes and all those sorts of things. And Timo and Dave Opar have been saying that for years, but no one listened because the technology showed you, over/below this cutoff point. So that's what sometimes technology can do, even though it's been proven to be reliable and valid. And so now we're sort of going back and saying, well, a NordBord is one thing, but it's not the thing.
But for probably five years and still in a lot of places, it's considered the only predictor of hamstring strength. So just get it strong and it'll survive. The other thing, which is dear to you, is the analytics revolution, which is currently taking place. And it seems like you won't get a job as a sports scientist unless you can code. If this AFL soft cap goes up, I guarantee you a lot of clubs will say, well, with that extra money, we've done pretty well while it's come back down, we’ll maybe get another coach and a data scientist, thinking that that will make us be able to predict injuries, predict performance. And you who’ve led that, and I'm not meaning to pump you up too much, but you've led that revolution and been at the forefront of it, have more recently when I hear your talk and speak to you over a nice coffee in south Melbourne say you that we've gone too far with it.
It's not as predictive as perhaps what everybody thinks it has been, and we need to really do this with a lot of caution and tread really carefully with what analytics we're looking at and the success of it. Now, that can only be done with better computing and better programs and technology in that sense. Then when we start to bring it into our analytics, which we do, let's say GPS plus NordBord plus force plate plus heart rate plus heart rate variability, which has all been with the use of technology. And then we apply some analytics, which are yet to be really proven and shown to be in any way successful in predicting performance and/or injuries. It's a real murky situation that we've created for ourselves.
Just sort of wading through that now, myself, that has been a real challenge. And I was helped a massively by some really good people at Arsenal who were experts in this space. They really answered a lot of questions for me, but before that I was thinking that analytics was the answer.
So there's two areas, the NordBord and the hamstring and the analytics, which saw an uptake in use. And after more detailed analysis and thought and consideration are probably not the be-all and end-all that we thought they were. It's a long answer to a short question. Sam Robertson: It's got me thinking. Firstly, I love that example of the NordBord, because it's really practical and it's a really good one. I haven't spoken to those two guys about it, but I can imagine they'd be extremely frustrated with where that's gone, particularly again, as you mentioned, they've done a lot of research in that area, before the Nord board even came out as well.
You also talked about the role of sports science and it's really interesting about, are they applied technologists really? And that's not a good thing if that's what they've become. But again, I think in some sports that's really what that role has become. You look after the technology. It's almost like they're the property manager for technology instead of actually the sport scientist.
And then the final thing, just on the analytics there, I'm increasingly becoming convinced that the end use of the analytics is the next real area for development there, in terms of how does it actually get operationalised to make decisions and, even more importantly, evaluate them. If we look at some sports now, the analytics has become overly preoccupied with tracking data. You've got whole clubs that just look at tracking data. I get the attraction of that, but I'd like to see it become a little bit more diverse and hopefully that happens.
Just moving us into the last couple of things I want to talk to you about, which is really the future, which is not only where you'd like to see the tech heading, but also maybe where you might like to not see it head as well. When are we starting to get into the gray areas there? Have you got some ideas in mind about where, if you're sitting there doing this job in however long you want to keep doing it for, in 5 or 10 years, what's the next big thing that's going to really help you? Darren Burgess: A really dangerous path that we seem to be going down is this sort of 24 hour monitoring of players, and thinking that that's what's going to impact performance. I see a lot of and permanently wearable devices which are of interest, no doubt of interest, but I think it's a really dangerous space, in terms of privacy and all those things that come into that space. I am concerned that we just keep going more, mor