Freelap Friday Five with Dr. Matt Jordan
Dr. Matt Jordan is a strength and conditioning coach/performance consultant for elite athletes with six Olympic cycles of experience. He holds a Master of Science in Exercise and Neuromuscular Physiology, and a PhD in Medical Science from the University of Calgary. Matt has consulted with more than 30 Olympic and World Championship medalists and provides expertise to high performance organizations in the NHL, NBA, NFL, and military. He is currently the Director of Sport Science (Strength & Power/Mountain Sports) at the Canadian Sport Institute Calgary (CSIC) and leads the Sport Science/Sport Medicine program for Alpine Canada. Matt provides science-based education courses for strength, fitness, and performance coaches of all levels through his website.
Freelap USA: Periodization (defined as planned, sequential overload with phases complementary to the next), in general, has taken significant criticism in the last decade. What are some positives and negatives to this model, and where do you see it heading?
Matt Jordan: Yes, for sure, it seems like the concept of “periodization theory” has taken a bit of a beating recently. I have to say, I have also thought critically about periodization over my career.
I remember my first introduction to periodization theory in my undergraduate degree, reading textbooks authored by former Eastern European sport scientists. I recall all sorts of reaction curves or performance responses to various sequences of training loads, and the planned/purposeful manipulation of volume, intensity, and density of the training stimulus to optimize performance. I learned about the various organizational structures of training load and training cycles, and the concept that training should progress from general means through to more specific means leading into a competition phase.
Underpinning this notion was that the planned manipulation of training load resulted in the attainment of a peak level of performance at a desired and specified time point in the future. As a young coach, all of this made sense to me. There was just one problem—where was the data to support these claims? I say this because most of the figures looked like hand-drawn sketches rather than being empirically based.
I also ran into a paper titled “The End of Periodization” by Yuri Verkhoshansky in New Studies in Athletics that was passed on to me by one of my great mentors, Dan Pfaff. I read this paper with great interest. Dr. Verkhoshansky raised several criticisms of traditional periodization theory. Namely that:
- It didn’t account for the dense competition schedule of the modern-day athlete and the requirement for them to be consistently on-form.
- It was not rooted in biology and instead was based more on a logical approach to organizing training load.
- It did not account for new advances in the scientific literature.
- It was not founded in science and was conceptually based.
As I moved from undergraduate studies into my master’s, I started to develop a bigger interest in the data that underpins the claims made in our profession. I’m not trying to be dismissive. Rather, I was looking to maintain a healthy skepticism.
Dismissiveness implies a negative feeling or scorn for an idea. There is far too much dismissiveness in our profession. Skepticism just means that more data is needed to accept the claim or proposition. Contrary to dismissiveness, I think there is too little skepticism in our profession.There is too much dismissiveness and too little skepticism in our profession, says @JordanStrength. Click To Tweet
I remember another conversation in graduate school with a professor who was also an avid triathlete. I was taking a course from him on muscle physiology and periodization came up in a conversation. He said: “Matt, you realize there is no scientific evidence supporting periodization theory. First, most studies are of short duration with relatively small sample sizes. Second, cells see signals and these signals are converted into cellular processes that lead to a tissue-level adaptation. The training stimulus is the signal for the cell. It is fundamentally unnecessary for the stimulus to follow some preplanned manipulation of volume, intensity, and density in order to activate cellular processes. The key is that the stimulus is progressed as adaptation occurs.” He concluded by saying: “Periodization is a concept. It is not based in science.”
I am fully aware that not everything that counts can be measured, and not everything that can be measured counts. But, at some level, we must seek data to support personal opinions and anecdotes. The science always has to come up behind the coaching.
As I reread these periodization textbooks, I was often left with questions like: How was training load quantified? How many athletes did they include in the analysis? How did they measure performance? And, why the hell doesn’t the data I collect on my athletes look like this?! My curves were never that pretty or consistent over time or between individuals.
