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At SimpliFaster, our gaze is forward. Training. Technology. Speed. Every day we ask: What are the best ways to go from where you are to where you want to be? As 2018 winds to a close, however, we thought we’d indulge in a rare backward glance to survey the year that was. Even then, in order to know where you’re going, you have to know where you’ve been, so this review will also double as a preview of what to expect from us in 2019.

Every day we ask, ‘What are the best ways to go from where you are to where you want to be?’ Share on X

Whether looking back or looking forward, SimpliFaster offers an accessible platform supporting coaches, athletes, and high-performance professionals along the micro and macro paths of athletic achievement, ranging from “one day better” and autoregulation to Olympic cycles and long-term athletic development. That open platform continues to grow through the ongoing evolution of our blog, the expansion of our online resources, the increasing line of performance equipment available in our web shop, and the broadening scope of our sponsorships and partnerships with leaders in the field.

Where do we go next? Here’s where we’ve been the past 12 months.

SimpliFaster Blog

Chris Korfist kicked off 2018 at SimpliFaster with the phrase “I thought I knew all of the butt exercises” in his post “Top 5 Glute Exercises for Sprinters.” There it is—whether you’re training a slate of elite sprinters or a crew of new clients harboring January 1st resolutions, whatever you thought you knew, there’s always more. Or, at least what you thought you knew can be re-examined, with enough of a different twist to make what was old into something new again. Over the course of the next 12 months, 261 original posts followed, presenting a range of authors, training methods, and performance technologies that would be impossible to do justice to in the space of a few short paragraphs.

When aspiring authors reach out to us and ask what we are looking for on the blog, we tend to respond simply: “Value.” Solutions have enduring value. Here’s a problem, here’s how I tried to solve it, here are the outcomes I observed as a result. Whether the challenge at hand involves general training for sport, properly using high-performance technologies, or specifically developing faster and more explosive athletes, since the answer to most questions in sport is “it depends,” from those simple foundations (problem-solution-outcome), the possibilities are limitless.

When aspiring authors ask what we look for on the SimpliFaster blog, we respond simply: ‘Value.’ Share on X

Through the course of 2018—and anticipating 2019, in turn—that enduring value often came via our regular contributors covering their unique areas of expertise. During the year, we featured Carl Valle’s prolific examinations of industry trends, techniques, and topics (“10 Sport Scientists Strength Coaches Need to Know”); William Wayland’s from-the-trenches programming advice (“7 Upper Back Pulling Exercises for Athletes”); Shane Davenport’s creative methods for integrating new equipment and technology in training (“The Top Accommodating Resistance Methods for Strength Coaches”); and Craig Pickering’s deep dives into cutting-edge sports science and research (“Creatine: Not Just for Muscle”).

Call those the “Big Rocks,” if you will—from those jumping-off points, the SimpliFaster blog in 2018 was further propelled by a diverse mix of returning authors and engaging new voices. We championed thought-provoking posts from continuing favorites such as Cameron Josse, Hunter Charneski, and Ken Jakalski; we also introduced proficient authors making their SimpliFaster debuts, including Jeremy Frisch, Nanci Guest, Carmen Pata, and Cody Roberts. Meanwhile, in our Freelap Friday Five series, we offered weekly interviews with top practitioners sharing their own words on the topics that inspire their passion each day, featuring notable conversations with JB Morin, Ken Clark, Michelle Boland, and dozens more.

In addition to coaching philosophies, exercise selection, and best practices, SimpliFaster is dedicated to the tools and technologies that support these methods on the track, in the gym, on the court, or in the lab. These tools may come with a technical manual, but for those still evaluatingwhether to buy or needing suggestions on how to make the best use of the tools they have, SimpliFaster continues to provide “from the horse’s mouth” articles on how to apply top products available on the market. Among the equipment-based posts on the blog in 2018, we featured Fredrik Correa on flywheel training with the kBox, Sean Smith on neck training with Iron Neck, and Eric Joly on developing speed on the HiTrainer.

Something we missed in 2018? Something to add in 2019? Feel free to send your firsthand insights on training, technology, sports, and speed to [email protected]. We consider new submissions year-round and our editorial team of Rachel L. MacAulay, Jeanie Simoncic, Joel Smith, and Nathan Huffstutter will work to bring your words to life.

SimpliFaster Resources

Back to that concept of value. All the coaching experience and insight in the world is useless without athletes to coach. You don’t need us to tell you that it can be a volatile industry, and in 2018 we added our Job Board to the SimpliFaster platform. It’s an easy-to-navigate, reverse-chronological listing with over 3,000 open positions for sport coaches, PE teachers, sports scientists, strength and conditioning coaches, and interns. Positions in track and field, soccer, volleyball, swimming, tennis, football, basketball, baseball, lacrosse— you name it, across the United States there is a demand for coaching talent.

For both job seekers and job posters, the job board is free to register for and use, with positions sub-categorized by sport and an additional section to post resumes. Visit the job board and see what’s out there.

Beyond the hiring front, in 2018 SimpliFaster also expanded our clinic calendar, featuring a monthly view of USATF educational offerings, TSAC courses, NSCA conferences, CSCS exams, and much more. Have a look to see what’s on the horizon and stay on top of the opportunities available in 2019.

SimpliFaster Store

In 2018, SimpliFaster added more and more products to the line of high-performance technology and equipment available in our online shop. The intent is, once again, value: Products we believe are the “gold standard” in their space, available to coaches, athletes, and performance professionals in a single location, with the customer support and follow-through that are the hallmarks of SimpliFaster.

The SimpliFaster store features high-performance products that are the gold standard in their space. Share on X

In addition to touchstone products like the Freelap timing system, GymAware’s velocity-based training, and Exxentric’s kBox and kPulley, the SimpliFaster store features the ability to browse and buy from 1080 Motion, Assess2Perform, Hawkin Dynamics, HiTrainer, MuscleLab, Swift Performance, PNOE, and more.

Sponsorships and Partnerships

Bringing the year full circle, not only did Chris Korfist write our first post of 2018, but the year was also bookended in part by our sponsorship of the Track Football Consortium’s clinic in Tampa, FL, in mid-December. Leading up to the pre-holiday conference, we featured new posts from event founders Chris Korfist (“Microdosing off the Track and the Tools to Make It Work”) and Tony Holler (“Why Coaches Recruit Speed (But Still Neglect It)”), and helped promote TFC events featuring speakers such as Ken Clark, Ron Grigg, Dan Fichter, and Al Leslie.

In 2018, SimpliFaster also continued our enthusiastic sponsorship of the Just Fly Performance Podcast. Joel Smith’s weekly interview series continues to be one of the most valuable online resources available, providing consistent insight into best practices in training from innovative coaches and professionals in a range of sports. Rather than asking boilerplate questions, Joel directs conversations toward those unique areas where each guest is currently pushing the envelope, providing consistent value to his audience in conversations with the likes of Henk Kraaijenhof, John Kiely, Rob Assise, and Cal Dietz.

Joel Smith’s Just Fly Performance Podcast is one of the most valuable online resources available. Share on X

In this past month, we were also pleased to be a sponsor of the online World Speed Summit, hosted by Tyrone Edge and including sessions on speed training with USC Track & Field Head Coach Caryl Smith Gilbert, ALTIS Sprints and Hurdles Coach Chidi Enyia, and previous SimpliFaster contributors including Derek Hansen and Tony Holler.

In addition to championing those providing educational resources in the field and on the web, SimpliFaster further bolstered our output in 2018 via partnerships with ALTIS and Power Lift, who each began to fill out their own pages on the SimpliFaster blog. Over the previous 52 weeks, ALTIS delivered tips on warm-ups and preparation from Chris Miller, the building blocks for a performance culture from Jason Hettler, and a master class in applying the ALTIS “Kinogram” method from Stuart McMillan and Dan Pfaff.

Meanwhile, under the Power Lift banner, in 2018 our friend and frequent contributor Bob Alejo posted articles on grip strength and game-day lifting. He also served as “master of ceremonies” for roundtable discussions covering topics ranging from power development to supplementation strategies, coordinating conversations with members of the Power Lift Educational Board (including Mike Young, Bryan Mann, and Doug Kalman).

Onward. Forward.

Just as Chris Korfist provided an appropriate kickoff to 2018, Jamie Smith of The U of Strength offered a fitting summation in answering the fifth and final question of our last Freelap Friday Five of the calendar year. (Smith was so comprehensive in his approach to tackling each question that we split the interview into two parts.)

“I look at resistance training and all of the varying weight room movements as tools that play a part in developing a robust and resilient athlete. When coaching an expansive range of different sports and skill levels, it’s essential to have an extensive toolbox.” 

