So, if you do one talk about technology and rehabilitation, then Mike Sicati and Steve Cohen immediately believe you're an expert in technology, and so then you get a chance to do a talk about wearables. And so, doing a talk on wearables is really interesting. Now that I'm in a neutral position of working with umpires, I have a chance to call every club and the people I used to work with and ask lots of questions, and they're willing to talk to me now about what they do. It's no longer proprietary, and they feel comfortable to give me a lot of information about the pros and cons of wearable technology. So, what I'd like to just go through today is just the benefits of what wearable technology can do for us, the process to determine what wearable technology you might use, talk a little bit about data collection process. Is it a evidence-based process, or is it a practice-based process? Talk a little bit about reliability and validity of the technology that we're using, and just kind of give you one little sample of what we're trying to think about doing with some umpires and how that kind of led me down a path that was a little bit different than what I expected. So, technology's great. I think it gives us a lot of opportunities to look at our athletes a whole lot differently than we used to, but when I went to put this presentation together and I looked at the National Strength and Conditioning Association's essential sports science text, I think one statement kind of stood out to me, and this is the statement that I think drove me in putting this presentation together. In some situations, the urgency for organizations to be on the cutting edge of new ideas and become early adopters of technology, as well as the momentum of technological advances that pushes them and chases them into new innovations, can place sports scientists in a difficult and challenging position. And I would take that one step farther. I think it places all of us in a really challenging position. I've been there, so I kind of have already lived this a little bit. If the organization is trying to do things and you're trying to do things, I think it places our team physicians, our athletic trainers, our physical therapists, strength and conditioning coaches, I think it places all of us. Sports science is great. I think when it's evidence-based, it certainly is very, it can be very beneficial to us, but there's a lot of information out there about technology and wearables that just isn't accurate, and I think we have to be careful of what we're using and what we say technology can and can't do. So wearables, again, a chance to put something on your athlete. They can use it in a practice, they can use it in a workout, they can use it in a game, potentially, depending on what's been approved. And they're all opportunities to look at our athletes in ways we've never been able to do before, in particular, looking at prevention or screening options, assessments, and also tracking our athletes. So I think the opportunities are great with wearable technology, we just have to kind of look at it a little closer and make sure we're doing the right things. So how about the process? Of course, if you're from Philadelphia, you have to talk about the process because that's what we do, and by the way, that still hasn't worked out, for those of you that don't know. But our strength coaches, this is the one chance for everybody on board and everybody to have a collaborative effort, so it has to be strength coaches, it has to be your organization, it has to be your team physicians, everybody has to buy into the same idea of what you want to do. And so how do we get to that process? Well, the scientific method, everybody's been through this before at some point in time, you find the problem as a group that what you want to solve. This collaborative team ever comes up with an idea, you create a hypothesis, and then the big step, of course, is deciding what part of technology do you want to use to solve this problem? And does that technology ultimately give you the answer you want to know? Because if you don't choose the right technology at the end of the day, you really will not have solved the problem. So what's the difference between evidence-based and practice-based? Well, evidence-based is great, right? We set up a research study, it's very controlled, everybody's on board, there's a whole lot of things that are going on, and we know at the end of the day we're going to get the answer, and we're hoping that whatever hypothesis we created, we solve. Whereas practice-based data gathering is a little bit different, right? We're going to take a wearable technology, we're going to put a player in a batting cage, we're going to put a player on a mound, we're going to put them in a workout, and we're going to gather data and then retrospectively go back and look at that data and determine whether it gave us any information. And I think both of these concepts have the ability to do very well for us. I think the only concern I have is when the practice-based outweighs the evidence-based, and I think sometimes we have to, again, be careful of what we're getting from the technology. So how about the quality of the data being collected? Well, Aura, and I'm not here to promote one product or another, obviously, but Aura puts out this, that they're the only vetted ring-shaped tracker on the market. And that might be very true. I don't know who the experts are that vetted that product, but certainly it'd be something that we would want to look at. And there's a lot of data that we've been collecting for years. We've been collecting heart rate data, we've been collecting heart rate variability data, we've done GPS data for several years, and all those things are pretty well-researched. Understand that the variability from the gold standard of whatever you're doing may be a little bit different, and from vendor to vendor, there may be differences in the actual data that you're collecting. And so the one recurring theme I got from most everybody I talked to at both the professional and college setting was that they wanted the ability to actually collect the raw data and be able to analyze it themselves. And that's something that I had never really talked about when I was having my experiences with technology in my previous life with the Phillies. So again, this comes down to understanding the difference between having reliable and valid