I also found that despite seeing many well-designed (and very elaborate) periodized yearly training plans (YTP) with all sorts of color coding and time-trend graphs, very few coaches had any sort of retrospective approach for determining whether or not the plan was executed properly, and if so, whether it worked.
If we are to validate the concept of periodization theory in the real world, or on any pragmatic/operational basis, it seems necessary to have five things in the workflow:
- The initial hunch on which the periodization scheme is based;
- A process for designing the training plan;
- Execution of the training plan with some form of athlete monitoring;
- Verification that what was planned and executed were the same; and
- Achievement of the prediction (i.e., achieving optimal performance when it counted).
Instead, I found that these periodized training plans were more often than not just conceptual arrangements of the training stimuli at the front end of the training process without any objective and verifiable evidence about the efficacy of the plan and the predictions that were made at the back end.
Don’t get me wrong: I see huge value in planning at the front end. This is especially important in sports with logistical challenges like multiple competitions, lots of travel, and the need to integrate many components for optimal preparation such as injury prevention strategies, mental performance, environmental training exposures, strength training, and tactical skills development.
However, the basic tenet of periodization theory is that the planned manipulation of training variables (volume, intensity, density, type) is more effective for eliciting optimal performance at a known point in the future compared to some alternative arrangement. It ties in principles like general adaptation syndrome and concepts from other scientific disciplines to explain physical performance phenomena we observe in the sporting world. (As an aside, I actually don’t see anything fundamentally wrong with leveraging paradigms in other disciplines to better understand our own, although we need to be aware that we are doing this.)
We also need to understand that when we discuss periodization theory, we are entering a scientific domain. Scientific theories are meant to explain phenomena and to make accurate predictions. When theories are no longer able to explain phenomena or to accurately predict events, they may be replaced in part or in whole by another competing theory. This is called a “scientific revolution” and there has been much written on this topic in by philosophers (see Thomas Kuhn).
In a scientific revolution, there is something called the burden of proof. The burden of proof rests on the shoulders of those challenging an accepted theory to provide a different theory that explains the new anomalous events in question while still explaining everything that the previous theory could.
In my experience, periodization theory and the process of periodizing training have always seemed to parallel a mini scientific experiment. So, let’s call periodization a mini scientific experiment in which the manipulation of training variables is meant to elicit an optimal performance at a known time point in the future (this is our prediction).
In order for periodization to have any value, I think each unique training situation has to be seen as a mini experiment. Our dependent variable is performance, our independent variables are the training parameters, and our prediction is that we will achieve some desired performance outcome at a specified time point in the future. This is the only way for us to answer the question: Is periodization theory a useful or dated practice?
I would like to frame the potential practical or intuitive relevance of periodization. I will do this by proposing two somewhat trivial scenarios. The objective in both scenarios is to compete in a weightlifting competition. In both scenarios, we will ensure the application of equal training load. In this case, our variables are: session count, volume, and intensity. The only difference is that in Scenario A, the training load is dispersed over six weeks, and in Scenario B it is dispersed over 10 weeks.
If periodization was irrelevant (i.e., the planned manipulation of volume, intensity, or density) both scenarios should lead to a similar outcome. It would boil down to the number of times the cells saw the signal (permitting sufficient recovery, of course) and to the psychological readiness of the athlete (another reason why periodization might work in our favor).
Now, let’s factor in that the athlete in Scenario A is returning from a lower back injury and has three years of high-level training experience under his belt. The athlete in Scenario B, on the other hand, is healthy and has 10 years of training experience. Clearly, as we begin to add context and situational differences, the performance predictions that we make based on the manipulation of the independent variables might be different. It may be the case that we would expect Scenario A to lead to a poorer performance outcome, but on the other hand, maybe not.
Remember, these are just predictions and predictions should be tested and verified. This is the intriguing, forever interesting, and captivating aspect of coaching and human performance. We are dealing with unique scenarios that require our experience and expertise. Predictions are made, training plans are developed and executed, and our hypotheses are ultimately put to the test. I think this is where periodization differs from planning.
So, where does that leave us? Should we plan and periodize the training program or should we just randomly assign the training stimulus?