Thank you for being with us on the journey through 2018. We look forward to doing our part in expanding everyone’s toolboxes as we move into the New Year.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

The commercialization of sport has led to an increased emphasis on getting an edge over the opponent in any (mostly legal) way possible. Historically, this was achieved through improved training techniques aimed at enhancing physical performance or reducing injury rates. Over the last few years, however, there has been a focus on how the backroom staff collects and utilizes data. This has naturally fed into an increased emphasis on how data is used to make decisions, and more and more sport scientists are tending to “borrow” from other disciplines, such as computer science and statistics, to help them make better use of this data.

As a result, we’ve seen a rise of the data scientist—or at least sports scientists that are comfortable in using data—within sport, with some prominent examples being Mladen Jovanovic, whose website I fully recommend, and Sam Robertson, a researcher from Victoria University who is embedded within the Western Bulldogs AFL team as Head of Research and Innovation. Additionally, a number of leading sports organizations, such as the New South Wales Institute of Sport and UK Sport, have recently advertised for data science positions.

People involved in sport should have some idea of what data scientists add to athlete preparation, says @craig100m. Share on X

Consequently, it is probably a good idea for people involved in sport to at least have some idea of what these roles add to the athlete preparation sphere. In this article, I aim to explore machine learning and its close cousin, data mining, in order to shed some light on what information we can expect to gain from these practices that are emerging in sport.

What Is Machine Learning?

First, some definitions. Machine learning refers to the process by which a computer system utilizes data to train itself to make better decisions. So, if we input a set of data—such as that from a GPS system—along with injury data across a season, the software will try to create a model that allows it to predict which players got injured. We can then feed in additional information, such as the next season’s injury data, and the computer will again try to predict injuries—but this time, it will also look for corrections in the calculations it makes in order to enhance its predictions. What calculations were unnecessary, for example, or which data point was given too much weight previously? We can then add more data, such as player wellness scores, ratings of perceived exertion, etc., and the program will continue to make these calculations, refining its output.

The goal of #machinelearning in sport is to be able to predict what will happen in the future, says @craig100m. Share on X

The aim of this is to be able to predict what will happen in the future: for example, which player from your youth team will become a world-class player? Which type of training is best for a given athlete? How likely is a given person to become injured, and how does this change with exposure to specific types of competition or training?

As such, the quality of the prediction is associated with the quality of data that is put into the machine. Garbage data in will lead to garbage data out. This is where the data mining aspect comes in: Data mining is the extraction of patterns (and therefore knowledge), from large amounts of data. It essentially represents the first aspect of efficient machine learning—which parts of data matter, and which can be discarded?

One of the advantages of the machine learning process within sport is that it allows us to better understand non-linear systems. Biological processes tend not to operate in a linear manner: This is important, because if we can only analyze using linear analysis—such as the “r” in standard correlation calculations—this can hamper our understanding of these processes. As a simple example, let’s take the recent work of Tim Gabbett and his development of the Acute:Chronic workload ratio. Based on the findings of a number of papers, we now understand that both too much and too little training are risk factors for injury.

Applying the #machinelearning process in sport allows us to better understand non-linear systems, says @craig100m. Share on X

If we plot this on a graph, with training load on the x-axis and injury risk on the y-axis, it would not be a linear relationship, but rather a curvilinear relationship in the shape of a U. As such, standard statistical methods for understanding this relationship (i.e., a non-linear relationship) are insufficient, and we need to start to build slightly more complex models. Adding more and more data types—such as wellness, age, previous injury history, sleep duration, and other aspects associated with an increased injury risk—increases the complexity of the modeling required.

Predictive Modeling

Another important aspect to consider is the difference between explaining what has happened and predicting what will happen in future. Explaining why an athlete has previously been injured allows us to identify some potential risk factors for this. Age, for example, has been found to be a risk factor for hamstring injury. As a result, we can state that age is associated with hamstring injury in athletes. But can we then use this information to predict future injury? To do this, we need what is termed a “holdout set,” meaning a set of data that has not been used in the previous statistical model to test the predictive power of that model in the future (the data used to create that model is termed the “training” set).

Obviously, in sport, it is far more important to predict what will happen in the future than explain what has happened in the past. A good example of this is a recent paper from the journal Medicine and Science in Sports and Exercise. Here, researchers collected data from a group of professional soccer players over the course of five seasons. They collected hamstring injury prevalence and severity, “exposure” time (such as time spent training and playing), anthropometric data, and information on a number of different genes. They then plugged this data into a statistical model, finding that the following were significantly associated with hamstring injury during that five-season period:

• Seven genetic variants
• Previous hamstring injury
• Age (with players over 24 more likely to become injured)

Furthermore, if the researchers selected two players at random, the probability that the player with the higher injury risk (as determined by the model) would be more likely to suffer an injury was around 75%…which is pretty solid. This represents the training data stage.

The next step was to use this model, and its related inputs, to “predict” future injury using holdout data. In this case, the researchers used data from the following season, in which 67 players suffered 31 hamstring injuries. Here, if the researchers selected two players at random, the probability that the player with the higher injury risk (as determined by the model) would be more likely to gain an injury was around 50%, which is essentially the same as flipping a coin—i.e., chance. So, while this model was useful in explaining previous hamstring injury, it did not predict future injury rates well at all.

The strength of any predictive model is enhanced by its total number of data inputs, says @craig100m. Share on X

The reasons for this lack of predictive ability are likely varied. The first is that the strength of any predictive model is enhanced by its total number of data inputs. A model trained on 1,000 players will typically outperform a model trained on 100 players. This is obviously problematic in professional sport, because the average first-team size in most sports varies from 20-50 players, and most teams do not want to share their data.

In individual sports governed by a central federation, it might be easier to overcome the problem of sample size—although, by definition, the prevalence of elite athletes is always going to be very low. Furthermore, sporting injuries are notoriously multifactorial, as demonstrated in a seminal paper by Roald Bahr and Tron Krosshaug. As a result, any statistical model aimed at predicting injury risk would need to have a great number of data inputs that cover the various individual risk factors, while the model used to predict hamstring injury in the paper under discussion only used a limited number.

As a result, it’s clear that, for complex outcomes such as injury risk—which is highly multifactorial in nature—we need a large number and range of data inputs. However, for more “simple” outcomes (and by “simple” I mean affected by a small number of variables), less complex models may hold promise. An example of this is muscle fiber type, which is largely influenced by genetic factors.

Understanding an individual’s genotype may be useful when it comes to selecting various training modalities and variables; but, at present, there is a limited number of available options by which we can achieve this. We could take a muscle biopsy, which is highly invasive and somewhat damaging to the muscle, or we could use some sort of test, such as a vertical jump, to predict muscle fiber type. A recent paper explored the effectiveness of a model utilizing seven different genetic variants to predict muscle fiber type, finding that it was pretty accurate. As a result, for more simple outcomes, such as muscle fiber type, a less complex model can be useful, while complex outcomes often require a complex model. 

From Data to Decision-Making

A further example of how we might be able to utilize machine learning as a way to support better decision-making was reported in a conference paper from late 2017. Here, researchers from Belgium utilized a machine learning tool to optimize training load based on the prediction of session rating of perceived exertion (sRPE). They collected data from 61 training sessions of elite Belgian soccer teams, where the players wore data collection sensors, allowing the researchers to gain insight into metrics such as speed, distance covered, and heart rate.

Additionally, after each training session, the players reported their sRPE for that session. Further inputs, such as environmental temperature, humidity, age, baseline fitness, muscle fiber type, and others were all added to the model. In total, the model performed well, providing coaches with the ability to predict sRPE before the session occurred, which has some obvious benefits: Individual training session load and intensity can be modified prior to the session occurring based on real-time data to ensure that the required outcomes are met.

The use of data mining and #machinelearning in sport holds promise, and has wide implications, says @craig100m. Share on X

Similar results have also been recently reported when attempting to predict the risk of injury in a group of soccer players. Here, the authors utilized a variety of inputs based around individual player anthropology (e.g., height, weight, age), sporting factors (e.g., position), GPS metrics, and various other workload-related aspects, such as previous training load. Their model could detect around 80% of injuries, which is better than currently available estimation techniques.

Additionally, the model had very few false positives; this means that few players who were flagged as being high injury risk went on to not get injured. This is important, because incorrectly suggesting a player is at an increased risk of injury can lead to needlessly missed training sessions, and possibly even missed competitions. A machine learning approach utilizing artificial neural networks has also been shown to correctly predict around 70% of a player’s competitive level (i.e., Premier League vs. Championship) when data such as passing accuracy and shots were utilized. Early research has also been undertaken to explore the use of machine learning in the development of optimal training programs.

