#030 Sport & Data Science Communication

In this episode of the Decoding Excellence Show, I'm sharing my thoughts and opinions on a critical aspect of sport & data science within sport organizations. This was something I have been thinking about more and more as the resources surrounding sport and data science continues to grow.

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Key Takeaways

• Communication is the critical layer of sport and data science: as resources and tools grow, the ability to convey what the data means inside an organization matters as much as the analysis itself.
• Having opinions about your field is part of the job: thinking out loud about where sport science is headed forces clarity that private musings never produce.

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Episode Transcript

This transcript was automatically generated. While we strive for accuracy, some words or phrases may be misheard.

[00:00:00] Sport Science, Strength and Conditioning, High Performance Coaching, welcome to the Decoding Excellence Show.

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[00:02:20] Hey everybody, today on the Decoding Excellence Show I am bringing to you a random show, but this show is going to be centered around the discussion of data science, sports science, and some of the common errors and problems, limitations and challenges that I see that exists in both. I'll be sharing with you my perspective of both disciplines, data science and sports science and hopefully providing some commentary and discussion about what we can do better to really bring out more actionable information to the right stakeholders in

[00:02:53] The organization. So without further ado, here's the random show centered around data and sport science.

[00:03:02] Hello everybody, welcome to this week's episode of the Decoding Excellence Show. Like always, I'm Adam Ringler, and today I wanted to discuss a little bit about data and sports science, and if you work in either disciplines, what you most likely have discovered is that we have this overwhelming crisis that is happening. And it seems like most of the conferences and clinics that I've got to, it seems like rather than discussing the right questions or answers or methodological approaches to either coding languages or anything like that, we're discussing a lot of the human

[00:03:45] Elements, the emotional intelligence aspects that's required to really actually bring any sort of actionable change to organizations. And this has sort of resonated in my mind and I continue to go back and think about these things after visiting with these conferences. And it seems like we're discussing a lot about communication and what we need to do in both realms to increase our efficacy ability to effectively communicate with key stakeholders. So, you know, I feel like lately in sport organizations and elsewhere, certainly companies as well, there has been a huge boom in

[00:04:31] Hiring sports scientists and data scientists, but the problem it seems like is that at least the critique that we've had is that we haven't really delivered a lot of value to these organizations bottom line. And I would, I'd refute that. Number one, I think there's, you know, some tremendous value that has come out in the last five to ten years about training methodologies and what we can do to better identify athletes, whether it's movement dysfunctions, neuromuscular fatigue, workload management, and the list can go on and on and on about what has become

[00:05:09] Commonplace, best practice, regardless if you have a robust data science or sports science department working for your organization. So, I'll leave that aside, but what I will say is that, you know, the refute has been that the challenge, the critique has been that, you know, despite a lot of financial contributions to both of these departments that they just haven't really carried their weight yet. And I think one of the root causes for a lot of that is that, you know, for the first part of of either teams or either departments, their first mission really is we have to ask better

[00:05:51] Questions and we have to really understand organizationally what questions are we wanting to seek answers for. So, a lot of times it seems like key departments and key organizations will, will make this financial investment into sports science or data science without really having any formulated questions about the organization. And that's this obviously the first part is that we have to ask smart questions, but then we also need to be able to wrangle and actually collect the right relevant data. And that has obviously been done on a sports science standpoint with

[00:06:29] You know, wearable technologies and force plate technologies and a number of different athlete management systems have come out and the list can go on and on about performance technologies, but we obviously have to collect valid and reliable data regarding our student athletes or our professional athletes if that's the realm that you work within. And then obviously the third part is we need to uncover insights. We need to have a good understanding about what the information is telling us. And I feel like a lot of the times what I see organizations do is they make that

[00:07:06] Strategic investment. They get either the technology first. They assemble the team around technology and then they hopefully try to figure out a question. And I think that's a backwards approach. I think it needs to start with questions first. We need to understand what the mission is. What do we need to do or accomplish during that mission, essentially the collection of data. And then we need to use it, break it down and better understand it for you know, key measurables or performance indicators from that. But that is all well and dandy, right? I think

