Sports Science, Subjective Measures, and Following Your Curiosities with Adam Virgile
On episode #97 of the Hockey Strength Podcast, I sit down with Adam Virgile.
Adam Virgile is currently pursuing his PhD in Human Functioning and Rehabilitation Science at The University of Vermont (UVM). He also serves as the Sports Science Coordinator at UVM where organizes the collection, interpretation, visualization, and applied integration of physiological data from the Men’s Ice Hockey and Men’s Basketball teams.
Prior to UVM, Adam was the Assistant Strength and Conditioning Coach (2013-2015) and Sport Scientist (2015-2019) for the New York Rangers.
Through his personal brand, Adam also creates tools and sports science resources including Microsoft Excel and Google Sheets tutorials, plug-and-play sheets/files, and infographics. You can find all of that at his website, adamvirgile.com
You can also find Adam on Twitter (@AdamVirgile) and Instagram (@Adam.virgile)
You can listen to this episode on…
Full episode transcript:
David Rosales: Adam, welcome to the Hockey Strength Podcast, how are you?
Adam Virgile: I’m good, how are you doing?
David: I’m doing well, thanks. So we’re kind of in a reverse situation here. You are in my home area of Burlington, Vermont. I am in New York City and you used to work for the New York Rangers so we’re in this kind of place reversal here. How are things in Vermont?
Adam: They’re pretty low-key from a COVID standpoint. You’re holding down the fort me for, and I’m holding the fort down for you so it’ll all be good. We’ve got each other’s back here.
David: Exactly, exactly. I want to start with… What was your start in strength and conditioning?
Adam: My start was just through school I studied exercise and movement science. That was the path that I wanted to go down. Not necessarily strength and conditioning, but just enhancing athletic performance in any way that I could. I also minored in nutrition because I thought that that had a large impact on performance as well.
You know I was taught through school how to periodize programs, cue athletes, and run them through workouts and that’s where it started. Then I got hired on by Reg Grant, who was the head strength coach with the Rangers at the time. And that’s that. I was really fortunate to get a job right out of school. And it took off from there.
David: Let’s back up to that, “fortunate enough to just get hired by the Rangers” right from your undergrad at UVM. How did that come about? And what do you think it was about your skillset that made you ready to slide right into professional hockey?
Adam: Well *laughs* this is gonna sound bad… But I don’t think I was a good fit to slide right into professional hockey. They took a big chance and I think it worked out okay. During my tenure at school I had a relationship with a professor here and I was just really curious about everything.
So I would volunteer to take the ice hockey athletes through Wingate testing and different tests. And help them run camps and just ask a lot of questions. When I graduated, he [the professor] gave me a call when I was still here in good old Burlington and he said “Adam I heard about this gig I think you’d be a good fit for it.” Then I get a call from someone in a couple of days and a few days later I get a call from Reg.
He introduced himself as the head strength and conditioning coach for the New York Rangers and I thought it was a joke. This professor he liked to joke with me all the time. So I kind of played it off. But then the next thing I know, I’m sending in a résumé and doing an interview and all that stuff. But to come back to your question, I think a lot of the stuff that I did in undergrad, just the curiosity that I had and the willingness to help others with anything involving exercise ad movement science. For whatever reason, that professor pulled my name out of a hat to give to Reg to call. That’s how I got the job, through knowing that professor but also at the same time doing some extra curricular things that painted me in a certain light.
David: And now you end up, right after you finish school, shipped down to New York and you’re working all of the sudden for the New York Rangers. And you’re watching Henrik Lundqvist and all these other pretty famous Rangers walk around. What was that experience like just your first few weeks on the job?
Adam: It was interesting but I never skated. I was kind of a basketball guy growing up, In the winter I played basketball. So when I got to the Rangers, I’m seeing these people. But to me they’re just people. I’m coming from a college environment also so I don’t really understand the magnitude of being a professional athlete.