Clearly, the use of data mining and machine learning in sport holds promise. If we can predict what will happen in a given circumstance, then we can make interventions to guide us to the desired outcome. This is obviously going to be of great use when it comes to training program design and load management, hopefully improving athlete performance and reducing injury risk. The concept also has wider implications.

For example, these techniques could be utilized when developing tactical frameworks—within a team, which moves and passing networks lead to the greatest success? Data mining can also be used with competition data to better understand the underlying aspects that are most associated with success. For example, if teams that win perform a certain skill better than others, it allows for the use of targeted technical training to ensure that players can effectively execute those crucial skills.

It’s important that coaches and data science specialists speak each other’s languages, says @craig100m. Share on X

This is undoubtedly an area that will grow in the future, as evidenced by the increasing number of data science roles in sport. As always, because sporting success often relies on an effective supporting team, the ability of each support team member to speak each member’s “language” is important. As such, it is potentially important for coaches to at least have a bit of working knowledge around data science, especially at the highest level. However, just as importantly, the data science specialists will have to speak the coach’s language. Given the promise this area holds, I look forward to watching it develop.

Further Reading

Practical prelude to machine learning by Kyle Peterson

Predictive modeling of football injuries by Stylianos Kampakis (PhD Thesis)

Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance by Emily Cust, et al.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Coaches of distance runners should be asking an overarching question, one that is often not mentioned because it seems way too obvious: How does an athlete get better at running? Most leading researchers, physiologists, and coaches will point out various things that coaches need to convey to their runners. But I like to narrow it down to basic, easily remembered concepts that can be expanded on in an equally simple manner:

1. How to use oxygen more efficiently
2. How to improve lactate threshold
3. How to enhance running economy

A bigger and stronger heart that pumps more blood to the muscles makes sense. So does having strong respiratory muscles that can move great amounts of air in and out of the lungs more efficiently. To emphasize this point, early in my coaching career, I had a wrestler who was running cross country to “get in shape.” After admiring a competitor who appeared to glide through three miles to win a big race, the wrestler observed “that kid has balloons for lungs.” Another essential component is the ability to efficiently extract oxygen from the blood by way of muscle cells. Knowing this, coaches can select at least one of these qualities to target in training.

In all of this, there is one component—by way of Owen Anderson’s most recent book, Running Form: How to Run Faster and Prevent Injury—that appears to address what I consider the “elephant in the room” that most coaches probably are aware of but are not sure how to deal with: running economy.

Running Economy

Running economy is the amount of oxygen we use at a given running speed. We can easily make the case that an efficient runner will probably use less oxygen. The reality is that genetics likely has something to do with this, but the amount of oxygen a runner can use effectively without any waste can be influenced by what I refer to as a few key economy indicators.

First, we need to consider what Dr. Jordan Metzl highlights as key economy indicators:

1. The way in which a runner pushes off the ground (vertical oscillation)
2. Arm swing
3. Stride length
4. Ground contact time
5. Stability
6. Number of mitochondria in the muscle cells
7. Strength and efficiency of the cardiovascular and respiratory systems
8. Efficiency of metabolism
9. Neuromuscular coordination

Some of these points fall under what most coaches would call biomechanics. And these same coaches would agree that good running form is economical with no wasted motion. Okay, that sounds great, but what can we do about it? How many coaches are struck when noting that some runners look inefficient but run very fast?

When this happens, we start to consider (probably with good reason) that the way a particular runner looks might be due simply to the way they need to translate the skills of running based on their structural asymmetries and abnormalities that we don’t even know exist. It’s a fair point for coaches to keep in mind: style may indeed be the way runners translate the skill of the sport.

Kaleidoscopic Coaching

At my clinic sessions, I now talk about our need to engage in “kaleidoscopic coaching” for those of us working with distance runners. Meaning, we all know that inside our personal kaleidoscope there are all kinds of shapes and patterns that we call coaching strategies, workout concepts, and enhancement drills.

Rather than fixating on maintaining and considering only one specific pattern, sometimes we need to “turn the tube” so the same pieces emerge in different ways. We might not choose to change what we do, and that’s fine. But at least we can come to accept that other patterns do exist, and sometimes looking closely at the new arrangements can enhance the way we coach our athletes.

I contend that sometimes we need to entertain the possibility that the elephant in the room for distance runners may not really be an elephant but a completely different animal that we don’t fully see because we haven’t “turned the tube” on our kaleidoscope. How a runner looks while running is often due to the traditional way we view mechanics, and that’s precisely why “turning the tube” is so important—we see all the same parts in a somewhat different way.

What Are Good Mechanics?

The classic example of one-way vision is how coaches have long approached the apparent mechanical flaws of Emil Zatopek, the great “Czech Locomotive.” But was Zatopek a mechanically-flawed runner who simply learned how to translate the skill of running despite the shortcomings in his form? Zatopek’s incredible success in distance running should lead us to consider that mechanics is not simply style of form and that perhaps we’re overlooking the idea that the mechanics we consider essential are not even the right ones—and in fact may be an entirely different animal.

As Owen Anderson suggests, “shouldn’t a definition of proper form go beyond smooth activity and control of the torso? Should it also include precise mention of how the feet, ankles, and legs are functioning with actual scientific numbers placed on joint and leg angles, limb positions and movements, and foot angles at initial contact with the ground?”

If forward propulsion comes from what the legs are doing, shouldn’t we focus on lower limb actions? asks @Zoom1Ken Share on X

Most coaches will say it’s difficult to do such a complicated analysis outside a locomotion lab, but perhaps we’re missing the whole point. If forward propulsion really results from what the legs are doing and not what the upper movements appear to reveal, shouldn’t we focus on the lower limb actions?

And this is what I believe Owen Anderson attempts to explain in his book.

Midfoot Landing

So what are the characteristics of the mechanics animal we need to identify? Here is what more and more researchers and biomechanists appear to agree on: a midfoot landing underneath the runner.

What do we need to identify? The midfoot landing underneath the runner, says @Zoom1Ken. Share on X

Why? First, this landing will reduce stress, and mechanical stress can lead to injury. Second, a midfoot strike makes for a shorter ground contact time. When a runner’s heel strikes, their foot hits the ground in front of their center of mass. We observe that the leg is straighter, and this straight leg results in a braking action. The foot landing so far forward from the runner forces them to pull their body forward instead of pushing off the ground.

The bottom line: Zatopek, most known for winning gold medals in the 5K, 10K, and Marathon in the 1952 Olympics, won because, as Anderson points out, “his legs and feet interacted with the ground in very positive ways, but this has never been mentioned in the examination of his form.”

To deal with this elephant in the room, we should first verify that it is indeed an elephant before we consider correcting its trunk position.

References

Anderson, Owen. Running Form: How to Run Faster and Prevent Injury. Human Kinetics, 2018.

Metzl, Jordan D., and Claire Kowalchik. Running Strong: The Sports Doctor’s Complete Guide to Staying Healthy and Injury-Free for Life. Rodale, 2015.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

In this three-part series, I explore 10 different research questions that I feel sports science could make a big difference by attempting to answer—and in many cases, is close to doing so. In Part 1 and Part 2, the questions I explored were:

1. Is a low-carb, high-fat diet effective for athletes?
2. Is caffeine really ergogenic for everyone?
3. Are isometric loading exercises as effective as eccentric loading exercises for hamstring injury prevention?
4. What effect does the gut microbiome have on athletic performance?
5. Can we develop real-time markers of exercise adaptation?
6. Can we use genetic testing to predict talent?
7. Do sports supplements have an additive effect, or is there a ceiling?

Obviously, I have my own biases, and some of these areas are from the fields in which I hold a strong interest, but I have tried to cast the net as wide as possible. For each question, I’ve provided:

• A brief review of what we know so far.
• Why it’s important to know more.

My expectation is that, over the next 10 years, we will get closer to more concrete answers in many of these.

Are the ‘Proven’ Effects of Ergogenic Aids and Training Interventions the Same for All Populations?

How science works is that you recruit a group of people—commonly termed “the sample population”—and then conduct your research intervention on them. Because researchers often require subjects who are somewhat similar in order to minimize sources of variation within the results, this often leads to certain groups of people being underrepresented within sports science research. As an example, men and women mightmetabolize caffeine differently, and females potentially metabolize caffeine differently at different stages of their menstrual cycles. As a result, most researchers tend not to recruit females into research exploring the use of caffeine, because they can’t easily figure out at which stage of the menstrual cycle their subjects may be at, or whether their use of oral contraceptives is affecting the results.

