Mollie Brewer joins us to discuss how we interact with data – which can say as much about coaches and athletes as the data itself.
Episode Transcript
Trevor Connor 00:04
Hello and Welcome to Fast talk. Your source for the science of endurance performance. I’m your host, Trevor Connor, here with Coach Rob pickles. We talk all the time on the show about what the data means, power, heart rate, tss, ATL, and dozens of other data points. But what we can forget in these deep dives into the numbers is that training data has gone from a few bits of information that added a little bit to our workouts to something that now fundamentally shapes how athletes and coaches interact with our sport so not surprisingly, a relatively new science has popped up called sports HCI, which stands for human computer interaction. It studies how both athletes and coaches interact with their data and training platforms, and how that can impact their training, their interactions with one another, and even their sense of self worth, and it raises very important questions, like, is it ethical for a coach to see an athlete’s 24 hour HRV data? The coach may look at it with the best of intentions, but is it going to make the athletes stress having a poor night’s sleep knowing their coach will see it here to discuss this emerging field and how it will impact our training and coaching, is MOLLY BREWER, a past colleague of Rob’s and mine. Brewer is now pursuing her PhD at the University of Florida, studying the impact of Computer Information Science on sport. Molly will talk with us about this emerging field of sports, HCI and how data has impacted athletes, but more importantly, we’ll discuss her recently published paper looking at how top coaches interact with data coaches across sports seem to play two roles that a data analyst and as protector. As data analysts, it was a surprise to discover that coaches want to analyze the data themselves. They don’t want black box solutions. But as a protector, she was surprised to discover the fact that coaches will avoid data they know is valuable in order to prioritize the privacy of their athletes. First joining Brewer will hear from Dr Steven Seiler with his thoughts on the impact of new emerging data. Dr Michael Rosenblatt, owner of evidence based coaching and author of the Norwegian training method, Brad Culp So start thinking about how you personally interact with your data, and let’s make you fast. Well, Molly, welcome to the show. Been excited to have you join us. Thank you for having me so we have some background with you. Truly is exciting to have you on the show, because this is not our first time meeting you. You and Rob in particular, have worked together in the past. So tell us a little bit about your background, and Rob will let you jump in and tell everybody how great Molly is.
Mollie Brewer 02:29
Yeah, I have a background in sports science, and I got the opportunity to work at the CU Center for Sports Performance in Boulder, Colorado, and as a kind of between undergrad and Master’s student, I got to do an internship, and Rob was my first mentor at the facility, and my first exposure to deciding whether I wanted to go into exercise physiology or kind of go the physical therapy route.
Rob Pickels 02:56
I’d say that I did a good job, because you stayed in exercise science and physiology, but I don’t know. I think we’re talking a lot of computer science today, Molly, so maybe I steered you in a better direction.
Mollie Brewer 03:08
You definitely had a huge influence on me staying in exercise physiology. It was after that experience that I enrolled in a master’s program, and then I got filled experience in professional cycling. Got to continue advancing my skills at the Performance Center, doing a lot of testing and helping you guys with research. And then I was actually presenting at a conference on some of the work that we had all done together in lactate analysis and prescription for training and endurance sports. And my now advisor was in the audience, and she’s like, You have to come to Florida and help us with some of the work we’re doing in wearable technology and sports. And at first, I was like going from exercise physiology to computer science seemed absurd and impossible at the time, but yes, now I’m enrolled at the University of Florida studying computer science.
Rob Pickels 03:55
I think that the connections we make throughout this field, throughout our lives and our careers, ultimately end up guiding a lot of where we go. And sometimes it’s this river that you’re just following along, and you don’t quite understand where you’re going to end up. But we can end up in some wonderful places, and I know that for me, I ended up moving to Boulder in some regards. Similar to you, there were members from Boulder Center for Sports Medicine that were in the audience of one of my talks, and that’s where that connection came from. And for anybody that’s out there, whether you’re a student or whether you’re involved in this shake as many hands as you can get in front of as many people as you can create, all of these connections. Molly, I think that you’re underselling yourself still a little bit though you’ve done a lot of work in Europe with some professional teams and riders over there. Tell us just the audience a little bit about that, so they have the big, full picture of all of the different things, because right now, it sounds like you’re just the student who’s always been in school, but you have also you have a lot of practical experience too, yes,
Mollie Brewer 04:49
and it balances itself out really well to have both the lab experience and the field based experience, because I think it’s important to learn how to apply some of the things we do in the lab. Um, with the real world applications of how coaches and athletes are utilizing them in like actual settings. And I got the opportunity to go over to Europe with women’s cycling, with Tip co SVB, which later became es tip co SVB, and work in women’s cycling and help out with the dynamics of the sport over in Europe, I got to go to the first Perry rebem, which was really exciting and such a great opportunity. But again, it was just like seeing the real world application of what the impact of travel and logistics have on the physiology and coaching practices. So I
Trevor Connor 05:33
gotta say the thing that impressed me talking about what you’ve done and how motivated you are. We were waiting for Rob. We got on a little bit early, and you were telling me about your spring break, which was last week. And here you are, somebody who’s going to school in Florida. The obvious spring break would be drive to the beach and sit there. Instead, you signed up for a course with Dr Steven Seiler that is being taught in Europe, which meant you had to for your spring break, you had to get up every morning at 330 to join this course. It started at 4am
Mollie Brewer 06:09
Yes, correct. That’s what I did over my spring break. But I think you guys are very familiar with Dr Steven Seiler work, and it was worth the early mornings in order to, like, hear a lot that he had to say and his teachings, and then also the presentations he offered and the interaction with other PhD students that were included in that week.
Rob Pickels 06:28
I’d love to actually sit in on a Siler lecture. I’ve never had that opportunity. I wonder if it’s different than, like, eating hot wings with a guy. I feel like we shoot the shit a lot, for lack of a better term, I’ve never been lectured by him.
Trevor Connor 06:40
You know what would be fun? Rob The Muppet Show was it Stanton Waldorf, the two hecklers that sit up above the stage and make fun of the show, right? That would be us. We would just join the show and heckle Dr Seiler the entire time.
Rob Pickels 06:53
Maybe one day, Trevor, we can just show up in Norway and crash one of his courses just like sit in the audience. Don’t even tell them we’re coming. Oh, that’ll be great. Let’s do it.
Trevor Connor 07:04
It would be fun. I’d 100%
Rob Pickels 07:08
do that to tell you I’m not even joking about it. I would definitely do that.
Trevor Connor 07:11
Actually, the more you talk about it,
Rob Pickels 07:17
it would be worth it. Back on topic. What are we covering here today, Trevor, this is a topic that I’m not gonna lie It’s been a while. Trevor, you’re gonna get mad at me for saying this. It’s been a while since I’ve actually researched something before an episode, and that’s probably because I’ve taken a little bit of a step back. I’m doing a lot of podcasts. And Trevor was like, Hey, I’m doing this episode with Molly. You want to be a part of it? And I was like, Yeah, of course. I want to be a part of it. I love talking to Molly. She’s always doing great stuff. And then I, like, saw the topic, and I was like, Oh, I might need to actually read this paper before I’m able to talk about it. So Trevor, kick us off. What are we talking about today? Yeah,
Trevor Connor 07:51
so Molly, this is your first paper, which we were very excited to cover. It was just so we are recording right at the end of March, and my understanding is this, gets published beginning
Mollie Brewer 08:02
of April. April 26 is the first day of the conference.