First, I absolutely feel it is necessary to plan. Planning is important for a variety of reasons, including: it often brings stakeholders together in planning sessions; it allows us to account for many aspects of the training program (a few listed above); and it forces us to think critically about what we are doing.
Second, I believe that there are optimal and sub-optimal arrangements of the training stimulus in terms of the timing, sequencing, volume, intensity, and density. I also believe that for periodization theory to have relevance, we have to continually put our performance hypotheses and predictions to the test with some level of objective and verifiable evidence. Periodization is a mini science experiment. We believe if we do x, y will occur at a specific time point. This is both the best way to approach training (in my opinion) and the most fun, as we will be forever challenging ourselves, our beliefs, and our training constructs.
I may be criticized for this next forecast about where we end up with periodization, but my opinion is that someone or some sport system is going to blend the critically important aspects of a coach’s instinct with the objectivity and ever-increasing presence of data.
As with most professions and disciplines, we are entering an era where a tuned-in practitioner who can embrace the ever-increasing presence of data and data science while still nurturing their instincts will be the one who ultimately forges an entirely new path. Who knows? Maybe someone will introduce a new theory for how we organize training that does everything that periodization theory does and then some. Whereas the ability to track performance variables in most sports was next to impossible 60 years ago when periodization theory was first conceptualized, we are now in an era with wearables and a big data approach to quantify performance and discover new patterns/relationships.
Let’s keep asking questions about periodization theory, thinking critically, challenging our own and each other’s beliefs (in a healthy, skeptical sort of way), and always strive to bring the science up behind the coaching.
The positives about planning for the coach are:
- It forces us to think critically about our training plans.
- It promotes collaboration.
- It enables us to integrate multiple components of the sport performance process.
Periodization differs from planning, as we are making a prediction about performance. This opens a door for us to test our predictions and to further our understanding of the training process.I think periodization will meld into a real-world science that allows us to study training response, says @JordanStrength. Click To Tweet
The negatives of periodization for the coach are:
- It remains more of a concept and less of a verifiable experimental process.
- The profession is in its infancy, so there are lots of unexplained phenomena that fly in the face of the basic tenets that underpin periodization theory.
The future for the coach is one that blends science and practice. With the progression in athlete monitoring, data science, and the profession’s knowledge base, I believe we will see periodization meld into a real-world science that allows us to study the training response in a verifiable and objective manner.
Freelap USA: What’s your specific take on jump profiling as it can fit into the weekly and monthly training organization and adjustment models?
Matt Jordan: I have spent the majority of my career finding a place for assessing strength abilities. I used to call them “strength qualities,” but I prefer the term “strength abilities,” as an ability can be quantified. I had a low to moderate level of success doing this early in my career.
The main factor that limited my success was the accuracy and precision of my assessments. Imagine a dartboard where the goal is to hit the bullseye with five darts. Accuracy refers to how close we are to the bullseye, whereas precision is how close the darts are to one another.
Your dart throwing could be precisely right (darts hit the bullseye and are close to each other), precisely wrong (darts are way off the bullseye and are close to each other), or generally right (darts strike around the bullseye but aren’t very close to each other). You could also be generally wrong, which basically means hitting everything in and around the general vicinity of the dartboard. To assess change in most performance factors, we need a decent level of accuracy (we measure what we want) and precision (our measurements are repeatable) in order to succeed.
All this changed when I took a trip to the International Conference on Strength Training in Colorado Springs (an excellent conference that will be in Perth, Australia in December 2018). I met Bill Sands, who introduced me to an affordable force plate system. I also saw a fantastic presentation by Dr. Per Aagaard, who dove deeply into the vertical jump not as a simple skill performed in sport, but as a movement that provided much deeper insight into the mechanical muscle function of an athlete. Here, it seemed possible to characterize neuromuscular readiness, neuromuscular fatigue, neuromuscular function after injury (and with aging), and performance reactions to a training stimulus.