When I see a guy getting helped by someone, putting their weights on the bar, I’m thinking: Why are you helping him? Why can’t he do it himself? Tell him to rack his own weights? I didn’t know these guys. I wasn’t mesmerized by any of the stardom I guess that I wasn’t exposed to.
David: And your role was just strength and conditioning at first? Your first few years?
Adam: There you go. So part of my job was to help manage the data collection. I didn’t really know what that meant. But I did know going into the job that there was some data being collected and I guess I was interested in research and technology that I’d be involved with this stuff.
So I was hands on with the athletes implementing programs and at the same time I was collecting a lot of information from them at the same time. For example we had strength and conditioning software platform that we’re trying to put our programs into and relay the programs through the software platform. And then the athletes were wearing devices on the ice. And a bunch of other things.
Eventually I got really interested in this information because throughout school I was taught how to periodize programs and cue athletes but I wasn’t exposed to all this different technology and the metrics and the interpretation of what everything meant. So I started trying to figure that out a little bit then I started to figure out how to visualize it and analyze it. Eventually I reported back to Reg. Some of stuff he enjoyed and thought was beneficial for the programming side of things.
More questions come from the data, so then it reached other people and other people had questions. What this led to was me spending a lot of time on the computer when my primary job was to implement programs when I needed to perform these tasks. But I was always taken away by the computer to answer these questions people had.
That’s where the sports science stuff really began.
David: We’re going to get to the sports science stuff in a minute but I just want to underscore that already I see a similarity in your path. You took the extra step to go after some of your curiosities and explore them. In this case it was a lot of testing and analyzing numbers and of that stuff. And that led to creating your own opportunity.
Adam: Yeah, it literally did.
David; I think that’s a super cool lesson for everyone that sometimes you just kind of have to take initiative with things and explore your own curiosities and see where that takes you. It might be a path exists. I think I read this, now please fact-check my research. But you were the first ever sports science person for the Rangers.
Adam: Yeah. What you said is literally what happened. I was the assistant strength and conditioning coach and eventually a question was proposed to me like, “do you want to do more of this computer stuff or more of the strength and conditioning stuff.” I said this computer stuff was pretty interesting so let’s go with that.
The next question was, “What do you do? Can you write up your job description?” And that’s kind of how it happened more or less. But like you said. I think it’s really important to explore your curiosities. You don’t know what your passions are until you get invested into your curiosities and find out what those passions are to begin with.
David: For sure. And you literally created a category. We talk a lot about in business and marketing, you have to create a category, break the category. You literally made something that didn’t exist before. I think that’s super cool.
You stayed with the Rangers for six years. What were some of the biggest lessons you learned over the course of that time? That might be too broad of a question, but take a whack at it.
Adam: Yeah, I learned a lot. I think all of my colleagues that I did because when I came in I did a lot of things that were not okay. I think probably the biggest lessons that I learned was seeing through different perspectives.
What I wasn’t really exposed to in college was.. you know I would do something and I would have my perspective and the athlete would have theirs and that was kind of it. But now for example, when I created a report and it had a player’s body weight on it or something like that. Knowing how the player is going to perceive that information, how the strength coach, the athletic trainer, the coaching stuff, management, the owner, how all those different people could perceive that information.
An example that I have is, people are probably going to be like, “this is so dumb, you’re an idiot,” and I probably was. So I was from Boston and I had a computer skin on my laptop that was a Boston team. The New York Rangers are owned by the Madison Square Garden company and I was kind of a fan of the team. So I had it on my computer. And I walked around with it on my computer for a long time. And I was told to take it off multiple times but I thought it was kind of a joke. Eventually there was a real hard sit down and they told me, “You have to take that off. Could you imagine if the owner saw that? You’d be fired right away.” I didn’t think of that.
So little things like that I grew up through the Rangers and I look at a lot of my staff members there was part of my family. That helped me grow up to a certain extent. I’m not there yet, but I made a couple of steps in the right direction I think.