Trevor Connor 08:05
So this is hot off the press, but this episode goes live right after, so we’re recording a little bit before, but when this episode goes live, this paper will have just been out a few days, and it was a fun read, despite the fact that you put a giant confidential right across the text, which made it hard to find, but that’s okay. But where I want to start, we think we’ve heard every single term, but you introduced in this paper a term that I’m sure you’re very familiar with, but we have never once uttered on the show, and it was something that was very interesting to me. So tell us a little bit about what sports HCI is and what that stands for.
Mollie Brewer 08:43
Yeah. So HCI stands for human computer interaction, and this area of computer science is about how users interact with technology. So it’s the human facing side of technology, so not necessarily the software engineering of building it or the data analyst analyzing the data. It’s about how users assess the technology, if it’s usable, if it’s valuable, how they use it and apply it into practice. And in this case with sports, it’s how coaches, athletes and even spectators are grouped in that interact with technologies in that sports data ecosystem, yeah,
Rob Pickels 09:23
Molly, I think you mentioned something in there that I just love to clarify. Is data essential to HCI, or there’s other computer systems, right? And what I came up with was, like those devices that people are using to train reaction time, right? That’s a computer driven system that people are in literally, humans are interacting with it. Is the data component really essential? It doesn’t
Mollie Brewer 09:44
have to be limited to the data. It can be about interacting with interfaces. Are they easy to use? Do people struggle with them? Can they interpret them? Well, one part of human computer interaction is if a individual has a goal, how long does it take them to achieve that goal? People, and can we make it simpler and easier? Does it match their mental models of what they think the icon is supposed to be? And that’s a lot about human computer interaction, which doesn’t necessarily have to do with the mass amounts of data. And then also it can be about how the tools or the technologies shape how people think, fill and behave. Psychology is brought into this field and social sciences, and that’s really important about kind of the experiences around technology, which would also not necessarily be all about the data, but data is a huge part of it.
Trevor Connor 10:35
What I find fascinating about this is we have talked many, many times on the show about the data and the value how to use the data, the value of the data should use heart rate should use power. We just did an episode with Dr Seiler about breathing rate, and we try to talk about how to use the data. But that’s not what this is about. This is more about how both coaches and athletes interact with that data, how they interact with the computer interface, how it influences their training, how it influences their relationships. So it’s kind of looking at the data, but from a biopsychosocial side, is that accurate? Exactly?
Rob Pickels 11:11
Excellent. Tie Back. Trevor, wow. In the background, I’m going to look up what the biopsychosocial episode was. But Molly, you can keep talking.
Trevor Connor 11:21
So let’s start. We’re going to focus mostly on the coach side, because that’s what your paper is about. But before we get there, you mentioned in the paper that a lot more research in sports HCI has been done on the athlete, so I was interested in diving a little bit into that. What had they been researching with athletes, and what are some of the things they’ve discovered from this research?
Mollie Brewer 11:42
Yes, so sports ACI is actually an emerging field. It doesn’t have a long standing history, and that’s because technology is evolving so rapidly, just in the last couple of decades, and it’s now, I want to say, like fundamental, but like everywhere in sports practice, even at the recreational level, not just for the professional level, there’s unprecedented access to data and technology in sports right now, and athletes have been the primary focus of this just recently evolving field, and a lot of that is because they’re the ones that the data is being collected from. And so the focus has just been on how they use it to plan view interact and then reflect on it afterwards. And in research, it’s easy to go directly to the source, and that’s the athletes. And so that’s why a lot of it has been primarily focused on them, and then also integrating aspects of physical activity behavior. What we know about a hearing to exercise that novice like gamification and that can help them stick to exercise plans. So we see a lot of gamification in technology, around sport technology, we also know that like trends and visualizations help people stick to goals and see progress. So you see that a lot in sports technology, and so developing that interaction has just been the first step in this field. So
Trevor Connor 13:00
have there been any interesting discoveries from this research with athletes? What they’re seeing, how athletes interact with data, how they interact with the interface. The main goal
Mollie Brewer 13:10
of sports technology comes down to being able to measure the metrics or the outcomes or performance in the most accurate way possible, like we want accurate metrics. And so I think that was like the primary focus in the beginning of the research in this area. But now we’re not just measuring raw metrics. We’re now can derive those metrics and they become recovery scores, stress scores, VO, two, Max, we can give information about training load, and we can take all those raw data and metrics and put them on platforms and athletes can visualize and see information. So I think some new things we’re learning about is how data impacts the sporting experience, beyond just giving a metric about performance, and that’s where we look into more of how does it affect their competency, like how they feel about themselves. Does it impact rumination does it impact their self worth? It can promote relatedness build community. We see that with like social sharing platforms of data sports technology, which is in a lot of sports technologies, like being able to share your activities that you’ve done.
Rob Pickels 14:14
So real quick, that episode was episode 255, the biopsychosocial approach. It was with Michael Crowley and Andy Kirkland. Quick little aside there, Molly, I’m wondering, maybe, on the athlete side of things that you’re discussing here, what’s the end goal of sports? HCI, is it purely to just sort of understand the world that the athlete lives in? Is this to better inform, say, athlete decision making, so that maybe they’re more empowered, or they have more autonomy over their choices. Is this to inform tech companies to say, hey, Garmin Strava, whoop. Here are some things that you can do, and it’s going to improve the outcomes of the people that are using your product. I
Mollie Brewer 14:54
think all of the above. There’s technology developers that are involved in this research that. There’s psychologists, there’s social scientists, sports scientists, and so I think just through what lens you’re viewing it from, and who you’re interacting with, and I don’t think it can be done in isolation either. Like we want good, accurate metrics to inform sports performance. I’m a sports scientist. I want that. I want good outcomes to be able to make decisions, but we also want to enhance the sporting experience of individuals, and I think technology can do that if used appropriately. And so that’s another area. Can we use these technologies to help people engage and have better experiences in sports and how they pursue physical activity? And can we help the physical activity endemic we’re under in the world through sports technology. So that’s another way lens of individuals who are looking at that is, can we help overall health outcomes with these sports technologies? And then technology developers want people to use their products, and they want them to be usable and interactable and accessible. And can we learn from how people now apply them to improve that, because one big thing in human centered computing is all humans should be able to use technology, just not a small subset of the population. So we also want to make sure that the visualizations meet end users of all types. And it meets not just elite athletes using the technology, but recreational athletes. It meets your weekend warriors, or anybody that wants to use the technology to serve a goal or health purpose. It’s
Rob Pickels 16:27
interesting hearing you say that, because it reminds me of the breadth of this field. And a number of years ago, I don’t remember exactly, when I was on an exercise bike and it had a computer display on it, and there was a video game that you interacted with and to catch. Maybe they were dinosaurs or something like that. Your goal was to catch these creatures, and at times you had to ride really hard to catch up to them, and at other times it was easy. Maybe there was some steering that was involved, or whatever else, but it was a very interactive game, and you didn’t realize that you were doing an interval workout. This is a way that you’re talking about improved exercise adherence, or just this endemic of low physical activity. You know, this is a way to bridge exercise into people who maybe aren’t inclined to exercise just for the sake of exercising. Not everybody like us loves to go out and just ride their bike for hours on end, and being able to tie the technology component like you’re doing into this and say, Hey, how do we design these effective programs that are going to captivate people, that are going to motivate people, but it’s also going to get them worthwhile physical activity, I think, is really interesting. So