Is this a problem? Simply put, yes. Approximately half of the population of the world is female, and, accordingly, roughly half of all elite athletes are female. Yet, in many cases, we don’t fully understand how various interventions affect this sizeable population because they are so underrepresented within sports science research. Indeed, a recent study reported that less than 40% of subjects within sports science research were female.

Similarly, elite athletes are, by definition, quite rare. Very few individuals have the ability and luck to be able to perform at the highest level, and when they do, they’re unlikely to want to take part in research studies that may harm their performance. As a result, researchers find it very hard to conduct research, especially intervention studies, on elite athletes; consequently, elite athletes are comparatively underrepresented within sports science research.

Elite athletes are unlikely to participate in research studies that may harm their performance, says @craig100m. Share on X

Is this problematic? Well, we don’t really know as it hasn’t been extensively studied, but there is at least some research that suggests elite, well-trained athletes gain more of a benefit from caffeine, and less of a benefit from other ergogenic aids such as beetroot juice. This means that, if you’re working with an elite athlete, in many cases the research on which you’re basing your decisions is perhaps not valid in the athletes you coach.

This in and of itself isn’t necessarily a major problem; sports science doesn’t exist just to enhance athletic performance, but can also be a method to improve the health of a wide range of individuals by guiding training program design and nutritional interventions. But here, again, we can run into problems; because most researchers are based at a university, there is a tendency to recruit university students to exercise intervention studies—and these subjects don’t necessarily accurately reflect the wider population.

All told, we clearly need more research in underrepresented subjects within sports science. This is especially true for female subjects, notwithstanding the issues researchers face in controlling for the menstrual cycle, and elite athletes, again keeping in mind that the recruitment of such athletes can be difficult. By being able to understand these, and other, populations, we will be better able to make evidence-led recommendations, and support practitioners who work closely with these people, enabling them to (hopefully) make better decisions.

Why Does This Matter?

Many different populations of people, especially females and elite athletes, are underrepresented within sports science research. Crucially, some evidence indicates that both groups respond differently to certain interventions, suggesting a need for more targeted research on these populations in order to better extrapolate the data from current studies and enhance their performance and health.

Can We Predict Exercise Response?

When coaches give a training program to their athletes, they are essentially making a prediction, stating that “I believe this is the best training program for you at this time.” If the training program leads to improvement in the athlete, then the coach is seen to be successful—even though we don’t know if the athlete could have gained greater improvements from a separate training program. Conversely, if the athlete doesn’t improve, then the coach can alter the training stimulus for a second training block, with the updated prediction that “I now believe that this training program is the best for you at this time.” As a result, happening upon the optimal training program for a given athlete is often a process of trial and error, with many things tested, and the ones that are perceived to work sticking, along with a large helping of luck.

One of my interests is in trying to understand whether we can predict this exercise response; that is, can we determine how much someone will improve with an exercise training program before they undertake that training program? If we can gain the ability to do this, then we can remove the trial and error process, and match athletes to the training most suited to them.

If only it were that easy.

First, a little bit of background. Since the mid-1980s, it has been demonstrated through research that not everyone gets the same improvements from exercise. Most famously, this was shown in the HERITAGE Family Study, where researchers recruited 720 subjects to a 20-week aerobic training program, putting them through a wide variety of pre- and post-training tests. Here, the results showed that, while on average, VO2 max (a measure of aerobic fitness) improved by around 380 mL O2, some subjects improved by over 1000 mL O2, while others showed no improvement (and, in actual fact, appeared to get less fit due to training—which makes no sense and is most likely measurement error).

This was also true for various health markers tested for, such as fasting insulin; most people improved, but some more than others, while others got worse. Similar results have been shown following resistance training: after a 12-week training block in one study, the mean improvement in 1RM was 54%, but varied from 0% to 250%.

The cause of the variation between individuals in response to a training program is as yet unknown, says @craig100m. Share on X

It’s clear, therefore, that there is the potential for considerable variation between individuals in response to a training program. As a result, a big question that needs answering here is “What are the causes of this variation?” We can essentially boil these causes down to two factors: “true” and “false.” “False” factors refer to things such as measurement error and random biological variation, which make it look like there is variation, when actually there isn’t (if you’re interested, this is probably the best paper on the subject).

How much of the variation in response to a stimulus is “false” is open to debate. Nevertheless, we also know that there are a number of aspects that lead to “true” (i.e., real) inter-individual variation between subjects in response to a training stimulus. In a 2017 paper, I categorized these as genetic, environmental (i.e., non-genetic), and epigenetic, and I wrote about these for SimpliFaster here. Genetics play an important role in how much an individual responds to exercise, with studies tending to find that around 50% of the variation between individuals in exercise-related traits is due to heritable factors. The other roughly 50% is therefore down to aspects such as nutrition (getting enough energy, protein, and micronutrients), sleep, and psycho-emotional factors, such as the stress levels of an individual.

In theory, if we can ensure that everyone achieves the optimal environmental factors, such as getting enough sleep and adequate nutrition, then that should help to maximize adaptation to a given training program. This leaves us with genetic factors, which, explaining around 50% of the variance in response to exercise, are clearly important; if we could understand which genetic factors explain the variation in response, and we know the genetic makeup of a given athlete, could we use this information to predict the training response?

There isn’t a great deal of research in this field, which is why I’ve identified it as a potentially important route for future research. Some studies have looked at individual genes, such as ACTN3, the famous “speed gene.” Here, it appears that individuals with a certain type of this gene respond better to high-load resistance training (i.e., lifting heavy weights), and it may also play a role in post-exercise recovery and risk of injury. A few other studies have looked at the impact of other individual genes, but the relative effect size of any individual gene on training adaptation is likely to be small. Instead, we need to identify an increased number of genes, and combine them into a single score

This is what a study in which I was an author did; here, we used the results of 15 different genes to determine whether people would respond better to high- or moderate-intensity resistance training. We then gave around half the subjects the “correct” training, and half the “incorrect” training, for an eight-week period. After the training period was completed, those who had undertaken the “correct” training, as determined by their genetics, demonstrated around three times the improvement in a countermovement jump test than those who had undertaken the “incorrect” training.

These results were both praised and criticized in equal measure, and it’s important to keep in mind that they require replication. However, they do suggest there is promise to such an approach, especially when we consider that other researchers have shown the use of similar methods to predict the response to aerobic training. Like using genetic testing to predict talent (explored in Part 2 of this series), there are ethical concerns regarding the use of genetic tests for training prescription.

It’s not just genetics that holds promise in this area. A second potentially promising biomarker is that of microRNA (miRNA). In order to adapt to exercise, our body has to produce new proteins. These proteins can themselves drive adaptation, or form part of a new structure; for example, in skeletal muscle hypertrophy, the body produces proteins that form part of the muscle, allowing it to grow.

At the cellular level, these proteins are produced from DNA. Our body “reads” this DNA, creating messenger RNA (mRNA), which travels to the ribosome, which “reads” the mRNA and creates the new protein. miRNA appears to affect this process by breaking down or destabilizing the mRNA before it can be read (among other processes), altering the expression of a given protein from a given gene. miRNAs appear to impact the adaptation to training.

As an example, researchers from a 2011 study recruited 56 men to a 12-week resistance training program, comprised of five resistance training sessions per week. They then identified the top and bottom 20% of responders in terms of increases in muscle mass, and compared differences in miRNA signature between the two. They found that three miRNAs were downregulated in low responders, and one miRNA was downregulated in the responders.

The ability to predict the response to exercise is an area requiring further research, says @craig100m. Share on X

If we can better understand whether baseline (i.e., pre-training) levels of miRNA affect the response to a training stimulus, then miRNA profiling might be useful, although at present it requires either a blood test or muscle biopsy, which may not be palatable to all. Nevertheless, the ability to predict the response to exercise is an area requiring further research, as doing so should enhance the training process quite substantially. A further understanding of the contributors to variation in training response is required here, as is the development and validation of predictive panels utilizing this information.

Why Does This Matter?

Designing training programs is essentially a matter of prediction: Coaches match athletes to the training techniques they believe will yield the greatest improvements, and then refine via trial and error. If we can predict the response to a certain type of training before that training occurs, then we may be able to more readily match athletes with the training type that will promote the greatest adaptations, and hence improve performance to a far greater extent.

Are Low Doses of Caffeine Optimally Ergogenic?

I’ve already discussed in this series how caffeine is the most established, and most used, performance-enhancing drug in sport. And, best of all, it’s legal. However, even with all the research conducted on caffeine, and even with the wide use of this ergogenic aid, there are still a number of unanswered questions regarding the practical side of its use by athletes.