[00:07:43] Those are the the obvious things that we should do in either department, whether it's data or sport science. But where I see a lot of these, you know, conferences, clinics and symposiums discussing more and more about is that once you have these things, what do you do with it, right? And this is where people's skills and your ability to communicate what those insights actually really mean for the sport organization or department that you work within. I think that's incredibly rare. And I think it's smart that more of these conferences are discussing

[00:08:20] Sort of the communication piece because I think that, you know, what we find most commonly is that sport scientists bring a huge academic background and a well sort of versed research knowledge into an organization. They obviously have the technical skill sets to run the instruments or to in the sake of a data science standpoint to, you know, collect clean and manipulate data in whatever programming language of choice that they particularly use. But what is challenging for both respects is that how do you communicate what you find and the nice little gg plots or the

[00:09:02] Nice little tables or analytics that you collect on both sides? How do you communicate that to the key stakeholders, the ones that actually make decisions that affect the bottom line? So this is essentially where I wanted to go with this article, right, or this podcast here because I think that, you know, begs the question, if we are collecting the right things and we are, you know, obviously, communicating this information is the other party listening. And that is something that I also see when I talk to colleagues across the country and across the globe, is that

[00:09:43] They might have the right information and the right, you know, inference from that information. But the counterpart isn't using it to make any sort of actionable decisions. So what I have sort of understood in the course of my career and discovered that, you know, I think sometimes the very best leaders all recognize that data science and sport science can deliver something to them, right? But I think that the common challenge is how is it being delivered to them? That's I think that's the problem. I think that's the air that more of us need to continue to refine from a skill

[00:10:26] Set standpoint of actually that communication piece. So we have great data. We've collected that data in a very robust and very predictable way. But how do we actually communicate the findings to those people? And that is something that I think is being recognized on both parts, right? Like the key stakeholders of organizations understand that there's there's value and objective data. The other side of it, sport science and data scientists understand that there's a huge value in data. But there's this disconnect that exists in between them. So sometimes the the common things

[00:11:02] That I see is that, you know, I sort of infer due as probably the first fundamental flaw that we as both scientists need to, you know, improve is that a lot of the times we'll have these algorithms and we have this data inside and we present it in a way to a sport coach or a key stakeholders. But the language that's being used in our presentation or in the communication is unfamiliar to the listener or to the coach or to the to the athletic director or whoever it might be. So that is something that we need to actually improve on. We need to improve on our ability to relate

[00:11:41] What we find to communicate it to translate it into a language or a vernacular that is better understood by the counterpart. So it might be perfectly appropriate when we are sitting amongst a table of fellow sport or data scientists to communicate in a way that is, you know, the language in which we operate or which we speak in or which we talk in. And that is perfect, right? That's what you would expect to hold a very highly academic vernacular language when you're discussing key concepts with colleagues or peers, right? But when we are communicating that information to

[00:12:20] People that might not be as well versed, I think it's better off to put it in more layman's terms and more coach speak, if you will, and actually translate what our findings are to what the sport coach actually needs or communicating in a way that is better inferred by them. Secondly, I think a lot of the times what we'll see is that, you know, most of the times I've seen it and I've certainly have been through it very parts of my career is that we will go and chase down a rabbit hole that is that's being pursued by a key stakeholder or a sport coach or whatever it might be.

[00:13:00] And what essentially what they're asking for is to produce data or produce information that essentially supports their hypothesis, right? And I think that is a that's a challenge that we also have to face, right? We are essentially scientists that need to go out and objectively evaluate and collect data and and not hold a bias about an opinion one way or another. And I think it is valuable for us to be able to seek the truth, right? And not necessarily seek the opinions or data that will best support the hypothesis of a of a leader or of a stakeholder

[00:13:42] That wants information that will best support their own speaking notes or their own presentation. So, you know, a lot of the times what I've seen and heard is that sport scientists and data scientists get put into a corner of, you know, essentially searching and seeking the answers or the air, you know, I use this with air quotations, the truths that the key stakeholders want. But the very best I think that we've worked with and I certainly I feel like currently, right? They are, you know, unbiased about what answers come out of data or come out

