Monitoring and Analytics Part 2: Front-End Monitoring

Monitoring. Analytics. In the age of big data, these are becoming important buzzwords in sports. Using technology to physiologically monitor what's going on inside an athlete's body—during competition, during practice, or before they even show up for a training session—can give coaches important insights into how to better prepare athletes for optimal performance. The data gathered can result in better recovery strategies, more effective training methods, and healthier, less-frequently injured athletes.

If you haven’t read Part 1, start there: in addition to unpacking the 3 main reasons why physiological monitoring is important, I give some low-cost solutions for implementing a monitoring program on a budget.

In Part 2, I’d like to go a little more in-depth with some of the methodologies we currently use at the University of Massachusetts Lowell with our ice hockey team, to at least give an idea of what is possible if you are fortunate enough to have the resources to embark on a more sophisticated monitoring program. 

First, we need to understand the idea that “stress is stress.” It doesn’t matter if it’s good stress, bad stress, physical stress, mental stress, or emotional stress—all stress is interpreted by the brain in the same way. So one of the primary questions that drives our monitoring program is, “How much stress are our players under?” 

To attempt to answer that question, we break our monitoring program into 2 parts. 

Part 1: Readiness (Front-End Monitoring)

The first part is our “Readiness” program. This is where we try to get a handle on the physiological state of our athletes prior to a training or practice session. We want to know what they are prepared to do, and what the “cost of doing business” will be. You see, training is really all about applying stress to achieve some kind of desired adaptation. The brain doesn’t really know that an athlete who is bench pressing is doing that as an exercise—it simply thinks there is something really heavy about to crush it, and it had better get it out of the way and adapt to that stress so next time it happens, it can survive that threat or an even greater threat (something heavier).

The same is true of skating during practice or a game. The brain doesn’t really know you are playing hockey, it just thinks you are trying to get away from some predator, and it better adapt by making the body faster and/or better conditioned so that next time that tiger jumps out from behind a tree, you can get away from it. 

So, as you can see, a good strength and conditioning program is really all about manipulating the stress applied to the body to achieve a specific and desired adaptation. That is why random, “more-is-better” workouts aren’t great for long-term athletic development—they do not target a specific adaptation. And this is why we start our monitoring with our Readiness program, so that we know just how much stress we can apply to our athletes each session so that they adapt the way we need them to, without over- or under-working them. 


To find out how “ready” our hockey athletes are, we use two different tools. The first is a basic questionnaire, like the one I outlined in my previous article. At UMass Lowell, we have a wellness questionnaire on an app that the players log into each morning. Here they report how much sleep they got last night, their level of fatigue and soreness, their mood, and a few other basic questions. This information is digitally passed along to me in real time, so I start to get a sense of where our players are at from a recovery standpoint, first thing in the morning. This information can be very powerful, especially when you are able to compare how a player is reporting relative to other factors, such as their typical score, their typical scores for that particular day, the training load from previous sessions, and other factors that go into the balance of fatigue and recovery. 


The second tool we use in our Readiness program is HRV. HRV stands for Heart Rate Variability, and it is essentially a measurement of the time between beats of your heart. More accurately, it’s the measurement of time between the R-R wave of your sinus rhythm (the boom/boom of your heart beat). This time frame will change (albeit by extremely small increments) depending on whether your Autonomic Nervous System is more sympathetic, parasympathetic, or a balance of both.

While there is no “good or bad” with the HRV score, the information can tell you a lot about how the athlete is adapting to the stress of training, practicing, and competing. Looking at the athlete’s HRV score in relation to their Questionnaire score—in addition to variables like training loads, where they are in a particular periodization scheme, and external factors such as school workload—can all provide a window to better understand where the athlete is when he or she walks in the door.

We gather all of the Readiness information on the front-end, so we can analyze and utilize that information before we do anything with our athletes. It not only helps drive some day-to-day decisions about our players (if someone is unusually low in HRV and their Questionnaire, we may alter their training or practice plan), but it also helps us lay out our longer-term schedule to maximize athlete readiness when it really counts: game day. We can look at the trends from this information and compare them to our training loads from each day and week, and get a good idea of how to structure our practice week so that our players are as recovered as possible going into the weekend. 


One important note about the Readiness information: just because a player receives a “low” score does not mean he can’t compete or train. In fact, it doesn’t even mean he can’t have a good day. I have seen players have the best games of their life, or hit new PRs in the weight room when their Questionnaire and HRV are in the tank. What the Readiness information tells us, however, is the “cost of doing business.” 

When one of my hockey athletes walks into the weight room with poor recovery scores, he may be able to accomplish what is put in front of him, but it will cost him more in recovery after the fact. An athlete who can usually play equally well in back-to-back games may be much more fatigued after the first night, and therefore have less in the tank the second night if they came into game 1 with poor Readiness scores.

This emphasizes the importance of the “Art vs. Science” relationship in my first article. The data analysis (analyzing an athlete’s Questionnaire and HRV scores) is the “science” portion, but it is important for coaches to also use the “art” of decision making. Just because the data suggests one thing doesn’t mean that doing the opposite isn’t warranted in a particular situation. In other words, we might still play an athlete with low Readiness scores, but we will now have a better understanding of what he is capable of the second night.

Stay tuned for Part 3 of my series on Monitoring and Analytics, where I will discuss our methods of "back-end" analysis (looking how much physiological stress an athlete actually accumulated during training, practice, or competition) and how it relates to how we as coaches adapt our program and methods to meet the needs of our athletes on a given day.

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Devan McConnell is a Volt Athletics Advisory Board member. He is the Head Sports Performance Coach at UMass Lowell, working primarily with the Division I hockey team. Learn more about Devan and his innovative Sports Performance department here.