Trevor Connor 17:30
one of the things I found really interesting that you did mention in your study, even though you were focused on coaches, is how much now athletes are investing their sense of self worth into this data. We would love it if you expanded a little bit on that. Yeah,
Mollie Brewer 17:45
so technology has very positive uses. It can build the community, like we said, allow for like, a sense of competency. If you’ve achieved a goal, there’s like, a quantifiable goal, and you can see your progress over time. Those make us feel good. We know we’re on the right track, and it can provide like almost a reliability check that you’re doing what you need to do, and you’re going to make the progress that you need to get to your goal. But there’s also this aspect, or the other side of the coin, that over reliance on sports technology, and when the metrics are kind of over emphasized, without the context, it can create an interfere with confidence and enjoyment in the sport. And I think we might all have interacted with that of too much data can start to get in your head, and you might the athlete might think, Oh, if they don’t hit the number, when we know there’s just fluctuations in performance and you always are not going to be on an upward trend that can get in your head and might be perceived as a personal failure, if you like, go out and just can’t hit your power numbers for the day, and then it can have an impact on how you feel the rest of the day about yourself and your activities. In HCI, there was a recent paper that came out that kind of sports technology can almost create a moral framework where being good, and that’s in quotes, means that you hit your number, and being bad is when you don’t hit it. And we never want to get to that point with the data or the technology, and we don’t want to create like, an internalized pressure or self judgment, which I do think can happen with athletes at time to time, with just how much metrics and data overload we can get right now. So
Trevor Connor 19:20
you actually made me incredibly self aware. Thankfully, this weekend, because we had really nice weather, I’ve been in my basement on my trainer all winter, so I finally got out for a ride and like, oh, I don’t need to look at a screen. I can go out and enjoy the environment. And was going up a climb, and I have the newest Garmin, and it shows you the Strava for the climb and compares you to the different people, including your best time, and it shows you the grade and just this ridiculous amount of data. And I got about halfway up the climb and realized I have been doing nothing but staring at my computer. I’m now just outside staring at a smaller screen. I’m not looking around or. Actually enjoying this climb at all, and thought about what I’d read in your paper, went, Okay, stop this, stop looking at the screen and actually enjoy being on this climb. So I get it that we have so much real time data now we can just get obsessed with it and then focus on that, as opposed to just actually being present in what we’re doing, yeah, and
Mollie Brewer 20:21
even though my paper wasn’t on cycling, you guys know, my heart will always be in cycling, and I’m the sport of cycling, and I think cycling is unique in that. I think we may be one of the only sports, and you can correct me if I’m wrong, that has a cockpit of data right in front of us, and we can partake in a sport where visibly seeing the data is actually very accessible in the middle of the effort, which I don’t think we see that in many of the other sports I know, running, they can, but it involves, like, changing your arm motion to look at the data while cycling, we can, like, basically zero in on a whole screen of data. Like I have seven fields of data in my Wahoo bike computer that I can look at the entire time on my ride. I think that
Rob Pickels 21:03
this goes beyond just data overload as well. Where I know I was riding in a fantasy island in Tucson, an area that I wasn’t familiar with, and so I had mapping up on my Garmin, and it was like beeping at me every 30 seconds, and I thought I was on like the wrong trail, because they were doubling back, and then it was beeping at me. I was going the wrong way. I almost took that computer off my handlebar and threw it into the middle of the desert. Fortunately, I didn’t, but that was the point that I was at Molly You bring up in your paper, it’s beyond just cycling, and we’re all cyclists in this room. A lot of people that we are speaking to are cyclists, but it was eye opening to me, because you were working with a lot of team sports athletes, and in that situation, or I should say, team sports coaches for your paper, and in that situation, there was this unique aspect of the fact that the coach was collecting data that the athlete wasn’t necessarily aware of, or I shouldn’t say aware. They knew that the data was being collected, but they weren’t necessarily, say, seeing the real time metrics of their heart rate or whatever else it was that was being collected. And that was a really unique aspect to me, because as a cyclist, that never, ever happens. If I’m with a coach, I’m usually so far away that they don’t even know what’s going on in the moment. Never mind. So it kind of explained this unique situation that you came across here. Yeah,
Mollie Brewer 22:15
so in a lot of the team sports that I work with, there’s a ton of data being collected on the athletes at all times of their performance and even outside their performance. And a lot of these are coach facing technologies. We call coach facing technologies, the ones that the coaches directly interact with. And then there’s athlete facing technologies, which are more like the wearables the athletes wear. And then they can actually themselves, view the data and kind of self interpret the information. And many of the technologies being employed in these team sports are coach facing. So the athlete is wearing a vest, or they’re wearing a device, or they’re jumping on a force plate, and the coach is receiving the information, and the athletes never seeing it, and the coach is making decisions on that, and it’s like a behind the scenes, interpretation and application to decision making.
Rob Pickels 23:04
So for example, you bring up a lot of football, and I’m pretty sure that’s American football in this paper. Of not football, but football. Yes, those athletes are wearing GPS devices that coaches are using to monitor gameplay activity and maybe making decisions. Of Oh, player 73 has 63 minutes of play time, and he’s probably getting tired, and so I’m going to sub him out, and so on and so forth.
Mollie Brewer 23:25
Yeah. So one of the biggest metrics that’s being utilized is something called player load, and it’s very similar to what we use in cycling with the example of training stress score or TSS, and it’s a way to quantify how hard and how long the practice or the game was, I think across sports, that’s really important, that metric, that idea of, can we quantify how hard and how long something is so that we can make informed decisions of how it’s impacting the player? And then also, can we progress them to meet the demands of a competition? And they’re doing similar in team sports, and they’re measuring that through accelerations, decelerations, change of motion, and they’re trying to generate the same number, and the coaches are using it to design practices. Check in with players, like, if they see a sudden increase in this workload number, the way we might see a sudden increase in a TSS score, they can go to the athlete and say, like, what were you doing? Are you okay? Can we give you some more resources? Maybe we should back you down, or if they do a competition and they get a certain workload number, then they can design a practice leading up to it to meet the demands of that competition the same way we would do for a race, where we could see how hard was the accumulated stress of that race. And then if we’re going to do a race again, or a similar race, can we build up training so that the athlete is prepared for the intensity and the demands of that competition?
Trevor Connor 24:47
What we’re saying is that the data can really inform but it can also get athletes off track. Here’s Dr Michael Rosenblatt talking about how data can take athletes in the wrong direction.
Dr. Michael Rosenblat 24:59
There’s two. Much data we’re forgetting to see the forest through the trees, we need to take a big step back. There’s all this data that we can look at, but there’s also we can misinterpret what we’re looking at. It’s good to see it, but it’ll be very obvious if there’s a problem or if things are going really well. Yeah, I think take a step back. I used very, very little data with my athletes, just some key measurements. And how are you feeling? How are things going, and then reassess, are we seeing the improvements and make little changes along the way. So
Trevor Connor 25:25
how do you recommend a coach responds when they have an athlete who says, Oh, I have all this data. Tell me what it all means, and they’re getting too caught up in the weeds. How should a coach respond to that? Well,
Dr. Michael Rosenblat 25:35
that’s a tough question, because I think actually it’s a very common thing for many endurance athletes, and I say maybe try to speak to the athlete about saying, bring them back to their goals. Well, what are you looking to achieve? And then build confidence in that athlete that that coach is going to be able to bring them in that direction, regardless of whether they’re looking at the data or not. Maybe take the focus off the data and go back to the goal.