David: Yeah none of us are there, Adam. None of us are there. That’s a really cool anecdote to share that a lot of strength and conditioning and coming up in the field is just growing up as a human being first and not necessarily learning everything there is to know about strength and conditioning and sports science.
With that, I do want to transition to sports science because this is a role that you kind of created because you are one of the, I’m going to think of a better word after I say, this, cavaliers of creating sports science into the mainstream strength and conditioning.
How would define sports science and what does that even mean to talk about that in the field?
Adam: I want to take a step back for a second. I’m not a pioneer or a cavalier, they’re a basketball team, in this field. Sports science has been around for a long time. Although, as you alluded to with your question, it’s still kind of an iffy definition. It’s not well defined. But it has been done in other places outside of the US for a really long time to a high degree overseas.
In the US, it had been done in other sports but I think hockey is starting to employ sports scientists. Hockey is a bit more traditional than other sports so I guess I was one of the first officially named sports scientists in the NHL, but, with that being said, other strengths coaches — before I was the sports scientist Reg was also the sports scientist. And I know other strength coaches who are also sports scientists. They’re the head strength coach, they’re the nutritionist and they’re the sports scientist. So all that stuff was being done there just wasn’t really a dedicated position for that.
What it means is, the way I see, is utilizing information coming from an athlete’s physiology in an effort to optimize performance outcomes.
It might be to reduce injury risk, and also just to improve their performance in what they need to do on the ice.
David: Okay. That makes sense. I’m just translating for my own brain that doesn’t know a ton about sports science. You collect data, and you use that data to make positive change. Whether that’s reducing injury, increasing speed, performance, et cetera.
Adam: Exactly. And I think one of the key differentiators just from — I don’t know actually know that I think about it… we’ve had stats for a long time like game stats and performance stats. But I think the key thing that differentiates the typical sports science from that type of stuff is integrating physiology to have a good understanding of physiology to incorporate that information when making decision that are meant to improve performance outcomes.
David: Okay yeah and that’s when what you do gets more specific integrating the specific skills of a strength coach with the science/technology background in bringing in new data that hasn’t been used before.
Adam: Exactly.
David: After six years with the Rangers you went back UVM (The University of Vermont) to pursue your PhD which I’m assuming is very related to sports science. Why don’t you talk about why you decided to do that and what research you’re doing.
Adam: So, I’m a planner. Two years before I left the Rangers this was in place. The reason fro that was more of a family decision; that was the primary reason for it. But — and this is going to get a little sad so I apologize — one of the main reasons was also to pay back that professor that got me the original job with the Rangers. He’s a professor at the University of Vermont and I thought I’d be nice to share my experience with him and we could work on research together as kind of like a “thank you I appreciate you” thing.
He ended up passing away recently of a sudden heart attack. That’s no longer there. But I have this passion in going after research that I think he would be perceive as being valuable. Those are the two primary reasons I started doing the PhD: for family and for him.
The program, they don’t actually have a sports science program at UVM. The program is called “Interdisciplinary Health Sciences.” Before it was called “Human Functioning and Rehabilitation Sciences.” But I was confident with this professor here that I could do sports science research even if the program wasn’t geared towards that. I’m continuing that pursuit and I am doing sports science research with the athletic performance department.
The primary things that I’m looking at are subjective questionnaires and how they related to sports specific performance. Things like rating of perceived exertion, well-being, stress, energy levels, perceived recovery and how those coincide with sports specific performance.
One of the things that’s difficult about sports specific performance is that it’s really difficult to quantify. And it’s really difficult to decipher the expectations of an individual athlete using box score stats. If you’re a fourth line player, what do you expect to see in the box score? Probably zeros across the board with some time on ice and maybe a couple of hits. But that’s about it.
David: Penalty minutes.
Adam: Yeah. PIMs, maybe. That’s great, but also it provides an advantage for the other team. So if you’re comparing athletes and their performance levels, if you’re looking at goals and assists that’s great if your primary job as an ice hockey player is to score goals or get assists.