I returned to the Olympic training center in Calgary (The Canadian Sport Institute Calgary) and realized we needed to pursue the acquisition of our very first force plate system because our jump mats, linear position transducers, and accelerometers where just not providing the accuracy/precision that we needed.
We purchased two force plates, as a single force plate was too small on its own to test our athletes. As time went on, we further refined our data analysis techniques, moving away from hand-bombing jump files to automated analysis with custom-built computer scripts.
As our capabilities evolved, our workflows, accuracy, and precision improved. However, all we had were numbers. We did not have very many relevant questions or hunches that we could test. One thing I did have with the dual force plate setup was a qualitative assessment of left versus right vertical ground reaction force asymmetry in squatting and jumping. This realization was one of my first real wins for using monitoring to improve my coaching ability.
I started to find that routine kinetic (force) asymmetry testing with my rehabbing athletes was informing me about the predictions I was making with the training programs I prescribed. My hunch was that my program would improve an athlete’s ability to generate force through the injured limb, and now I could test this hunch. I started to experiment. All of a sudden, I realized the key to integrating any assessment or monitoring strategy was having relevant questions and anchors. Anchors are important variables like injury status, training status, performance level, and phase in a training cycle. These are the variables that bring context and meaning to our data tables filled with performance metrics.The key to integrating any assessment/monitoring strategy is having relevant questions and anchors, says @JordanStrength. Click To Tweet
Jump monitoring eventually started helping me quantify an athlete’s reaction to a training program and test my predictions. I took the perspective that in addition to the skill of jumping, the related movement strategy and performance variables might provide deeper insight into the mechanical muscle function of my athletes. On a simplistic level, I applied a training stimulus and expected a temporary loss in performance or a change in jump strategy.
These occurrences are likely, due in part to neuromuscular fatigue, but fatigue is a complex state. Rather than use the term “fatigue,” a more appropriate term may be “performance fatigability”(Roger Enoka, 2018, personal communication). We understand performance fatigability as the effects of fatigue on performance or, in this case, the ensuing changes in various jump performance/movement strategy related parameters.
Following a decrement in performance, I expected an adaptation leading to an overall performance improvement. This is the basic response that characterizes the reaction to a training stimulus. My challenge was capturing this response—it seemed exceedingly difficult in most high-performance sport settings because performance in a given sport was either too variable or contained too much complexity for performance to be quantified with sufficient accuracy and precision.
As performance in most sports is really tough to quantify, it seemed I might benefit from having a surrogate measure; namely, a repeatable and standardized performance test that could be performed on an ongoing basis to help me characterize an athlete’s reaction to the training stimulus. Additionally, the test should also be pragmatic. If it isn’t pragmatic, it just won’t fit into the world of most high-performance sport settings.
This is where vertical jump monitoring fits, in my opinion. Assessing vertical jump performance and vertical jump strategy with the right equipment provides a standardized and repeatable performance test that fits well in a high-performance sport environment, allows us to assess an athlete’s reaction to the training stimulus, and may inform us about the athlete’s underlying mechanical muscle function.
Additionally, with a dual force plate system, we can measure the right vs. left force asymmetry in movements such as the reversal of the downward acceleration of the body center of mass (aka the breaking phase or the eccentric deceleration phase) and in the acceleration of the body center of mass (aka the propulsion phase or the concentric phase). These movement phases are important for many reasons, both in terms of training for injury reduction and performance.
Also, kinetic (force) asymmetries may help guide our processes around monitoring athletes throughout return to sport after injury and might help identify non-injured athletes who have trainable deficits. More scientific inquiry is required to support these propositions.
To summarize, many scientific studies on athlete monitoring list the variants of the vertical jump as potential movements that can help us monitor neuromuscular performance fatigability and an athlete’s reaction to a training stimulus. Additionally, there are many studies that link left vs. right asymmetries in movements like the vertical jump to non-contact lower limb injury and return to sport monitoring. From my perspective, weekly jump profiling allows me to test some predictions (not all) around aspects of my training program with a repeatable and standardized test. By evaluating jump performance and jump strategy variables, we may be able to detect relevant neuromuscular adaptations that transcend the skill of jumping and reflect the basic function of the neuromuscular system.