Trevor Connor 25:59
So I think this is a good segue. Let’s get to your study. You mentioned right at the beginning of your study, there’s been a lot of research in sports, HCI with athletes, but not so much in coaches. So you really wanted to be one of those first studies. So tell us a little bit about what you were studying and how you conducted the research.
Mollie Brewer 26:17
So we know that in competitive sports and even recreational athletes too. Coaches play a central role in shaping an athlete’s performance, and we know they support their well being. They’re very influential in decision making, and that effective coaching can lead to positive performance outcomes and a boost in confidence. And one thing that was missing in this research space was the role of coaches in this data interaction. And so our study wanted to look at what are the experiences of data and technology with coaches, and we specifically did it on collegiate coaching staff, and we wanted to look at how they use this data to support athlete performance and then overall athlete well being. So
Trevor Connor 27:02
how did you do this? So you just basically brought in top coaches in several sports from the university, and you interviewed them, correct yes.
Mollie Brewer 27:09
So we started by gathering as many voices as we could to hear about their experiences. And one thing that’s important to note is that coaching is not a one person job in collegiate athletics. It’s a team of individuals. So it’s a team effort across the sports teams, and there’s representatives from the head and assistant coaches, but also strength and conditioning coaches, athletic trainers, dietitians, sports scientists. There’s administrative staff, and we wanted to hear about how kind of data flowed among them, but also how their roles impacted the sports data interpretation and how it was applied for performance insights. So we interviewed in focus groups. So each focus group represented a team, and then the focus groups had representatives from each of these different roles and positions of who worked with the teams.
Trevor Connor 28:02
So let’s dive into what you found. And it seemed like one of the key findings you’ve discovered was that the coaching staff has essentially two roles, one as a data analyst and another as protectors. So we’re going to dive into each but can you just give us the summary of what you mean by those? Yeah,
Mollie Brewer 28:19
so with this explosion of technology and data in sports, we found that the traditional coaching role has evolved, and that coaches are now taking on these two additional roles in response, and that is a data analyst, and that kind of captures just the coaching staff’s effort to extract meaningful insights from the data, and then distill them into actual decision making to improve performance for the athlete development and team success. And then the second role was about them being a protector. And this idea that more data isn’t always better, especially when it could introduce stress or complex like over complexity for the athletes, and how they were simplifying and managing the dissemination of the information from the data to their athletes. One of the
Trevor Connor 29:12
questions I wanted to ask you, because I didn’t quite get this in the study, so you have a mix of sports here. So that was a men’s American football, men’s basketball, women’s basketball, women’s soccer and women’s volleyball. Did you see these roles being pretty consistent across all the sports? Or did it vary? It was
Mollie Brewer 29:29
very consistent, and that’s how our findings were shaped, as that these insights were expressed across all of them, despite different genders, different teams, different aspects of performance that all the coaches were trying to create relationships between the data. They were manually connecting the different systems of technology. That was one big thing, is that we’re quantifying so many aspects of the athletes performance across all the different seasons. So pre season, competition, season and. Off season. But a lot of these systems operate separately or in silos, so there’s not a way to merge the data, and the coaches are manually trying to connect them. What does hydration status look like for workload numbers? What does recovery from a wearable look like for what the workload output was for the game? And the coaches are doing that across all these sports with varying technologies, but similar technologies just applied in more of a sports specific context, and then with the protector role, like the term we’ve used for protecting the athletes, emotional well being and privacy. With the technologies, all of our coaches were very sensitive to the impact data could have if it wasn’t managed appropriately for the athletes, like that was very consistent across all the sports teams.
Rob Pickels 30:42
Molly, I’d love to hear more, because you worked with a lot of different roles across these teams, right? You had coaches, you had dietitians, strength and conditioning coaches, athletic trainers, sports scientists. But she also had administrative staff. I’m interested to hear how did administrative staff end up interacting with data, and how did that influence maybe some of the conclusions in your study. So we
Mollie Brewer 31:03
only actually had one administrative staff represented with one of the bigger teams, and I think it is important to include them. I wish we could have had more representation. But this is a unique sporting environment in that these student athletes are students, and they have navigate the roles of being a student as well as performing for their sports and traveling. And so this person was very big on like logistics and also managing the academic side. And so the technologies they were referring to a lot were communication ones, of communicating schedules to the athletes, making sure they get the appropriate tutoring times and they get the relays of like, when practices are, when travel is, and those are important technologies as well as managing sports. But it’s important to remember like this is a team of individuals trying to support athletes, and they each bring a unique aspect to the role and how data is interpreted. But one thing we saw is that the raw data isn’t shared to every single individual in the raw report, like they are simplifying and managing the data so that it goes to the appropriate role and they can make decisions.
Trevor Connor 32:10
So I want to dive a little deeper into this, because you did say in the paper that data is now central to coaching, and also made the point that coaches are not passive consumers of the data. So what did you mean by that
Mollie Brewer 32:22
passive consumers would be people that were just like taking in the numbers and applying them directly? And we found that was not the case for our coaching staff, that we called them active users. So they were taking the numbers that was outputted by the technologies, and they were integrating their own context, intuition, sporting experience and sporting knowledge to make those decisions, there was a lot that was going into taking the raw metric or number and making it usable in sports, and that’s what we meant by active interpreters and not passive users. What
Trevor Connor 32:55
I found interesting on those lines is that they weren’t using the tools that were necessarily provided with whatever technology was recording the data that they would export it, pull it into Excel and do their own interpretation.
Mollie Brewer 33:08
Yeah, some of the teams had just historical ways that they interacted with their teams or shared information, and that was pulling the information into one unified place. And that’s going back to there’s a lot of technologies, but they don’t offer an integration or an easy way to pull all the information into one, and so the coaches are relying on themselves to do that.
Trevor Connor 33:31
And you were saying also that the coaches really didn’t like black box data, so if one of the tools was doing an interpretation and they didn’t understand how it was being manipulated, what sort of formulas were being used, they had a hard time trusting it.
Mollie Brewer 33:45
Yeah, the more derived a metric was, the lower the trust in it. And we’ve seen that in a lot of human computer interaction studies with both athletes, and we saw it with our coaches, that even though a lot of these technologies wanted to make life simpler for coaches by outputting a number the coaches wanted to know how it was calculated. That was really important in their decision making, that they didn’t want to apply it to their practice or athletes without understanding what all went into the calculation. But those metrics were still important to them. It was just adding in the contextual knowledge. It just affected applying the data point if they didn’t know the background on how the metric was derived. So
Trevor Connor 34:22
I found that really interesting, because you look at what a lot of the tools are doing now, is they are trying to do all the calculations for you, do the interpretation for you, make it really simple, so you don’t even have to look at the data. It’s just going to tell you what the data means. And what I was reading in your study is that’s not what coaches want. They want the raw data. They want to do their own interpretation. They don’t want to interpret it for them. I think
Mollie Brewer 34:47
sometimes they want it easy and accessible, because sports are high pace and high performance, and there’s a lot at stake. But these are they’re athletes, and they care about them, and they care about. The impact it has on their performance. So they don’t want to apply things blindly. I think if they understand what the metrics mean and how they’re calculated and they can trust them, then they can move forward with like, just getting the number. But I don’t think we’re completely there yet. Yeah,
Rob Pickels 35:13
and I think that the end user is really important here as well, right where we’re talking about professional coaching staffs at elite d1 for our European listeners, we’re talking about d1 which is the biggest, the bestest collegiate sports. And these are probably some knowledgeable individuals. And Molly in your paper, you did talk about the fact that different coaches interact with data in different ways. It felt like some people used a lot of intuition. Some people were very data driven, but they probably have the intelligence and the tools and the time and the interest to actually dig into this data a little bit more than maybe just the common lay person who is picking up running for the first time, and they don’t have a lot of either formal or informal education. Yes,
Mollie Brewer 35:57
that was a great way to put it.