So one of things I’m doing is asking athletes how they perceive their performance to be. Gimme a grade for yourself on an A-F scale for every game. I’m also asking the coaches to grade each athlete on an A-F scale. Also, when we’re looking at performance we can use the indicator of performance as whether or not the athlete is meeting the expectations set for them. I think that’s an exciting part of the research.
With all these subjective scales we’re using, the end goal is understanding how they correspond with performance. Taking a couple of steps back from that is, people use and practice today scales that have colors on them, scales that are oriented in different ways. Those scales haven’t gone through validation processes that the oringal validated scales went through.
Imagine in 2000 or before that, there’s a scale: rating of perceived exertion. And we’re writing it on a piece of paper or just in black and white and it’s not exciting. Now with all these new technologies coming out people are using a colored slide with red to green and they don’t have the words that the others have or the numbers in the same orientation. I’m trying to figure out whether these scales when they’re presented in this more modern way and technology have the same validity as the scales when they were presented in their older way.
To do that we’re collecting heart rate information from all the player to see how their perceptions coincide with the objective measures of work.
David: You’re looking at subjective scores and comparing them to objective scores and seeing how objective our subjective feelings actually are. I’m not sure how far into the research you are but do you have any predictions about how that’s going to look.
Adam: I did have them, and I don’t have finally confirmation of them. But there was something I was exposed to in the NHL: there’s no in-game data. There are no wearables allowed in game and that poses a problem when you’re trying to assess the stresses going through an athlete’s body over time. Because you can collect data during practice but you can’t during games.
So you have two options. You can either simulate that information to provide a more robust picture of what’s been going on or you just give it a value of zero and totally disregard that information. To simulate that information, for us, we use data from our AHL affiliate who could wear devices during games. Let’s say you’re looking at the past three days and two of those days were games. You’re only seeing what they did in practice if you give them zeros, but if you give them something based on the number of minutes they played during the game that corresponds with the heart rate values from an AHL affiliate then at least you have something to fill in that hole that’s more accurate than zero.
You can then have a more accurate prediction of what’s going on. So that’s a long way of me saying that I had a lot of looks at the AHL data. And I ingested that and what I noticed was, from a heart rate perspective, you’d start game one of a back-to-back-to-back, because that’s how it is. Game one is here from a heart rate load, game two is here and game three is here. Almost every time.
To me, I felt that objectively it looked like they’re doing less and less. But in reality I couldn’t see a way where they’re level of effort would be less and less. That made me question how looking at training load… For example, let’s say that someones is acutely fatigued. Their training load from an objective perspective isn’t very high. But their perception of effort is still very high. What’s more important? Their actual effort and the perception of the effort or that number that is just arbitrarily low because of the presence of acute fatigue?
At UVM I looked into that. We tracked RPE and heart rate loads and we played back-to-backs. And essentially what we’re seeing is that RPE stays the same, regardless of game 1 or game 2, but we see that drop in heart rate. That’s what I expected to see. And it’s interested to see because a lot of people like to say, “oh what are you collecting for internal training load? Are you collecting RPE or heart rate?” Well, they’re not the same thing. So bucketing those two things together may not necessarily be a good comparison to make or a good exchange to make if you’re deciding what to do for monitoring training load.
I don’t remember what the question was but I hope that I answered it.
David: We’re meandering here. I want segue a tiny bit. On strength coach Twitter, you’re definitely one fo the “Excel” guys. Every time you pop up everybody’s like “Check out Adam’s new excel video.”
What is it that you use excel for and why is it so valuable to you as a coach and sports scientist?
Adam: This is actually a really good question. When I was with the Rangers I used Excel a lot because the technologies we invested in weren’t able to provide the information that we needed to get. At least in a way that I knew how to do it and a way that was packaged in the platforms with information. I needed to package it in a way I could get the information that I needed and Excel was something that was cheap. I could play around and figure things out without asking for money.