[00:14:23] Of sport science. They just want the truth. And if that means that it goes against what their opinions are or what their beliefs are or what their, you know, most priestly held beliefs might be, then what the very best do is they alter their beliefs and they have the right to be wrong and the right to change their mind. And I think that is a really powerful hallmark of a great leader. And then finally, what I see sometimes across the board is that when sport science or data scientists actually go and present their information, they're presenting in a way that sort of shoots

[00:15:07] Themselves metaphorically in their foot, right? So they might create really sound charts and visualizations and graphs or whatever, but they actually get a lot of the times I, the conversations I get from people is they're very nervous to actually present this information, right? Wrong and different. No other that they're nervous because they don't want the other party to extract the wrong ideas from the analysis. And I see that all the time. Is that, you know, they will, you know, go out of their way to do everything from a protocol from a criteria standpoint, very, very robust

[00:15:47] And sound. But it's again, when you're standing in front of a crowd of your colleagues or peers organizationally wide or from a conference that they just simply don't want the information that they are presenting to be miscommunicated. So a lot of times that fear really sort of derails them from actually doing, you know, their best work and presenting their ideas in the best way. So again, I think all three of these commonalities all center around communication skills. And that is something that I think that as we go through our own sort of curriculum of development

[00:16:32] That we need to have a better understanding of what we need to do to communicate these ideas with key stakeholders. Rather than potentially, you know, learning a new software system or programming language, we just really need to spend more time on our ability to communicate because at the end of the day, no matter how great the information or chart is, most of the times great coaches will, they'll lean on your translation of the data and translation of the sports science to actually lead them in the direction of where they can drive the decision making process.

[00:17:14] And that's just something that I don't often, you know, I don't often see done yet, or at least continues to need to be discussed amongst us. It needs to be championed by us. And we really need to put a greater emphasis on what we need to do to better those skill sets. So, you know, ultimately, I just think that what we collect and how we collect it has always been, I think, really, really sound. And I think that, you know, technologies allow us to collect things at a rapid speed that was otherwise 10, 15 years ago, really challenging to objectively measure.

[00:17:59] And then, obviously, with the collection of data science sort of bleeding over into the sport organizations, what we have is a lot of things that key stakeholders don't really understand. They understand that there's value in it, but they don't understand potentially what the value could be or what the information is telling them to do. So, my recommendation is that we need to really try to, I don't want to say water down what we're finding, but have a better understanding of how to communicate data and sports science to lay audiences, those that don't work in this

[00:18:43] Profession, those that don't bleed this profession, that they don't love this sort of this pursuit. We need to have a better understanding of how to communicate those things. And that might mean, ultimately, how we organize data and sports science teams and departments so that when we do put together these departments, we put together these people that first and foremost that we are doing so in a thoughtful way that essentially starts with the right questions in the beginning and then seeks out the right technologies to better our ability to answer that question

[00:19:28] And then position the right people in the right spots, the labor force, those with the technical and skill set knowledge to be able to do it, but then all the while to wrap a bow around all of this is to be able to make sure that there's people in the organization that can translate what they find to the right people so that those with the power and the ability to make the decisions within the organizational chart actually feel confident with the information that they have presented to them in a way that they can actually understand.

[00:20:06] Hey, everybody, that's going to be it for this week's episode of the Decoding Excellence Show, the Random Show. It is my hopes in the new year to try to bring you a show every single week. If it's not a interview with some sports scientists or sports performance coach or leading expert in their discipline, then it's going to be me. I'm going to practice the habit of being a professional behind the microphone and continuing to bring you a show every single week. Unsure exactly whether it's going to be Fridays or Mondays for publication dates, but stay tuned.

[00:20:51] I'll promise as I continue to refine our own process here to give you a date so that it could be a little bit more predictable than the Random Show that just pops up here and there. But like always, thank you so much for supporting the show. I hope you got a lot of value and hopefully this Random Show simply made you think because that is the nature of the Decoding Excellence Show to really try to bring out the very best ideas. As always, there's a number of different ways that you can support the show. The first thing is I have a monthly newsletter that goes out.

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