data that we can get from these things. When vendors come out and start to tell you that they have proprietary ways of doing things, that sends a red flag up for almost every person I talked to in both the professional and college scene. So again, I think the raw data collection is something that needs to be considered if you're thinking about using some type of wearable, and you need to use, you need to reach out to all kinds of institutions to help you with that. I think, again, the one thing I thought that people were doing most effective, or the clubs that were doing the most effective work, were not hesitant to reach out to outside sources like universities and other colleges to have help from people that are doing this on a regular basis. Utilizing data from sport to sport, not always optimal. There's a ton of GPS data out there in soccer, which is really great, but when you try to apply that to baseball, especially on acute to chronic workload ratios, it doesn't really always apply. It's a totally different sport, certainly different aerobic capacities for these athletes, certainly baseball players can tend to be a little chubbier than soccer players. And we've tried this in the past with some very simplistic things, like 60-yard dash for baseball players, which is not always ideal, because at 90 feet, we tend to take left turns, and when we take left turns, that's when hamstring injuries typically occur, or other injuries. And the same for the FMS screen. Long ago, we put the FMS screen in the NFL Combine, we came up with numbers and said that, well, if you were a 14, it was somewhat predictive of injury, we tried to carry that over to the other sports, and I think at the end of the day, we found that functional movement screening was good, but it was only good at what it was supposed to be doing, which was to document asymmetries in the athletes and things that we needed to work on and address from a corrective exercise standpoint. So how about the challenges of wearables? Well, certainly, the ability for the product to actually stay on and work and give you the data at the end of the day is important. It shouldn't put any athlete at risk when you're using it, and unfortunately, you actually have to worry about the union, so from a professional baseball standpoint, the players' union has to agree that they're allowing you to use this technology when you go to play soccer. And oddly enough, in my new job, you can believe that the umpires actually have a union also, and anything that I go to do has to be approved by them. So how about just a simple example of something that we were talking about trying to do as an organization being Major League Baseball for the umpires? One was just collecting heart rate data. We have no idea what the heart rate of an umpire is during a game, and so there are many reasons we would wanna know that. One would be exercise prescription for sure, but the other would be return-to-work decisions. So umpires, in case you don't notice, and now that I tell you, you might start to notice even more, they get hit in the mask quite a bit throughout the season, and they have quite a history of concussions. So if you're doing a return-to-work plan for an umpire off a concussion, you certainly should know what their heart rate gets to when you're making an exertional program. But we wanted to take it one step farther, right? We wanna know, what's the recovery of an umpire? If you look at the umpire's travel schedule, they're never home, there's no home game for the umpire, so they're always on the road. So we wanna know a little bit about the recovery of the umpire. And so why would we wanna know that? Well, one, ZE scores. For those in the room that don't know what a ZE score, that little box you see on your screen every night and you argue that the pitch was out of the box and it wasn't a strike even though it was called a strike, they actually do get graded every night on those. And so we'd like to know, is there a correlation between recovery and how well an umpire actually scores? And then take it one step farther, we'd like to know, does their recovery have any predictive value of how susceptible they might be to a concussion? So the rotation of umpires has always been they go from home to third, to second, to first, and there is some debate in my own mind and others that maybe that's the wrong way to go because of the stresses of being an umpire and there's different positions. So, that said, I thought, well, you know, how hard could it be just to take something and get heart rate variability? I had the pleasure of talking to Dr. Kyle Ebersol from the University of Wisconsin in Milwaukee. And so he presented me with this slide that if you're taking heart rate variability strictly just from a device, you might not be getting what you want because you didn't account for position, breathing, time of day, sample length, environment, and all kinds of other things about heart rate variability that I had no idea even existed, but as an exercise physiologist, certainly he did. Again, these simple things that we think we're collecting on heart rate variability and recovery may not be giving us what they want if they're not collected in the right manner. This is a guy who actually took it and looked at the data from some of the devices and compared that to a 12 lead EKG just so he could figure out whether it was accurate or not. This is some pretty good stuff. He actually did a research project with the Milwaukee Brewers on a five day rotation, probably about four or five years ago, so really interesting stuff. Again, as we continue to get pursued by 50 plus companies every year as Major League Baseball in the pursuit of collecting data and finding out information on our players, I think we just have to be careful. We have to understand the processes to go through to look at that data. We should be thinking about collecting raw data from these companies, and we have to be at least aware that everything we're being told we're getting may not be true. A lot of people helped me put this presentation together. A lot of people a lot smarter than I. Gave me a lot of great information, and the resources I have here certainly are beneficial for me. A lot of people I talked to didn't want to be identified, which I certainly understand, and I thank you for your time.

wearable technology

sports science

evidence-based practices

collaboration

data interpretation