One of these is the impact of individual variation on caffeine, which I covered in Part 1 of this series, as well as in this paper. A second one is whether habitual caffeine intake reduces the subsequent performance-enhancing effects of caffeine (which I discussed in this paper); the surprising thing is, we don’t really know. Finally, we don’t necessarily know which dose of caffeine is optimum for performance—and we likely never will know, given how much variation there will be between individuals as to what an optimum caffeine dose is.

Nevertheless, most caffeine guidelines suggest that the optimum caffeine dose is roughly 3-6 mg/kg of body weight, with no additional benefit of doses greater than 9 mg/kg of body weight. In 2014, Lawrence Spriet published a hugely influential review paper on the impact of lower doses of caffeine—typically 3 mg/kg or less—on performance. The main finding was that these low doses of caffeine, while not as extensively studied as higher doses, likely did exert ergogenic effects, most notably in aerobic endurance events.

What I’m interested in understanding is whether these low doses of caffeine offer similar performance-enhancing effects as more typical higher doses of caffeine. This is a potentially important question; high doses of caffeine can exert a number of side effects that may negatively impact sports performance, such as increased anxiety, gastrointestinal discomfort, and poor quality sleep following training or competition, which may negatively affect recovery. If these lower caffeine doses are as ergogenic as higher doses, then athletes susceptible to these negative side effects can just take less caffeine for the same performance improvement.

Conversely, if any athlete is using caffeine to enhance their performance, then they want the caffeine to increase performance as much as possible. For example, a runner before a competition could choose between 2 mg/kg and 5 mg/kg for their caffeine dose. If both lower and higher doses are optimally ergogenic, then they can pick the dose based on preference. However, if 2 mg/kg, while ergogenic, is not as performance-enhancing as 5 mg/kg, and they can tolerate this higher dose, then they should choose that higher dose.

The optimal dose of #caffeine will likely vary from athlete to athlete and between events and sports, says @craig100m. Share on X

So, are there any differences between lower and higher doses of caffeine, in terms of their performance-enhancing effects? It’s hard to draw really firm conclusions from the research. If we return to Spriet’s seminal paper on the topic, I count 14 studies that used a low caffeine dose and utilized a performance test (as a brief aside, I always prefer it when caffeine studies explore the impact of caffeine on some aspect of performance, such as time to cover a distance, time to exhaustion, or similar, as opposed to measuring fat oxidation rates or ratings of perceived exertion). Of these 14, only four directly compared a low caffeine dose with a higher caffeine dose, and of these four, we get contrasting results—two find that increasing the caffeine dose enhanced performance to a greater extent, while two found that both the lower and higher caffeine doses enhanced performance to the same extent.

In short, there is a relative lack of trials comparing low and higher caffeine doses for their respective performance-enhancing effects, and these trials often have conflicting results. By increasing the number of studies exploring this question, we should getter a better idea of which type of caffeine dose is most optimal for athletes, allowing us to better inform their pre-training and pre-competition caffeine strategies.

Why Does This Matter?

Because caffeine is such as well-established and well-replicated (and legal!) performance enhancer, many athletes consume it. However, we’re not quite clear on the optimal dose yet, and, more realistically, it’s likely that the optimal dose will vary from athlete to athlete, and between events and sports. Recent research has shown that lower doses of caffeine—defined as 3 mg/kg or less—can be ergogenic, but it’s not yet fully clear whether such doses are as ergogenic as the more commonly recommended 3-6 mg/kg. Fully understanding this will enable athletes to be better informed as to the optimal caffeine dose for them, enhancing performance.

There’s Still Some Way to Go

While it is tempting to think that we pretty much know all there is to know within sports science, hopefully some of the points I’ve raised in this series demonstrate that we have some way to go before this is true. This is a good thing: The use of sports science has been instrumental in enhancing performance over the last 20 to 30 years, and has even spilled over into improving the health of non-athletes. Given the progress we’ve made so far, further enhancing our knowledge in these areas will allow us to improve health and performance to an even greater extent.

The use of sports science has been instrumental in enhancing performance over the last 20-30 years, says @craig100m. Share on X

Finally, this list isn’t exhaustive, and represents areas in which I have the most interest. I’d love to hear from you as to the questions you’d appreciate gaining some answers for from the field of sports science.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

In elite sports, athletes maintain an incredibly hectic schedule throughout the calendar year. During the season, they spend the bulk of their time on competitive games, practices, and general maintenance, while during the off-season, top performers will spend upwards of 20 hours per week preparing for the physical demands of the upcoming season. For college athletes, you can add time required for academics, “voluntary” workouts, and team functions. It’s pretty easy to see why these high-level athletes are constantly teeter-tottering along the edge of overtraining.

To keep top players healthy and performing throughout the season takes an experienced coach who understands their athletes and knows when to push harder as well as when to pull back on the volume and intensity. With this in mind, here are a few suggestions I’ve seen of how coaches monitor their players to better understand when they should crack the whip to push their players or pull the reins and allow them to rest.

Wearable Technology

One of the most popular ways coaches monitor their athletes is using wearable technology. There are tons of different athletic wearable gadgets on the market today that track various markers of performance and recovery. Some of the most popular options are sleep trackers, GPS/accelerometers, EMG garments, and heart rate monitors.

Sleep Trackers

Assuming they’re feasible for your team, sleep tracking devices can be an important piece to understanding how your athletes approach recovery (or their lack thereof). One of the better products I’ve seen is Whoop, which analyzes recovery, strain, and sleep. If you notice one of your players underperforming on a consistent basis, this tracking device can help you isolate the cause. Generally, an athlete who averages less than 7 hours of sleep over an extended period of time is not going to perform at their best.

GPS Devices

GPS tracking data helps a coaching staff understand different performance metrics (miles run, speed, etc.) during a match or practice and can provide insight into the stress placed on their players since, theoretically, more distance equals more stress. There are several companies in this market, with Catapult Sports being the oldest and most well-known.

One of my criticisms of GPS devices, however, is the implicit assumption that distance equals stress on the athlete, as different body types, genetics, and anthropometrics play a much greater role than a strictly quantitative measure of distance. For example, if a football lineman and a wide receiver each run a mile, the distance is the same, but the stress and fatigue each incurs is incredibly different.

EMG Garments

EMG garments have appeared on the sport technology scene over the last year or so and allow us to directly observe how much stress we’re putting on an athlete’s muscles both in real-time and from practice to practice. The previous scenario of a lineman and a wideout each running a mile shows how EMG is so valuable because it accounts for the differences in body type, genetics, and anthropometrics; it directly measures the stress that an athlete’s muscles undergo. Using GPS, we would not see differences in stress, but with EMG we see much greater stress placed upon the lineman as he fatigues as opposed to the wide receiver.

One of the most accurate and reliable companies I’ve seen and started using with my athletes in this space is Athos, which provides EMG compression apparel that mainly monitors muscular stress and muscular balance—think Under Armour and a medical grade EMG combined. I use it to establish baselines on my athletes from a stress and balance standpoint before monitoring them over time to either progress or regress my programming based on the goals for that individual athlete.

Also, the  real-time biofeedback helps my athletes self-assess whether they’re executing a movement correctly and then self-correct much quicker than external cues alone. Self-assessment and correction like this allow the athlete to build more efficient movement patterns, which in turn, helps them improve performance and reduce their risk of injury.

To get the most out of wearable tech, coaches must be realistic and have a plan. Share on X

Ultimately, wearable technologies are becoming a fixture in elite sport performance, but to get the most out of the technology coaches need to be realistic about what they want to measure and, most importantly, have a plan for how they want to implement the technology with their athletes.

I suggest coaches do some research before purchasing new technology to find the right equipment for their team and organization, as there are many companies out there that tend to overpromise and underdeliver on their marketing claims.

Subjective Questionnaires

Another great way to monitor athlete wellness—and one of the simplest—is a basic questionnaire that takes account of how your athletes feel at a particular moment. An old school method for sure, but it works and helps you get an idea of where your team and each athlete is on a given day.

The form will differ from program to program, but I suggest you have your athletes fill out a series of basic questions before every training session. Questions can include: “How many hours of sleep did you get last night?” “Do you have any areas of your body that are hurting?” and “How do you feel on a scale of 1-10?”

The questions should be specific and easily quantifiable. You don’t want an athlete just to say they’re “feeling okay.” Numbers are valuable and allow you to compare an athlete’s response from day to day. The questions should be the same every single day so you can monitor changes and trends over time to adjust training as needed.