Serial monitoring of this standardized and repeatable performance test helps me address the following questions:
- Based on my training plan, I expect my athlete to be fatigued. Is he/she fatigued?
- Based on my training plan, I expect by athlete to be recovered. Is he/she recovered?
- What is my athlete’s typical reaction to a given training stimulus?
- Given that there are neuromuscular deficits undetectable to the human eye, does my athlete display potentially trainable deficits as assessed with interlimb force asymmetry testing?
While there is no single test that can provide all the answers, weekly vertical jump testing has been valuable for me. We perform three to five countermovement jumps on a weekly basis (typically after a rest day) and sometimes we perform them before the rest day and at the end of the microcycle to further characterize an athlete’s reaction curve.
Freelap USA: What’s your take on functional asymmetry in athletes, for those who are healthy, as well as those who are injured and looking to reach a benchmark in an injured limb?
Matt Jordan: I have spent a great deal of time in the past 10 years diving into functional asymmetries. As discussed above, this did not happen in some sort of preplanned way. We obtained a dual force plate system because the Pasco plates we purchased were the only ones we could afford, and they were too small to assess an athlete jumping. Therefore, we needed two plates. I had no preset plan to evaluate interlimb asymmetries.
I arrived at this application quite organically by realizing that there were interlimb asymmetries that I could not detect with my eyes, that asymmetries tended to decline with the right type of rehabilitation but not according to some preset timeline, and that best practice calls for all practitioners to evaluate neuromuscular function in athletes returning from injury to ensure they are sufficiently prepared for full unrestricted training and competition. I also felt that while sports medicine professionals had their own standards for evaluating athletes after injury, most of the metrics available for strength coaches didn’t really get at the persistent neuromuscular deficits we often observe after injury.
Dual force plate systems allow us to simultaneously measure the vertical ground reaction force from the right and left limbs during movements like jumping. We calculate a functional asymmetry index by measuring the impulse from the right and left limb separately over specific jump phases. Taking a phase-specific approach is important, as it helps characterize the entire jumping movement versus a single time point. (For example, the instant of the peak vertical ground reaction force—this variable is essentially meaningless in jumping.)Force asymmetry testing is one of the single most important #neuromuscular metrics we collect, says @JordanStrength. Click To Tweet
We use the impulse asymmetry index to identify athletes who might have diminished lower body structural tolerance. We perform at least five and sometimes 20 movement cycles so that we can assess not only the magnitude of the asymmetry, but also the interlimb loading variation. This might mean that an athlete either displays a more rigid limb loading strategy (i.e., reduced interlimb loading variability) or they have one limb that systematically produces less impulse than the other limb. Our preliminary data indicates that an asymmetry index above 15-20% in the eccentric deceleration phase of a countermovement jump is predictive of lower body injury in elite athletes. As such, we flag athletes that have big changes in asymmetry, or get into this red zone, and adjust training appropriately—or triage to the appropriate person on our medical team.
Assessing functional asymmetry in this manner is also useful for monitoring an athlete throughout the return to sport transition after injury. This allows us to quantify the effects of the rehabilitation strategies and to generate better conversations around return to sport decision-making, as we are incorporating objectively determined metrics. For example, regardless of how much time has elapsed since surgery and how confident we all may feel, a 30% left versus right impulse asymmetry is what it is.
I’ve found this type of monitoring to be particularly important and informative for a performance team. With athletes returning to sport, rarely are we saying yes or no to a given activity. Instead, we look at all the factors, such as the time of the year, season (e.g., is it an Olympic year?), confidence, fitness, movement competency, and neuromuscular testing data to support the best recommendation. We might find an athlete who has a compensation pattern or neuromuscular asymmetry that presents with fatigue—therefore, we might make a recommendation to limit the duration of the return to sport activity. Essentially, this testing is here to support decision-making, not to override anyone.