That’s where I stared with the Excel stuff.
I started at UVM last year and I started teaching. They said, “why don’t you teach class, but maybe just make up your own.” So I started teaching this sports science-based class. And with that, I was teaching my students how to use Excel and Google Sheets because I think they’re really good teaching tools for collecting data and seeing what errors you can make with collecting data and also how to visualize the information.
It’s not a very steep learning curve as opposed to other software out there. So I was like oh we’ll have an Excel project and we’ll work on it throughout the year. And then COVID hit in March. Our students at a certain point were all remote. And they said, “Adam, this is really fun project but we don’t have the resources we need to get this done now since we’re not in-person. So can you shoot videos of you doing this stuff?”
I said yeah sure, and we put them on YouTube. At one point I shared one of the videos on social media because I thought it looked pretty cool and it got a response that I wasn’t really expecting. So that’s how the Excel stuff kind of came about and I’ve been running with that ever since because people asked a lot of questions and wanted more of it.
For your use of it, it depends on your setting. Creating programs, that’s something that isn’t really fun to do and you wouldn’t be able to really do that with something like R. It’s a lot easier to do when you see what’s in front of you, and Excel and Google Sheets provide that. Coding platforms don’t provide that in the same way.
Creating program templates I think it’s great for. Creating small research projects I think it’s great for. Also, if you don’t have that much time to learn a new software, I think it’s great for that.
For bigger projects, if you’re collecting time series data. When I say time series I mean, if you’re collecting data every couple of seconds during a game or play by play NHL data or larger data sets—then I would go to something else because Excel only has so much capacity for information and visualizing.
David: When we’re thinking about a strength and conditioning coach, what are the some of the things they should be looking at in terms of data and how would you recommend they organize that in a spreadsheet format?
Adam: It depends on what’s important to them and depends on what’s important the coaches and the people around them. For example, an athletic trainer — I know you asked about strength and conditioning coaches — has certain questions that they want to be able to answer on a daily basis. And the data that’s collected for them to answer those questions might be different than what’s collected for an S&C coach which might be different from a coach.
From an organizational standpoint, what I see some strength coaches do that I wouldn’t do is overwrite data for visualization purposes. What I mean by that is you have a dashboard, you have a pretty picture of the training week. And you type in what you want to do each day and you type in recommendations for the coach. Oh this should be a hard day, this should be a light day. Then the next week passes and then they overwrite that existing information with new information so they can just print out the same piece of paper and give it to the coach.
What I think would be more beneficial would be collecting data in a more formal, organized format, and then segregating the visualization from that. So many you still have this one page of information that you’re displaying for the coach, but you’re collecting the information in a different way that looks really ugly, but you connect it to that visual information.
Then what allows you to do is you can look at data from previous weeks, and totals, and season averages, averages by player. It just gives you a lot more room for interpreting different things within the data you’re collecting
David: And when you have the opportunity to look at all you’r data in a systematic way that’s where you’re going to find things you didn’t think of before, areas where you didn’t look at, possibility to dig deeper.
Adam: Exactly.
David: Cool, that makes a lot more sense now. I want to talk about, you even have, I’m looking at your website right now, which is very beautiful by the way, I’m looking at your Excel course: Team Fitness Testing Framework In Microsoft Excel. Tell us about the origins of this course.
Adam: I honestly don’t ever remember how that happened. But I had a bunch of videos taped. It’s what I did with the Rangers in Excel for fitness testing. We had a lot of talks, and it seemed to change every year, about how information should be calculated, how it should be displayed. Should we use standard deviation? Should we assign scores to things? Should we weight things differently? What this course essentially is, it’s a robust solution to that where you can pick whether you want to create a score by a standard deviation or the maximum and minimum values in the data set. And you can adjust the scores that you give people. Do you want it to be from 1-5? 0-100? Well it automatically calculates that.