Trevor Connor 35:59
So the last thing I want to talk about with the collection of the data. Then we’ll get to how they use the data. You said that coaching staff often struggled with some of the tools that were given to them. It was just there were either issues. They it wouldn’t work correctly. We already talked about the black box side of it, and I did find it again interesting. You said some of the coaches, even when they were given this stuff for free, it was basically sponsorship. If they didn’t trust it, or if it was problematic, they would just stop using it. I think that was
Mollie Brewer 36:27
more of like when it came to the assessment at the end of the year, like, if it’s not reliable or useful, there’s a lot of technology out there, they’re gonna move on to something else. But I think they do the best they can to apply the insights and find the value in what they have. It just takes a lot of intuition and competency on the coach’s side to make it applied and be useful and decide what metrics they want to use. Like a lot of these technologies are getting tons of metrics, and in one sport, a metric might be more valuable, or in one role to a strength and conditioning coach versus a nutritionist versus an athletic trainer, they might view the metrics generated by the technology very differently and use different ones in their applied practice.
Trevor Connor 37:07
And you did mention that every team was collecting 1011, different data points, and depending on the staff member, they would use that data differently.
Mollie Brewer 37:16
Yeah, so somebody that was helping an athlete return from injury might be looking at their baseline testing assessments, and then using a number to guide an athlete back to where they want to be. Maybe, if it was like jump count, like, this is the jump counts they were using like as a healthy athlete, and now we’ve lowered that number, and we’re progressing them back to be able to return to a full jump count in practice of how they determine the intensity and quantify the load of practice. Maybe this junk count number that would be like an athletic trainers usage of it. But then a strength and conditioning coach might look at a motion capture system and see an imbalance and flexibility, and they design a training program to improve that to reduce risk of injury. Or a coach might look at the workload number from a prior practice and decide that this athlete needs to do a little bit more recovery, while this athlete can be pushed a little bit more and so how they interpret these different numbers is different for their role.
Trevor Connor 38:13
So you just dived into the fact that they were using the data to guide training or rehabilitation, or whatever their particular focus was, were there other ways that they were using data? I think in the study, you mentioned, they are also using it to help with interpersonal relations with the athletes. Yeah,
Mollie Brewer 38:28
I think that one of the positive things that data and technology brings is it can guide a check in you can have up to 80 athletes on a team. A lot of these teams have 20 plus athletes, and you’re trying to keep your eyes on every single athlete, and these resources are providing outputs so you can see how hard or how tough a practice was for each individual athlete, and it allows for personalization and individualization. And if they see a bike in a workload number or a drop in speed or whatever metric they were using, the coach can now go up to the athlete. They can be flagged, or they can say, hey, like, how’s it going? What’s going on? Or they can provide additional resources. And that’s a benefit of technology, creating this, like, relational aspect, and bringing something else to the coach, athlete relationship. So
Trevor Connor 39:16
I want to shift gears here a little bit, because actually what I found very interesting your paper, and wasn’t something I had really ever read about before, is this ideas of the coach as a protector, so protecting both the athletes privacy and also trying to protect the athletes, emotional well being. So would love to dive a little bit into that. Let’s start with this idea of protecting privacy, it was good to hear the coaches, particularly with anything that was HIPAA related. So tell us a little bit about that. Yeah,
Mollie Brewer 39:47
so HIPAA is very important in collegiate athletics, and HIPAA is just the Health Insurance Portability and Accountability Act, and it provides strict protections for sharing personal health information, and some of these technologies do. Collect medical information. And another thing that’s under HIPAA is a lot of the body composition. And our coaches very much respect that in the conversations, they talk to us about how data can’t just be shared across the board because of these acts, and they have to follow these principles of who can interact and who can see this type of data, and that’s for protection of the athlete. So
Trevor Connor 40:22
one of the surprise findings that you mentioned in the study was that coaches would sometimes not use data that they knew would be valuable because of privacy concerns of the athletes. One example, I mean, I have a whoop strap. It’s constantly monitoring my heart rate variability. It tells me about sleep, tells me about my recovery, that would obviously be valuable data for coaches, but they’re resistant to using that 24 hour data because they feel it’s an evasion of privacy. Yes,
Mollie Brewer 40:51
correct. That was a unexpected finding for us as well, that among the coaching staff that we interviewed, I don’t think this is necessarily generalizable to all collegiate sports settings, but they had a heightened awareness and caution towards even non HIPAA protected performance related technologies, and these are specifically the ones that were 24 hour wearables or provided the automatic, continuous physiological monitoring. And they could talk a lot about how many of these metrics would benefit performance. And we know, as individuals who worked in sport science that knowing sleep quality and HRV and resting heart rate would benefit a coach when they went to decide if an athlete was recovered or not, or if they slept well enough. We know that sleep quality affects reaction time, and lack of sleep can increase injury risk, but they felt that these continuous monitoring almost was over surveillance for the athletes, and that the athletes would feel big brother if the coaches were constantly looking at every single minute of their day. Yeah, I
Rob Pickels 41:53
think that you’re discussing a lot about the coaches being protectors for the athletes. Do we need to protect the athletes from the coaches. I guess, in that regard, Is there information that should be not shared with the coaches? And I’m wondering sort of, in the bigger picture, maybe that we take whoop for example, there’s an athlete facing app. Are the coaches interacting with a coach specific edition, like in training peaks, I have coach edition of training peaks which looks different than the athlete facing side. And do companies need to be say, Well, I’m going to share this information with the athlete, but I’m not going to include that in the coach edition, because it’s just none of their business. I
Mollie Brewer 42:33
think that’s kind of where this research should that’s my personal opinion. But should go towards is both for the coach facing side. We talked about that earlier in the podcast. There was a lot of information being collected on the athletes that the athletes weren’t seeing, and some of that was for this protecting their emotional well being, but some of it was because it was producing huge reports that maybe weren’t simplified enough or overly complex to share with an athlete. Can we improve the coach facing technology so that they can share information better and in more simplified ways to the athlete. But then, on the flip side for athlete vision technologies, can we make it so that coaches can also interact with that data, where, in mindful of those privacy concerns, it almost
Rob Pickels 43:13
feels like there ought to be opt ins with this right where the athlete is able to say, like, Yeah, I’m okay with my coach having my 24/7 heart rate, and other athletes might say, No, that’s personal data that I don’t necessarily want to share with anyone else.
Trevor Connor 43:26
I think it’s such an important question because we’ve talked before about how you get athletes to get a whoop strap, or one of these 24 hour monitors and our ring and they start getting stressed about their sleep because they want to get a good sleep score. Add to that, imagine now their coach, who’s deciding if they go to a race or an event, or is determining their training, is also seeing that and seeing whether they got good sleep or not. That’s adding to the pressure. Now athletes feeling, oh, my God, I have to get good sleep or my coach is going to be upset with me. It wasn’t something I had admit, personally, given a lot of thought to, but it is really important that sort of data the coach is looking at it to help the athlete can actually have real negative consequences.