It seems the velocity end of the force-velocity spectrum is affected to a greater degree after injury than the force end. As such, we often observe <5% asymmetry in maximal isometric force in a leg extension movement alongside >20% asymmetry in the late phase of the squat jump when the athlete is moving at a higher velocity.
There are no hard and fast rules for clearing an athlete for return to sport, but a safe and reasonable objective is to measure interlimb asymmetries in high rate of force development activities like jumping of less than 15% with a goal of getting them down below 10%. A good goal for slower/higher force movements like isometric maximum voluntary contractions is to see asymmetries below 5-10%. It is also important to compare the overall force/power generating capabilities to the pre-injury level, as very often both limbs will have lost strength/power—meaning that asymmetries can be low due to a deficit in the non-injured limb.
Functional asymmetries are always present. It is impossible to be perfectly symmetrical in any one movement. So, we aren’t looking to determine whether there might be an asymmetry in a one-off movement. Instead, we are aiming to determine whether, over multiple movement cycles, a systematic asymmetry pattern exists.
Human movement is characterized by an optimal level of variability and the same is true for interlimb force asymmetries. Variability is a significant part of the natural world and can often be an indicator for health or peak physiological function. For example, it has been shown that elite pistol shooters display considerably better endpoint stability (i.e., gun control) than novices; however, the elite shooters display considerably more variability in muscle activation compared to the novices. It has also been shown that individuals with patellofemoral pain syndrome and lower back pain exhibit considerably less variability in muscle activation compared to their healthy counterparts.Variability can often be an indicator for health or peak physiological function, says @JordanStrength. Click To Tweet
We recently published a study in Medicine and Science in Sports and Exercise showing force asymmetry and thigh muscle activity data from elite alpine ski racers with/without ACL reconstruction. The ACL-reconstructed skiers did not display the interlimb loading variability patterns that we found in the non-injured group. While the non-injured skiers showed no systematic interlimb loading preference over three different phases of the squat jump, the ACL-reconstructed group displayed a pattern. This was reflected by ACL-reconstructed limb loading in the early phase of the squat jump, non-injured limb loading in the late phase of the squat jump, and ACL-reconstructed limb loading in the landing phase of the squat jump (averaged over 20 movement cycles).
In summary, force asymmetry testing is one of the single most important neuromuscular metrics we collect. We assess this in injured and non-injured athletes alike as a part of our routine athlete monitoring system. We flag asymmetries above 20%, but we aren’t just looking at the magnitude of the asymmetry. As human movement is characterized by an optimal level of variability, we also consider the loading patterns over multiple movement cycles with a special focus on the interlimb loading variation.
Freelap USA: What are some ways of looking at eccentric strength development for athletic deceleration, as well as sport movement in general?
Matt Jordan: I’m going to keep this one short. The best evidence shows that there are key differences between the neural control of eccentric and concentric muscle actions. In high-force situations, it appears the average human is unable to tap into their full strength potential. This has been called the “strength deficit,” and reflects the relationship between the force-producing potential of the muscle tissue and our neurological ability to access muscle tissue.
The strength deficit is quite apparent during forceful eccentric muscle actions where inhibitory factors at the spinal level and some factors mediated in the brain limit the ascending drive to the working muscle. We can assess these inhibitory pathways using various nerve stimulation techniques while recording force and muscle activity using surface electromyography. Per Aagaard published a recent paper on this topic that is available through an open access journal.
Additionally, there are many features inherent to skeletal muscle that make eccentric muscle actions different from concentric muscle actions. The differences have long been a problem of interest for scientists studying skeletal muscle. Many of these differences arise from passive elements at the level of the myofibril. One possible contributor to the passive force enhancement seen during lengthening contractions is the muscle protein titin. Walter Herzog also has a recent paper on this topic available through the same open access journal.
I think there are two questions at hand:
- How do we train eccentric abilities?
- How do we develop braking or deceleration skills?