I use questionnaires to decide if I should push an athlete on a given day. Share on X

I especially like to use these questionnaires for deciding if I should push an athlete on a given day. For example, if an athlete indicates they’re at a 9-10 or 10-10, I’ll talk with them to try to gauge the validity of that number before using that session as an opportunity to push their boundaries a little, depending on where we are in the season.

If we’re in an off-season strength and hypertrophy block, I might try to push the athlete by increasing the volume or intensity of the lift, whether by adding sets and reps, pushing a PR in a given lift, or progressing an exercise to challenge the athlete.

If we’re in an in-season maintenance block, I might use it as an opportunity to get some additional maintenance or skill-specific work done while keeping in mind the athlete’s upcoming game and practice schedule. How you push the athlete when they’re feeling good will always, first and foremost, depend on the individual athlete, where they are in their season, and their training priorities.

For tips on building questionnaires for your athletes, check out this article by Iowa assistant strength coach Cody Roberts where he dives into “Dos and Don’ts for Athlete Wellness Questionnaires.”

Performance Measures

Finally, a very common way to gauge how your athletes are feeling on a given day is by using established “baseline” metrics for different performance markers and then monitoring how far each athlete deviates from that baseline before or during a particular training session.

For example, if a football lineman with a 400-pound max bench is struggling with reps of 315 pounds, he’s probably feeling a little worn down—or worse, there may be an underlying injury. Either way, it’s an indication to back off the volume or intensity for the day and investigate further.

It doesn’t really matter what performance measure you use, only that the measure makes sense for your sport. A bench press, for example, probably wouldn’t give great insight to how a baseball player is feeling.

Resting heart rate is an easy performance measure that's useful across different sports. Share on X

A performance measure I like that’s easy to measure and can be useful across different teams regardless of sport is resting heart rate (HR). Once again, establishing a baseline and monitoring deviations is the key to success. After you’ve established a baseline resting HR, if an athlete shows up on a given day with a significant increase, they’re likely not in a good position to be pushed throughout the day’s training regardless of whether that increase is attributed to overtraining, dehydration, or general stress.

Here are some best practices from the Mayo Clinic for measuring and recording restingHR in your athletes.

Wrapping It All Up: Collect as Much Data as Possible

With any monitoring strategy, the goal is to better understand where your players are on any given day. The better you understand your players, the easier it is to gauge objectively how ready they are to train or play.

Ideally, we’d like to have as much data as possible, but more data does not always equal better data, and sometimes a “less is more” approach can be the key difference with the teams and organizations that use these strategies successfully versus the ones that do not. At the end of the day, our goal as strength and conditioning professionals is to find which data allows us to move the needle regarding player performance and availability in our individual sport.

By correctly implementing some of the monitoring strategies above, coaches better understand their players each season and, in turn, know how to more effectively adjust practice and training to win more games.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Many coaches might be aware of isoinertial training (horizontal) from the VersaPulley, which was introduced nearly 20 years ago. I was not aware of its popularity then, as I was training and not yet even considering coaching. More recently, the kBox helped put flywheel training back in the spotlight, and the systems from Sweden and Spain are huge here in the States.

Only use the #kPulley for an exercise after an athlete has mastered the traditional movement, says @ShaneDavs. Share on X

At Exceed Sports Performance, we got our hands on a kPulley in the middle of the 2018 summer off-season, and after a few days it became a part of our training. Since we already had a kBox at our disposal and an idea of what we liked and disliked, we decided to whittle down a list of exercises to the ones that made the most sense and wasn’t just about adding isoinertial training to an exercise better suited for conventional barbells and dumbbells. Creating the list was a hard process, because choosing your favorites and what may be best for others isn’t an easy task. This piece covers my five top exercises, with ways to do them better and how to determine when athletes are ready to perform them.

How I Created the List

I briefly touched upon flywheel exercises in a couple of previous articles, but kept the information pretty basic and straightforward. This piece will outline a few less-obvious choices and some potential options with which we are currently experimenting. We are lucky enough to have some research-grade sports tech at hand and will use it more to determine the efficacy of these movements. For now, the movements have passed the look and feel tests and have taken up a useful spot in our programming. We don’t typically just throw in some flywheel exercises, as that would be fairly lazy in my opinion, but we aim to replace or alter movements because of a specific need, and the kPulley and other flywheel tools create a unique opportunity for us.

All of the exercises can be done using traditional cables and elastic bands if needed, but the training effect won’t be the same. Four of the five movements require the athlete to aggressively overload the eccentric portion with an inflated concentric force, while the fifth (shoulder) should be strict during the entire exercise. As always, I would encourage any coach to come up with their own list based on experience, clientele, and specific needs, but we are sure there is value in the movements I list here.

Single Arm Eccentric Cheat Rows

Although it will seem like there are only two lower body exercises on this list (the rest being spine and shoulder training or rehabilitation options), almost all of them incorporate the lower body to create the necessary force to make them worth doing. What really makes the kPulley special is its use in horizontal pulling exercises that triple as oblique and adductor training as well. Although an athlete can do a simple row, and that is likely valuable for some of them, we much prefer the flywheel cheat row.

You can use a #kPulley in horizontal pulling exercises that triple as oblique and adductor training, says @ShaneDavs. Share on X

This exercise is great because it gives purpose to a movement that many athletes are already trying to do. How many times have we seen athletes do dumbbell rows with a little too much weight and somewhat “clean” the weight up? Plenty. Now we have a reason to let them cheat, assuming they know what an honest row should look and feel like. I believe this movement is actually much more of an anti-rotation/rotational core movement than just a simple row, and what makes this exercise special is that gravity isn’t limiting the technique and loading. “Cheating” can be taken to the next level and the forces acting upon the body are atypical of traditional weight training exercises.

Video 1. The amount of cheating can range from small assistance to total body exploitation of momentum creation. Coaches can experiment with how strict the eccentric portion of the lift is.

When an athlete performs the movement, they should use leg drive and a little bit of rotation to create the momentum and accelerate the handle concentrically. Then, they should control eccentrically using the lats, muscle groups surrounding the shoulder, obliques, and everything connected to the floor. Partial squat, half-kneeling, split stance, or any other method of ground contact will work, provided you can use the leg drive effectively. Most of the time, the exercise grooves into a pattern that is both safe and effective as a row and an anti-rotation pattern.

Rotational Chops with Triceps Ropes

The issue with most rotational movements is the lack of eccentric balance. Although the follow-through of rotational throws with medicine balls does have incidental eccentric contractions, the overload isn’t as high as you can create with flywheel training. In order to get a real bang for your buck, you need to cheat with skill and athleticism. Compensation cheating or fatigue-style degradation in technique is bad news, but a coordinated intentional cheat is what we are looking for with rotational chops.

Video 2. The goal with chops is to drive the force from the legs, so the receiving phase of the exercise is more demanding than traditional movements. The trunk is an excellent joint system to transfer force, but think ground up.

Receiving a true eccentric overload means athletes must create concentric momentum with a technique that uses the entire body. With most of the exercises listed, we want athletes to use a different technique to create momentum and a strict technique to receive the eccentric forces. If you’ve done your homework on baseball players or any rotational athlete, you’ll fully understand that forces are created from the bottom up. The ground is important and footing is paramount. If you need to add a wedge or a foot bar to create the force, go for it. The initiation of the exercise does start with a leg drive, but concentrically it finishes with a swing, so the athlete can be immediately ready to receive the forces in the proper body position.

Forces are created from the bottom up: The ground is important and footing is paramount, says @ShaneDavs. Share on X

Ropes are great attachments for rotational work. We use triceps ropes and prefer a single arm attachment using an overhand grip. We instruct the athlete to keep their hands close to them during the concentric phase of the movement and (usually) let the hands drift away during the eccentric portion. Similar to a Pallof press, the exercise has more torque as the hands extend farther away.

Once you gain efficiency in the strict chop, you can add a step or rotation during the concentric phase. You can step forward and to the side with the concentric phase as a conservative progression or alternative. Whether you stick with a strict movement or utilize the step, the chop is a great tool for tackling heavy eccentric force to the obliques and groin.

Eccentric Overload Hamstring Curl

We employ a lot of hamstring equipment at our facility, and most have a specific function and use. The same goes for the kPulley’s involvement in our hamstring work. I need to make the point that one exercise is never a cure-all or silver bullet for hamstrings. If you read the research, hamstring training seemed to be all about EMG years ago; now it’s about lengthening and eccentrically preparing hamstrings for sport. Don’t follow the leader: Diversify your program and train hip extension, knee flexion, and both simultaneously to ensure you cover the bases. As I mentioned before, we use flywheels to improve upon or replace a movement when it creates a better alternative than traditional options.

Video 3. Coaches should start off with the two legs up and two legs down before moving to two legs concentric and one leg eccentric. The rolling devices today are available from a few equipment manufacturers.