Rob Pickels 44:09
And I think Trevor, that’s a running theme throughout this paper. For me is there’s a lot in here. I had never given a lot of thought to, you know, Molly, I’m glad that you’re researching this, because it is causing me, even as a coach, to have these questions right in the practice. So yeah, very interesting
Mollie Brewer 44:26
and kind of more future studies is this study was purposely designed to hear the voices of coaches, but a lot of these concerns and insights that we found deeply impact the student athletes as well. And so our next step is to talk to the student athletes about their experience in this emerging space of sports technology. So that’s one of our next steps in research. Is to hear their side of what they think about, because we don’t know yet. What do they think about the 24/7 wearables, and whether it’s shared with the coaches or not, and if they want it shared or not want it shared, or what they consider even part. Privacy, like, what streams of information? So that’s one of our next steps, is to hear from them, and then also to look at this concern of wearables in this space through a security and privacy lens. One of our co authors is in cybersecurity and privacy, and some of these concerns that are brought up, he wants to look at through this new lens of, what do policies dictate around this space, like, how is this transforming the coach athlete relationship and a lot of practices in sports performance? What for good or bad? Just taking a look at the landscape that we have now in sports technology.
Trevor Connor 45:30
So there was another side to this coach’s protector, which is protecting the well being and the confidence of the athlete. And I love there was a quote from one athlete or one coach who said, I just think you’re giving them something else to mess with their heads. And kind of love that quote, but wanted to hear more from you on this protecting the well being of the athletes. Yeah,
Mollie Brewer 45:53
our coaching staff were big on like, the value that technology has, and how it can benefit the coach athlete relationship and help with personalizing training and individualization and manage large teams, but they’re very quick to show the potential pitfalls of data and technology and how they were strategically managing it and tailoring it to create a motivational environment for the athlete and not give the athletes so much information to worry about, like they had this belief that too much data could almost create an environment of stress for the athlete, and it was like they took it upon themselves to strategically manage the data so that the athlete only had the beneficial sides of it, so it could be used for motivation and to build confidence and avoid that over complexity and the stress and the rumination that too much data can sometimes cause in a sporting environment. And I
Trevor Connor 46:39
love that one of the examples you used was with their strength routines, some of the damage that the data can do there. So for example, if all the athletes on the team know what one another is lifting, and let’s say, as an athlete, you consider dead lifting really important, and you’re dead lifting X, and somebody else on the team is dead lifting 70 pounds more than you that can really get in your head and make you question yourself as an athlete. Yeah, so
Mollie Brewer 47:05
there’s a benefit of kind of the social sharing that it can motivate and build community and hold you accountable, but there’s also the aspect of social judgment and the pressure you put on yourself when you compare yourself to others and stray away from the individual nature that data can provide to a student athlete when you start comparing yourself with others on the team, and
Trevor Connor 47:25
that’s something we have literally, that tool in cycling with Strava, you can constantly see how you compare to people you’re racing with, to your teammates. And it really made me think, does that affect an athlete when they go to a race, if there’s somebody who’s consistently beating them up a climb, when they get into a race with that person, they just go, I can’t beat you. And it makes them not race as hard, or not race as well, two sides to every coin. It’s really interesting.
Mollie Brewer 47:53
I think that helps us think about what does this mean for AI coaching, and what does this mean for self coaching for athletes that self coach themselves and maybe rely on these technologies and platforms, what can we learn from the elite level coaches and how they manage and apply data and how they use it with their interactions with athletes to inform our future technologies and guidelines for those that don’t have access to elite coaching, I think that’s a really important kind of insight or consideration as we move forward with a lot of the AI coaching platforms and just recreational athlete access to many of these derived and raw metrics just at their fingertips.
Trevor Connor 48:32
That’s a really good point. AI does not have any consideration for the well being of the athlete. It just answers questions. Let’s take a minute to hear from Brad Culp who talks about this importance of the whole athlete.
Brad Culp 48:46
Yeah, it certainly. I think something’s lost. Look back to the coaches that I had early in swimming or early in endurance and triathlon and running. For the most part, it started so there was very little data, and there was so much personal, one on one communication and phone calls and meetings, and that’s something that I think might be dying out a bit. And I think that the very, very best coaches, especially at the elite level, are coaching the complete human, and the data is such a small part of that. So yeah, I think that the data can get in the way of some of the psychological coaching that is very important, and that is especially true for younger, high performing athletes, a kind of athletes, a 23 year old hoping to win an Olympic medal, psychologically, that can be a very sort of fragile or traumatic thing, and that’s a high stress situation, and a coach needs to be able to deal with that, because if that goes astray, everything out the body is a system, and everything else will go with it. So I think that it’s great for a coach to have more data and to know their athlete better, but it can come in jeopardy if certain coaches will just take that and do less of the other side of coaching and the more psychological stuff, and that’s where it can become a problem. So definitely good and bad. It’s certainly a golden age for coaches who. Love data because they have just more metrics and more and better ways to, especially with AI now, just better ways to understand it and analyze it than ever before.
Trevor Connor 50:10
Well before we get into your recommendations, the last thing that I want to ask about and Rob, please dive in if there’s any other things you want to ask about, but I did find it interesting that you tied this idea of protecting the well being of the athlete into the self determination theory. So I was hoping you could just take a couple minutes and explain that. Yeah,
Mollie Brewer 50:30
so I kind of talked about at the beginning that in human computer interaction, there’s also this they bring in the idea of psychology, and one of the areas is self determination theory, so there’s three dimensions of it, and it’s autonomy, competency and relatedness, and how those factors influence motivation. And a lot of sports technologies have been viewed through that lens of how being able to choose when you work out and track your workouts can build that autonomy and then seeing your progress through quantifiable numbers can build competency, and then the social sharing aspect we’ve talked about can build relatedness. And in our paper, we wanted to bring in the idea that coaches can mediate these dimensions as well, and they might be important factors when it comes to an athlete interacting with their own data in sports and how the coaches are facilitating these aspects, by the way they filter and manage the data for the athletes. So we see the relatedness with the coach interacting, explaining workouts, using the data to guide resources and guide individualization of training. We see the competency where they’re managing the environment, how the data is shown and interpreted alongside the athlete, but then their tension arises, and that autonomy, it’s a value for users to have agency over their own data, and we saw in this environment that there’s a lot of metrics and information that’s being collected that the athletes are not actually viewing. And so that’s the tension that arises. We see why from the coach’s point of view, and there’s value and respect in that reason of the impact data can have. But is there future research that can ameliorate this tension so that the athlete can have agency and autonomy over their own data, but the coach is there to support them along the way. So
Trevor Connor 52:19
this goes back to what Rob said earlier about potentially giving athletes the ability to opt in, to choose what data is shared and what isn’t shared. And I get the other two with coaches can use the data to help them better relate with the athlete, to build a relationship, and certainly can be selective in the data they share to help give the athlete a sense of competency. So it can be a very valuable tool. So Molly, I think the last thing to ask you about, you finished out the paper with some recommendations for the what do you call coach facing data systems? So can you tell us a little bit about what you’re recommending to help coaches with their interaction with the data and with these tools? Yeah.