The scientific research suggests that higher force eccentric training is required to elicit neural adaptations at the level of the spinal cord leading to the development of eccentric abilities, whereas higher velocity eccentric training is less effective. On a practical level, I have found that it may not be necessary for athletes to work with supramaximal loads to achieve this adaptation.
I typically start with slow eccentric strength training. A typical tempo might be six to eight seconds for the eccentric phase followed by a one-second concentric phase. I would perform this type of tempo with a four to six repetition bracket. I then move to a 4+4 or 3+4 program, where the athlete performs the first three to four repetitions on a four-second eccentric/1 second concentric tempo, followed by the remaining eccentrically performed repetitions on a tempo of six to eight seconds.
The final step is to use a device like weight releasers to overload the eccentric phase with loads approaching or greater than the 1 repetition maximum, but I would reserve this only for well-trained athletes.
A big issue in the industry right now is that in our quest for something new and something better, strength coaches may tend to overlook an athlete’s structural tolerance and general movement competencies when prescribing eccentric training methods geared towards neural adaptations. The bottom line is that if the athlete does not possess the postural control, postural strength, or technical competency for the movement in question, loading them up eccentrically will only serve towards unproductive outcomes.
Finally, when it comes to the skill of braking or decelerating, high-velocity loading is required. This can be done in the weight room, where we unload the athlete (they lift less than body mass) up to external loads equivalent to approximately 50-60% of body mass. These higher velocity braking movements are done in both unilateral and bilateral conditions.I include change of direction and braking type movements as a part of neuromuscular warm-ups daily, says @JordanStrength. Click To Tweet
I will always choose to add external load up to 50-60% of body mass or have the athlete drop off a box—I rarely, if ever, have combined an external load and a drop off a box together although I know this is a common practice. I also incorporate change of direction and braking type movements as a part of the neuromuscular warm-up on a daily basis to address technical, positional, and postural requirements related to sport skills.
Freelap USA: What is a commonsense approach to performance monitoring and tracking given the vast amount of data that can be derived from modern analysis?
Matt Jordan: I’m going to keep the answer to this one really short:
- Generate questions that matter. Simple questions are typically around the type of training prescribed and keeping athletes on the field of play longer (staying injury free and coming back safely after injury).
- Find anchors like injury statistics and validated performance indicators to make sense of the data you collect. Otherwise, they are just numbers floating in space.
- Record the simple things consistently rather than trying to get complicated with monitoring frameworks that just aren’t sustainable. Important things to monitor are: athlete readiness, training load, performance fatigability, and a marker of structural tolerance. (I use interlimb asymmetries in jumping.)
- Give feedback to your athletes regularly and translate knowledge—this should be done in person and in a very constructive way. At the end of the day, in most situations, this data actually belongs to the athlete (similar to medical information). We need to bring the athlete into the process to educate and create buy-in. What’s the point of all this data if it doesn’t change behaviors and make the athletes better?
- Learn the basics of statistical analysis, data manipulation, and how to visualize data. Very often, I drop into professional organizations that have heaps of data but are unable to work with big data tables and numbers effectively, so the retrospective analysis component (the fun part) is not done well. I use a free statistical software program called R. It’s downloadable on any operating system.
You can learn to generate your own reports so that you don’t have to rely on third-party solutions, although the learning curve with R is shallow. (For those who are confused, we often say a “steep” learning curve but a “steep” curve would be one where learning occurs rapidly. A “shallow” learning curve is one where learning occurs slowly at first.)
- Garbage data in = garbage answers out. The most important part of a commonsense approach to this new world is ensuring you get good data at all costs. New instruments should be validated. The repeatability of all metrics should be assessed. Equipment should be calibrated and checked regularly. Metrics should be validated in relation to the things that matter. Having a whole bunch of crappy data will lead the world off course. So, we need to maintain best practices for data collection, data entry, data cleaning, data storage, data visualization, and data analysis.
- Finally, we are still in the business of human relationships. We don’t coach spreadsheets. We need to lead with our hearts and our humanity, search for facts, and when we find facts that don’t conform to our aspirations, we need to adjust our aspirations and embrace the facts.