A popular technique in flywheel training is the “two-up and one-down” concept that most coaches are familiar with. Before isoinertial training became popular again, veteran coaches used two legs to lift the weight up before lowering the weight down with one leg when performing hamstring curls and RDLs. As with the row and chops listed above, adding technique variation to the concentric portion of the lift to overload the eccentric portion is just as valuable and effective as the two-to-one method, and the kPulley and kBox are perfectly set up for such.

I use #flywheels to improve or replace a movement when it’s a better choice than traditional options, says @ShaneDavs. Share on X

I believe there are five major exercises (and a few variations of each) for the hamstring using the kPulley that are effective, and each has a different setup and function. For this piece, I focus on the supine bridge hamstring curl, as it’s one of the most popular methods for training hip extension (statically) and knee flexion (dynamically) in rehab or training settings. There are much better options for training true hip extension, but the supine bridge hamstring curl plays an important role in our training program and is worth exploring a bit. Supine bridge curls do have eccentric benefits, but lack a true closed chain quality, so we consider them a high-priority assistance exercise rather than a main option for performance.

Whether you use a slideboard (towel, slide disc) or a wheeled implement, there are four ways to train the bridged hamstring curl. No bridge, bridge after concentric, bridge during eccentric and concentric, and two-to-one lowering. As for the topic of eccentric overload, the concentric (no bridge) to eccentric (with bridge) is our method of choice, and if you try it I’m sure you’ll agree.

Shoulder Reconditioning with Eccentric Forces

Narrowing down all the shoulder-specific exercises to just one option or movement isn’t very fair, so it’s easy to get upset that I didn’t pick external rotations or another arm care flavor of the week. The shoulder is an interesting joint in the PT world, and every year sees a change as to the best exercises for preparing the overhead athlete for sport and reducing injuries. By the time this article is posted online, I’m sure the best practice with shoulder rehabilitation and training will have changed again. Yesterday’s rotator cuff exercise will fade into tomorrow’s scapular stability training and then to something else later. Just like the principles of good ACL prevention, good training will help keep the healthy prepared.

Video 4. The external rotation range of motion is based on skill and individual anatomy. Build the range of motion up carefully and gradually over time.

We don’t do much additional training to the shoulder, but we do know that the rotator cuff, even with a well-trained athlete, may not be fully maximized. There are dozens of exercises for the shoulder and arm, but the primary recommendation is that everything is performed strict and you only use the kPulley after an athlete has mastered the traditional movement.

We have a few movements that we tend to gravitate to the kPulley for, but the good old half-kneeling external rotation (ER) can be recognized by many and is still broadly accepted. The key here, as with the other exercises listed, is that you create a little more momentum/concentric force using a variation of the technique and then quickly get into the proper technique to control the eccentric portion. An added bonus of the flywheel ER movement is that the transition from a face pull or row to an ER involves a bit of dynamic stabilization, which most studies have shown to be more important than simply strengthening the cuff.

Prepare a program that utilizes appropriate methods—not just the methods that sell to the masses, says @ShaneDavs. Share on X

Athletes with great corrective exercise routines and poor prime mover strength never succeed in sport. The opposite is often found in the training room or on the surgeon’s table. Be smart and prepare a program that utilizes appropriate methods—not just the methods that sell to the masses. Giving lots of funky exercises is like giving out full candy bars during Halloween—it may make you popular around the block, but it’s not the best practice for your nutrition program. Make sure your shoulder diet follows the same principles as your eating: well-rounded and balanced, with less junk.

My last recommendation with external rotation and scapular retraction exercises is to make sure you work with a very good sports medicine professional who is involved with football, javelin, and other throwing sports, not just baseball. Having a therapist who isn’t afraid to do anything overhead, while having the responsibility for throwing athletes such as quarterbacks and track athletes, has helped us tremendously. Sometimes it’s good to put aside the therapeutic bands and light dumbbells, and load the shoulder group with enough fortitude that it’s actually trained.

Knee Extension

Since I mentioned ACL prevention above, it’s worth noting that we deal with plenty of knee issues and “rehab” at our facility. An absurd number of young athletes start training with general knee pain or are training because of a major knee injury. We know that strength is lacking and that is usually where we start, but general strength is not quite specific enough. We have included a lot more quad strengthening, directly, in our programs and add in sequenced work for using the knee in almost all of our knee pain or injury cases.

We use the #kPulley the most for seated leg extensions and standing terminal knee extensions, says @ShaneDavs. Share on X

The two movements we use the most when it comes to the kPulley are seated leg extensions and standing terminal knee extensions (TKE). Both take some practice and setup manipulation, but the eccentric forces you can create using the pulley are invaluable. Specifically, the TKE movement: An athlete can use a little shift or body “English” to get the wheel spinning and then lock down the movement to control the flexion.

Video 5. Eventually, leg machines will grow in popularity, but for now a box works well. In the future, isometric and eccentric workouts will evolve to handle rehabilitation demands even better.

In almost every single “case” of general knee/patella pain we’ve come across, the affected leg has much less strength and control than the “good leg.” It’s probably a case of “chicken or the egg,” but we know that incorporating knee extension work directly before leg training has made a huge impact on our recovery times and long-term knee health success.

Video 6. It takes a while for coaches and athletes to get the handle of this exercise, but EMG biofeedback may help. Basically, the athlete is doing a reverse leg extension and uses the friction of the ground and momentum to challenge the quads.

Respect Momentum Before You Start

Most of the exercises listed use a little body English to overload the eccentric portion of the lift and, in doing so, require a little more focus and attention. There is an associated risk with any exercise that overloads a joint or body movement. With anything that will yield results, risk must be worth the reward.

Some exercises should be done one on one, while other exercises are fine to do without supervision at all when an athlete is highly trained and experienced. Other exercises are sure to be popular with the kPulley, but for our program, we know this list works well. Try each exercise and judge for yourself, as every facility and team training environment is unique enough to warrant you spending the time and thought to decide what is ideal for your situation.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Shailah Thornton arrived at Chapin High School as an 18.58 100-meter hurdler—she left Chapin with the second fastest time in school history (14.06) and a bronze medal at the UIL 5A State Meet (14.57). Shailah’s work ethic, focus, and determination were the top factors in her posting such dramatic improvements over the course of two years. They were further evidenced in her breaking her personal best during the indoor 60-meter hurdles (9.09) in her first year at the United States Military Academy Preparatory School (West Point).

Over the course of three articles, I’ll discuss Shailah’s practice plans, including drills, skill work, specific hurdle rhythm development, and other factors that led to her improvement. I should also note that many of our hurdlers at Chapin have improved using the same type of skill work and three basic hurdle drills. While the development and skill levels of hurdlers have improved at different rates, the focus of the training program has remained similar throughout. Finally, I’ll address the difference between coaching athletic freaks like Shailah and beginning hurdlers, and how we approach coaching different hurdlers of varying abilities, height, experience, and other factors.

This first article will address instilling speed for the 100/110 meter hurdles and why speed plays such a significant role in the sprint hurdles. As always, there are an infinite number of ways to coach any one event in track and field, but we choose to place a high priority on speed development for the 100/110 hurdles because, despite the barriers, it remains a speed event.

Early in the season, we test an athlete’s fly 10 or fly 30 time to measure absolute speed. Shailah ran a 3.67 timed with Freelap, which demonstrated that she was capable of running a high 12 or low 13 in the 100-meter race. This allowed us to understand that, while she didn’t have speed that would allow her to medal at the Texas state meet, she definitely had the natural speed to be able to three-step between each hurdle. Because of her power, Shailah was also a great accelerator; and because of her athleticism, she developed great hurdle rhythm and coordination.

Last year, I coached a hurdler with a fly 30 time of 3.63, which is faster than Shai, but the hurdler was only able to three-step through eight hurdles because she was only 5-feet tall, and ultimately ran a PR of 15.58. I also coached another hurdler last year who, despite having a slower fly 30 (3.85), ended up with a PR time of 15.35 because she is 5’6” and was able to three-step the entire race.

Speed in the 100/110 Hurdles

Because distance is predetermined in the 100/110 hurdles—including the distance to the first hurdle, distance between each hurdle, and distance to the finish line after clearing the last hurdle—working speed for hurdlers requires a very specific pattern. The first specific hurdle speed drill we try to develop is acceleration to the opening hurdle. Before we even begin to approach the hurdle, we spend a lot of time (twice a week during the general prep phase) working on pure acceleration without a hurdle. As I mentioned in “How to Create a Base of Power and Speed,” we practice acceleration in many forms, but accelerating to the first hurdle is a very specific skill that needs to be practiced early and often throughout the year.