Mollie Brewer 52:58
So a lot of these design recommendations were targeted for technology developers and other researchers in the human computer interaction space, and one of the biggest ones was integrate those siloed data sources so allow coaches to pull the information from the multiple platforms so they can get the complete picture and centralize those data streams, and that would improve efficiency and accuracy in the decision making and help the coaches. Another one was to enhance the transparency and explainability. So that goes back to those black box metrics to build trust in a lot of these technologies the coaches need and want clear insights into how the metrics are generated, and this just ensures that the data is interpretable and actionable for them, and they can apply those data points within their sports context. The other one we touched on a lot is designing technologies that balance that privacy and utility. So keep the athletes well being in mind, and keep the privacy at the priority, but the ensure that the technologies are still meaningful for performance management. So finding that balance between helping the coaches use the insights to facilitate performance optimization, but don’t cross the line in the over surveillance and the privacy concerns, and then one of the other biggest things, which I’m not sure we talked on, but it was like enabling the long term data continuity. And one thing we did see in collegiate athletics was there’s athlete turnover. It’s collegiate sports, they turn over every four years, if not sooner, there’s staff turnover. That’s something that’s in all professional sports. A new coach can come in with a different philosophy, new technologies are added and stopped using, and this can disrupt data tracking for historical data trends or benchmarking. And right now, a lot of times you can’t pull data from a past technology and then be able to put it into a new technology to make insights. So when you switch to a new technology, often you lose the historical data that you once had. So that was like another thing is to be able to pull raw data to use in special. Use cases, but also be able to transfer information from one technology to another, yeah,
Rob Pickels 55:04
touching on some of that, Molly, the nice technical term that you used was downstream reasoning across data streams, essentially removing the proprietary nature of a lot of the technology that we have. And I think that this is a big one to touch on, because it is opposite what a lot of companies are trying to do right? If I make this proprietary, and that means that the user has to stay within my ecosystem, because my products work together, because the analysis software, then that drives customers right? And this is a really big divide between perhaps what benefits the company in terms of revenue generation, and what benefits the end user in terms of usability. And this is something that I see a lot of issue with, and you have brought it up more than once, right? That everything is siloed, right? One APP talks to another, one piece of hardware doesn’t talk to the other, so on and so forth. And for the end user, I think ultimately we do need to find a way that this is able to be used across data streams, because that ultimately improves the effectiveness of all of these technologies. Correct?
Mollie Brewer 56:12
Yeah, I think that’s like a tension point between it makes sense in the technology developer landscape, but doesn’t make so much sense in the end user application approach to it. Yeah,
Trevor Connor 56:22
so Molly, I know this concern goes a little bit further. There are also issues that you can run into potentially with different platforms. I know you have a bit of an opinion on this, or do you want to tell us or share your thoughts with that? I
Mollie Brewer 56:35
think we see what a lot of our coaches were dealing with, the turnover in technology and the long term data continuity. We see it in cycling as well, like we have platforms where we have 13 years of data on in and maybe a new platform, a new technology comes up, but we’re hesitant to switch, because we don’t lose all of that insight and that data, and it just doesn’t easily transfer. But we also might use a platform because it integrates a lot of our technology into one, like their in house systems, and we can pull our bike computer, we can pull our wearables, and it can all go into the calendar interface. And so it makes it easily for a coach or an athlete to view it. And those are important for coaches and athletes. And things that need to be considered when we start using technology or moving technologies is, can this information be carried over, and can the important metrics that we use be integrated? And we saw that in the collegiate sport environment as well.
Rob Pickels 57:25
Yeah, I’ll call this out specifically for me at what place I see this is with Garmin, because my Garmin computer is always telling me what to do. It’s like you’re under trained. You need to do 16 hours of base riding today, but it has no clue what I’m doing when I’m riding inside on the trainer, because I don’t use my Garmin computer from riding on Zwift, and so it doesn’t have insight and access to that. And I don’t necessarily use the Garmin platform because it isn’t integrating when I use because I have a wahoo computer as well. I mountain bike with a wahoo computer, I gravel bike with a Garmin I don’t I’m weird like that, and so I can’t get all of this into one place, and so I end up using training peaks for a lot of that, because training peaks will pull that information in. But I do see what you’re saying here about switching.
Trevor Connor 58:10
Well, I wonder if, in your course with Dr Seiler, he brought this up last week because we did an episode with him talking about some of this data, and he was very negative about some of these broad reaching metrics that tell you things like, here’s how ready you are to train and here’s how fit you are right now. And when you reach out to the companies and say, How are you calculating this, they go, Oh, that’s proprietary. We’re not going to tell you. And he basically said to us, when they say it’s proprietary and they’re not willing to share it, I’m very reluctant to trust it. So I didn’t know if that was part of your discussion in the course with him last week, but that was certainly something that the coaches brought up in your paper. They don’t like black box.
Mollie Brewer 58:48
Yeah, I don’t know if we necessarily touched on that, but I think that was a notion that was very much expressed by our coaches as well. So they’re different sports, but maybe the high level coaches are not that much different in how they view and interact with technology to support their athletes. And I think building trust and metrics are important, and that transparency is a really important factor. Let’s
Trevor Connor 59:11
pause for a minute and hear from Dr Seiler himself, expressing the issue of validating the data.
Dr. Stephen Seiler 59:19
Love, hate relationship I have with these tools. I do think that there’s a lot of good that comes from it. I mean, the digitalization of the data, we’re able to capture some things. The only problem with it is that it’s very easy to create new metrics in a digital landscape, and it’s almost too easy in the sense that you can divide this by this and take it to the second power, and all of a sudden you’ve got a new metric without paying the price of validation and all you know, the rigor. So that’s my concern. Is that the digital tools, it’s too easy to just make up a new metric that seems, on the face of it to be a good idea. We need. Need to be critical. We need to be self critical in the way we use the metrics, you know. And I think it would be nice if the generators of these programs were also a bit critical as well, because you don’t want to train two metrics. That’s the danger, I think, is that athletes begin to like, for example, accum, they say, oh, I need to get my TSS up to the normal level, right? Didn’t get enough TSS, then you’re training two metrics, and that’s dangerous. I think
Rob Pickels 1:00:26
Molly, you talked about one area for future research, and that was taking what you did, this was with coaches, but taking a very similar study to athletes, or maybe student athletes. Where else is the future? Where else are you going moving forward?
Mollie Brewer 1:00:39
I think it is definitely looking at the assets point of view is like, how do they feel about all of the things that we’ve just discussed? Do they look at it as overly complex? Do they need support in understanding these metrics? We don’t know yet, until we talk to them. We’re looking at how evolving policies and rules and where wearables fit in. So we talked about that with the balance between privacy and performance insights, and we’re looking at it through a lens of like contextual integrity. So contextual integrity is looking at privacy and security through the context in which the information is flowing. So a doctor may be able to view your medical records, and that’s okay, because in the context they’re helping you address a health concern so they can use your medical records. And we’re looking at performance metrics in the same light. What can a coach look at in the context of sports to define and view policies and influence policies? We’re looking at how wearables are changing the landscape of sports, and maybe how policies need to be updated or altered to include this new stream of information. So
Trevor Connor 1:01:43
I kind of hinted at this earlier, but I’m very interested in directly asking this question, are you seeing a difference between male and female users? It was good to see in your study, you were looking at both women and men’s sports.
Mollie Brewer 1:01:57
Yes. And I would say, through this study and the conversations with coaches. We couldn’t directly generalize or answer that question, but it’s something that I’m very interested in. In the future is to look at if there are differences in how females and males interact and use technology and data in their sports practices.
Trevor Connor 1:02:16
Have you seen anything in the research to indicate anything yet? Or really, this is something that the research needs to be done. I don’t
Mollie Brewer 1:02:22
think in evidence based research. I’ve seen anything personally, so I think it does need to be done, but just through communications with other researchers and observations. I think that there is a discrepancy in how male and females interact with technology and data, but I think we need to bring some evidence based science to it to make those claims, or to improve technology use if there is a gap.