It’s going through a whole framework of creating your own custom scoring system for displaying the fitness testing information in a way that you want. You could have 10 different tests or 50 different tests and lets say you have 5 metrics per test then you have 250 metrics to look at. This allows you to create scores based off of multiple tests and bucket those scores into those categories so that you can also provide a very succinct picture so you can say, “oh, is this guy powerful or not?” All right well we have this score that’s composed of these four testing metrics and they’re weighted in this way and this is just their general power score. Then if you want more detail you can go into that and see okay these are the tests where he excelled in.
So it’s giving a bigger picture view before you get into the minute details of the testing.
David: Really then it’s just what we just talked about the previous question is: how do you take all this data and organize it in a way that you can actually use. You in the course go through in the course step by step how to do that and give a lot of suggestions for it. Does that sound accurate?
Adam: Yup
David: If you’re in a team setting and you have to test a team out I know that’s a lot of tests and printing it could be a really valuable resource.
We talked at the beginning about curiosity, which seems to me to be one of your superpowers and how that led you to your opportunity with the New York Rangers and how it led you to kind of create your own thing and you’re still taking it with you back to UVM.
So what’s something you’re curious about right now and something you’re really digging into and exploring.
Adam: My research. I’m curious as to whether all this objective data collection is necessary for making the decisions that we want to make. For example with rating of perceived exertion there are always going to be issues surrounding honestly, but at the same time, the issues that I’m seeing with the objective measures that I’m collecting like heart rate for example, could be a misrepresentation of how an athlete is feeling about the training.
I’m just really curious to better understand whether or not subjective measures could be used to give similar if not more beneficial information when making more informed decisions as opposed to the objective measures. The reason why that’s important is because subjective measures are really easy to collect, and they’re free. Essentially. They’re easily scalable. Like imagine you have a mobile app. And one of the things going on today is early sports specialization. Our kids are playing a lot of the same sport early on in life which can sometimes lead to increased rate of injury and also just dropout of sport because they get sick of it. So being able to provide a solution that could expand into the youth market, into the elderly and general population where you just open up an app on your phone and you record how hard something was, and gives you insight on yourself and your training.
It’s just like other apps or wearables that gives you information that you could then potentially use to change a habit or make a decision. I feel that there could be a lot of value in that type of stuff.
David: The keyword you said there that grabbed me was scalable. Because like you said if you can replace objective data with subjective data then now you can use that in any setting. Any personal trainer, strength coach, hockey coach could use it with needing to get a whole thing of heart rate monitors for a team, for example.
Adam: And one thing that I want to be clear on though is that I didn’t mean that it can replace objective measures, but it gives people a means, if they can’t afford those types of devices.
David: But I think there’s a lot more power in that because there are only 32 NHL teams and 32 AHL teams and 60 something division 1 teams in hockey and besides that, most of us are going to be able to have all the toys. That’s exciting stuff man. I’m excited to read it when you’re done with it.
Adam: Talk to me in 10 years.
David: Hahah yeah I heard research can go like that sometimes. Anything else you want to mention to our audience? Any final thoughts, asks for the audience, et cetera.
Adam: I think my story is a good example that it’s not enough to think about stuff and it’s not enough to read a lot of stuff, you kinda gotta do stuff. If that makes sense. I could’ve thought about sports science, I could’ve thought about the metrics a lot and been curious about then and not done anything about them. I could’ve thought about helping my professor and all the cool things. But if I didn’t actually act on that and went and did things I don’t know where I’d be today. Taking action on your curiosities, if that’s the word of choice today, is important.
David: Here, here. Very well said, Adam. Thank you so much for coming on the podcast, we’ll have links to everything including where you can reach Adam on social media, his website, and his Excel courses and videos where also on his website so once again thanks for joining us here.
Adam: Thanks for having me. It’s been a blast.
David: We’ll have to get a drink sometime if I’m ever back in Vermont.
Adam: I’m waiting for you.
