Data, Data, Data
The popularity of data in performance continues to grow, especially with all of the technology that’s out there. We have sports technology companies tracking movement and load, we have wearables such as WHOOP telling us our daily health metrics like heart rate variability (HRV) and resting heart rate (HR), we have a bunch of ways to test all kinds of fitness metrics like VO2max, resting metabolic rate (RMR), lactate and ventilatory thresholds, and the list goes on.
Before I continue, I want to give a disclaimer: I am a huge data nerd, I have a master’s degree in the field, I got my undergrad degree in engineering because I really liked math, and I’m a certified sport scientist. I track a ton of my own stuff to include sleeping metrics, RHR, HRV, VO2max, lactate thresholds, heart rate during my running sessions, weekly load from strength training, and barbell velocity speeds. When I wake up, one of the first things I do (out of habit) is to check my WHOOP data. I also track my athletes’ data across different areas of performance such as lactate based VO2max, lactate thresholds, session and weekly training load, and force plate data. On top of all of that, I even work full-time for a sport technology company where our sensors (inertial measurement units (IMU) and local positioning sensors (LPS)) track athlete workload, volume, and performance. With that being said, data (especially objective data) is not a requirement to improve in performance and truthfully, it sometimes gets in the way.
Hopefully I have made it clear that I value data and I do not think it should be completely thrown to the side. However, I believe there’s a balance and there needs to be a level of control. Oftentimes, people become overly reliant on objective data and they forget about the most important piece of the puzzle, subjective data. Subjective data includes things like perceived effort, and fatigue. If you have all of these numbers from technology telling you what direction to take, but you are not considering your own recovery rate and your own internal cues, then you’re ignoring your own physiology.
I can ramble on for a bit on this topic, but instead of doing so, I will provide some bullet points on how data should be approached and what I recommend:
What your body tells you is the most important piece of information: In most situations, subjective measurements are more important than any other piece of information a piece of technology can tell you. Listen to your body, and if you’re working with athletes, listen to what your athletes are telling you about their fatigue and how they’re feeling. Some people are dramatic, so be weary of that too.
A good example I like to use for this is subjective measurements and force plate data. There have been multiple occasions when athletes complain about how tired they are and how their legs feel like bricks or they feel like they’re moving slow overall. Then, when I have them do a countermovement jump on the force plates, their numbers look great across the board in all time-based (for example, RSI-mod) and performance metrics (for example, peak power). If I were to base it off of just the objective data, I would assume they are neurologically primed and ready for peak performance. But, knowing that athletes are great at being master compensators, I realize that they changed their jumping strategy in order to compensate and still produce the same output that they normally do (or even better). You have to look at the full picture of things.
Data is stressful, know when to incorporate it and when to cut it out: Imagine you are going on a run and you are expected to hit prescribed paces because that’s what the data told you to do. It can make a training session seem that much more stressful. Or, imagine you have a race and you wake up that morning and your wearable tells you that your recovery score is 10%…uh oh. That’s a whole other layer of stress added to your plate. In some cases, some people can handle the data well and use it to make informed decisions. And in other cases, it can drive someone to neurotic behaviors. Know yourself and/or the athletes you are working with; do not let the data drive you crazy. Your WHOOP may tell you that your dying, but you might actually feel fine and you might actually be ready to hit a PR that day.
Not all data is reliable: Data from technologies and other measurements can be an amazing tool. Many times, it can highlight some gaps you may have in your performance. But, also be aware of how the data is collected and the technology you’re using, because they don’t all operate at the gold standard.
I’m biased, but I think KINEXON is the GOAT of load-monitoring systems :)
Understand where the data can help you: Data can help fill in some gaps and give some extremely valuable information.
For example, I’ve been using a lactate meter in my threshold interval training sessions and I’ve noticed that my body is not efficient in the glycolytic energy system. It shows a gap in my training…although it should have been pretty obvious because I do not train in that energy system often or consistently…so truthfully, I didn’t really need the data to tell me that.
Some people get a VO2max test to get information on their fitness BUT many times, you can assume your VO2max will be good or bad, above or below average, just based on your training. Most likely if you’re consistent and you’re training hard on some training days and moderate the other days, you will probably have a decent VO2max. That being said, it’s some times helpful to get a baseline and train to re-test, that way you can get a clear measurement of your improvement.
Key Takeaways:
Training is most effective when you use performance data as a reference instead of relying on it to make every decision during a workout.
Develop awareness of your own effort and fatigue. This helps you adjust your training appropriately, as needed.
The strongest approach is to combine objective data with the ability to make decisions based on how your body is responding.