Rob Pickels 1:02:46
And Molly, you’re currently studying this in the University of Florida, and I know that you’re presenting at an international conference in November, right in the Netherlands, a beautiful place. How big of a field is this at this point? Is it growing? Is it emerging? Are there other groups out there that are also studying these problems along with you? So
Mollie Brewer 1:03:04
the first conference we’ll be going to is in Japan, but we are also going to one in the Netherlands. So the Japan conference is the called Kai computer, human interaction, and it’s all the disciplines coming together to highlight the evolving research. And our paper was one of the ones accepted to show this new kind of interaction with data that hasn’t been presented in research yet in this community. And then for the first time ever, they’ll have a separate sports Human Computer Interaction conference, and that’s the one that will be in the Netherlands. So it just shows how this field is evolving and emerging. And I’m very excited for that one to get to talk to other researchers that are interested and paving the way for research to be developed in this area. And there are researchers that are looking at this type of research, a lot of them with athletes. There’s a lot on training load management that has just come up, which is great. Like all these recommendations for how you should manage your training and how athletes are interpreting that and interacting with those recommendations, there’s a lot on how athletes interact with their technologies, and maybe adverse conditions, or winter sports, which is a consideration of cold weather, affects hardware, gloves, clothing, affects how individuals interact with their technology. There’s also in cycling, how people commute, like improving safety measures for athletes who ride their bikes to work among traffic. Those are other fields where it’s beyond the performance side, and because we know in cycling, you can ride a bike many different ways, and it doesn’t always have to be about performance. And so there’s researchers investigating making cycling safer on the roads, which is very important, and they’ll be represented at this conference as well.
Trevor Connor 1:04:42
So that kind of leads, I think, the final question to ask you, before we close this up, your research was on team sports, but you look at a sport like cycling or endurance sports, but particularly cycling, cycling might possibly lead the sports world in terms of the. Quantity of data that is collected. So I’m interested in how you would apply what you learned from this study to the cycling world.
Mollie Brewer 1:05:08
Yes, I was saying that I think cycling might be the leading sport and able to view metrics like just at their disposal while they’re moving and participating in their sports. So we have a cockpit of metrics, and I’m sure we could all interact and share all the fields we have on our Wahoo or Garmin bike computers and our head units, and all the information we’re getting in a single ride and in a race. And so one thing I’m interested in doing is investigating how cyclists of all levels and across all the disciplines that we have interact with metrics. Which ones do they think are the most important, and then how do they apply the recommendations that we get from these platforms you mentioned Rob like, what your Garmin says, like you’re unproductive, or maybe something will recommend that you do a more aerobic workout or more anaerobic workout, and I’m interested in how cyclists are interpreting these, how they’re applying them, how they’re trusting them. And then, how can we improve visualizations? How can we improve how information is given that align with sports science practices? I think, Rob, we have to go all the way back to like where I first came in with you is, are we aligning with best practices in sports because we want athletes to reach their goals and to increase their performance, because nobody wants a decrease in performance and nobody wants a plateau where they’re not getting better, and I think these sports technologies can facilitate that, but are we giving them the best advice and are we Helping them to reach that and avoid the pitfalls of over training and chasing after metrics and leaderboards that could inadvertently have a detrimental effect on performance. I
Trevor Connor 1:06:52
hate to say it, but I think it’s time to close things up, so we’ll get to our take homes before we get there. I do have a question for our forum, so please go to fast talk labs.com join the forum and tell us what you think. And here’s the question for this episode. As an athlete or coach, have you considered how you interact with data? What would you change? So that’s our question. Looking forward to hearing your answers. So Molly, first time on the show. But I know you listen so you’re familiar with how we close things out. We have our one minute take homes. This is where you summarize what you think is the most important thing for our listeners to take from this episode. So would you like to go first? Sure?
Mollie Brewer 1:07:35
I think that technology is very valuable, and it has a place in sports. It can provide a lot of great insights, and it can guide us to reach our goals, but we should be mindful of the potential pitfalls of it, and keep in the forefront of how data can affect our emotional well being, and take all that into consideration when we’re applying data and using it in our sporting journeys.
Trevor Connor 1:08:02
So I’ll go next and let Rob finish this out, because mine is along the same lines. What really caught my attention and I mentioned it earlier because I really hadn’t given this much thought. I’m a data geek. I love data, and I love it when my athletes send me data, because in my head, I know I’m looking at the data to try to help them, and I admit I hadn’t given a lot of thought to what is the psychological impact on the athletes. Are they worried about the data they’re sending me? Are they worried about me seeing their sleep scores? And that’s something I’m going to be a lot more aware of moving forward. And I think it’s an important conversation to have with each athlete of is this helping you, or is this actually making things worse for you and making sure we’re only looking at the data that helps them?
Rob Pickels 1:08:49
Yeah, for me, I’m gonna back it up and really look at big picture. And something that we talk about a lot on this show is the value of a team around a coach and around an athlete, right? And that we can’t expect one coach to be able to handle all aspects of helping that athlete achieve their goals. And this is a very eye opening experience to me, because Molly like this is another aspect of a team that really needs to be there. And for me as a coach, my God, when I sit here and think about this, there are so many hundreds of 1000s of things that we could also be thinking about. And I’m just, I’m super excited that there are people in the world that are taking on these questions, because ultimately it helps me as a coach, work better with my athletes, and that I have the support from people like you to be raising these questions right. Like Trevor is saying, I have not thought about this aspect of data and my athletes, and without the research that’s happening out there, we would not necessarily be given that information that we can then as coaches, you know, as the actionable interface between the athlete able to utilize So, yeah, super interesting. Like, I. Said, the first time in a long time, I’ve had to actually kind of learn about things before coming on the podcast. And this is a totally 100% brand new topic for me, and it’s fascinating.
Trevor Connor 1:10:10
Well, Molly, we’ve been trying to get you on the show for a while. I’m really happy that we got you to join us. So thanks for doing this. Yeah,
Mollie Brewer 1:10:18
thank you. It’s kind of nice coming full circle of being the intern in the very beginning, working with Rob, and then also getting to work with you, Trevor and Chris in the very beginning, and now coming back on and saying, Look at what I’m doing, like I’m getting a PhD, and I’m integrating what I learned from all of you guys into practice and trying to enhance the sporting experience for users and athletes?
Rob Pickels 1:10:43
Yeah. I mean, I think it’s fun for me as well, right? Molly, that I get to learn a lot from you, you know? And it’s funny. I think that the stuff that you’re now teaching me is more on the forefront than you could have learned the stuff that I taught you from anybody, but feels like the stuff I’m learning from you is pretty specific and special here. So well. Thank you
Trevor Connor 1:11:01
for saying that we’re excited to see where you go from here. I’m sure we’ll have you back on the show to tell us all about it. Thank you. That was another episode of fast talk. The thoughts and opinions expressed in fast talk are those of the individual subscribe to fast talk wherever you prefer to find your favorite podcast, be sure to leave us a radiant review. As always, we love your feedback. Tweet us at fast talk labs. Join the conversation at forums dot fast talk labs.com or learn from our experts at fast talk labs.com for MOLLY BREWER, Dr Steven Seiler, Dr Michael Rosenblatt, Brad Colt and Rob pickles. I’m Trevor Connor. Thanks for listening. You.