Accelerating to the 1st hurdle is a very specific skill that needs to be practiced early and often, says @mario_gomez81. Share on X

About accelerating to the first hurdle, Boo Schexnayder says: “The hurdle race begins with driving strides. These driving strides are strong steps with less than maximal frequency, and should give the athlete the same sensation one gets when sprinting uphill.” When trying to determine the best accelerating pattern for any hurdler, we spend a lot of time observing proper acceleration mechanics and looking for the most effective setup for the remainder of the race.

The variation of driving/pushing strides is dependent upon the athlete. Shailah pushed out hard for four strides before feeling tall and attacking the hurdle. The 5-foot hurdler pushed for five or even six strides because of her height. There are several tables that show how far each stride should be with proper mechanics, but ultimately the goal is to arrive at step 8, the cut step, between 1.9 and 2.1 meters before the first hurdle with proper acceleration mechanics.

Regarding height difference, Coach Ron Grigg, (Director of Cross Country/Track and Field at Jacksonville University) said, “[The] simple answer is that the shorter the hurdler, the farther away they need to take off in order to raise their center of mass in the correct flight parabola. Conversely, they will land closer to the hurdle they just cleared. It isn’t a significant amount, but there is a difference.”

Video 1. Zoee Huerta eight step acceleration to first hurdle in 2.65. Posted PR 15.58 as senior after a season best of 16.00 as a junior.

Video 2. Shavontee Harris eight step accel to first hurdle in 2.81. Posted PR 15.35 as a junior after posting a season best of 16.74.

For example, Shailah would consistently take off right on the 2-meter mark, while many of the other short hurdlers work on taking off father away. One interesting note to share here is that all of the shorter female hurdlers I have coached tend to overstride by casting their foot and essentially braking all the way to the first. They overstride because they do not think they will arrive close enough to the first hurdle. The overstriding often happens in the later steps to the first hurdle (step 5/6/7), which in turn decreases the velocity of the hurdler.

Wicket Spacing for Hurdlers

Because spacing between each hurdle is predetermined (8.5 meters for females and 9.14 for males) and three-stepping needs to be a learned pattern, we set up wickets with equal spacing when working with hurdlers. For example, the ideal stride length between barriers should be around 1.83 meters (approximately 6 feet) for female hurdlers and 1.94 meters (6’4”/6’5”) for males. Based on height, landing, and technical execution, the stride patterns will obviously differ.

Video 3. Zoee Huerta working on turnover using wickets set at average stride length for hurdler at six feet after acceleration.

Getting athletes to three-step properly and maintain speed is extremely crucial in the #hurdles, says @mario_gomez81. Share on X

However, getting athletes to three-step properly and maintain speed is extremely crucial in the hurdles. Therefore, when working wickets with hurdlers, we often set the wickets progressively up to 6 feet for females and maintain that distance and do the same for males up to 6’4” or so. We treat this as a part-whole-part progression, so that athletes can understand the frequency and speed between hurdles. This establishes the stride pattern needed to three-step between each hurdle. Obviously, the height difference between a hurdle and wicket is significant, but the main purpose for the drill is for the athlete to feel the stride pattern.

In the upcoming articles, I will explain the other three drills our hurdlers use, and why we rarely, if ever, use one-half hurdle drills.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

In this three-part series, I explore 10 different research questions that I feel sports science could make a big difference by attempting to answer—and in many cases, is close to doing so. In Part 1, the first three questions I explored were:

1. Is a low-carb, high-fat diet effective for athletes?
2. Is caffeine really ergogenic for everyone?
3. Are isometric loading exercises as effective as eccentric loading exercises for hamstring injury prevention?

Obviously, I have my own biases, and some of these areas are from the fields in which I hold a strong interest, but I have tried to cast the net as wide as possible. For each question, I’ve provided:

• A brief review of what we know so far.
• Why it’s important to know more.

My expectation is that, over the next 10 years, we will get closer to more concrete answers in many of these.

What Effect Does the Gut Microbiome Have on Athletic Performance?

The human microbiome—the collection of bacteria across our bodies, but primarily centered within the digestive tract—has been the subject of increased interest over recent years. The gut microbiome has a number of roles to play in the maintenance of optimal health, including the production of nutrients such as vitamin K₂, the neutralization and breakdown of pathogens and carcinogens, and the regulation of the immune system. Even more recently, research has shown that the gut microbiome can influence the levels of brain neurotransmitters such as dopamine, via the gut-brain axis, as well as the control of inflammation and oxidative stress during endurance exercise.

Because our gut microbiome clearly has a host of important roles, both in terms of general health and exercise performance, and is highly modifiable by diet, interest has grown in trying to harness this knowledge as a means to enhance performance. At present, we know that an increased amount of diversity within the gut microbiome is positive; obese people tend to have reduced bacterial diversity compared to lean subjects (and, in mice at least, transplanting the microbiome of a lean individual to an obese one can drive weight loss). Elite athletes also have an increased gut microbial diversity relative to non-athletic subjects (the main drivers of this being an increased amount of exercise, as well as an increased amount of protein intake).

And that, in essence, is where we are now: We know that we want diversity, and we know that consumption of a varied diet and exercise promote that diversity. If we were to test the microbiome of athletes, we likely would struggle to give more in-depth and personalized advice than that, at present. This is why we need additional research in this area; it would be worthwhile to be able to understand how we can utilize the information from a microbiome test to identify key areas for change. This, in turn, should drive performance enhancements.

These changes could be driven through the targeted use of particular bacterial strains through the consumption of probiotics, the recommendation of specific dietary changes, and even—potentially—the modification of training. We already have promising evidence that probiotic use can support immunity within athletes undergoing heavy training, and so further insights in this area should prove worthwhile.

Right now, we’re at the starting line of being able to utilize #gutmicrobiome info within sport, says @craig100m. Share on X

To that end, the main questions I feel need answering within the sporting sphere in regard to the human gut microbiome are:

1. Can we utilize gut microbiome testing to provide specific interventions aimed at improving performance?
2. Do changes in gut microbiome act as markers of overtraining or excessive training load?
3. How does microbiome diversity change across the course of both the training and competitive periods, and can we use this information to target key changes within the microbiome?

As such, I feel that, right now, we’re very much at the starting line of being able to utilize gut microbiome information within sport. We require further developments to drive the field forward and enhance our understanding—which, in turn, will hopefully lead to performance enhancements.

Why Does This Matter?

The human gut microbiome has interested scientists and the general public for a number of years. We know that an increased diversity is important, and we know the basic building blocks of what drives this diversity, but outside of that we struggle to make specific recommendations. By increasing our knowledge in this area, we may be able to use the regular screening of the gut microbiome in athletes to develop personalized recommendations for nutrition and training practices, and use it to serve as a marker of training load.

Can We Develop Real-Time Markers of Exercise Adaptation?

When we set training programs for athletes, we hope to improve their sporting performance, in part by improving their physiological abilities. Therefore, coaches have to set training that provides sufficient stimulus for adaptation to the given exercises to take place, and select exercises that drive the correct adaptations. A second important issue is that of recovery: Coaches must program training so that the sessions promote fatigue, but not too much fatigue that the athlete under-performs at the next training session or competition, or becomes injured. As such, there is a fine balancing act between sufficient workload to drive adaptations and not too much so the athlete becomes overly fatigued and/or injured. This is, of course, difficult.

The development of effective training programs has an additional challenge: It is often hard to determine which adaptations have taken place until weeks or months later. This is due, in part, to the improvements derived from training programs occurring in tiny increments on a session-by-session basis. As a result, coaches and support staff often have to rely on trial and error, selecting sessions and exercises that they think may drive the relevant adaptations and hoping for the best.

However, given that we now know there can be considerable individual variation in response to a training stimulus—both between athletes (i.e., what works for athlete A may not work for athlete B), and in the same athlete across time (i.e., what works for athlete C in year 1 may not work for athlete C in year 2)—selecting these exercises can be difficult. A potential solution may be the development of real-time markers of exercise adaptation; basically, can we develop a test or tests that tell us how well the athlete is adapting to the training stimulus, and indeed whether the specific required adaptations are occurring, in (or close to) real time.

The development of real-time markers of exercise adaptation would lead to more effective training, says @craig100m. Share on X

There are a couple of leading candidates in this area. One is cell-free DNA, which refers to circulating fragments of DNA found within the blood. At rest, small amounts of cfDNA can be found in our blood, but following both acute and chronic physiological stress, the concentration of cfDNA increases rapidly. As exercise represents a source of physiological stress, increases in cfDNA occur following both prolonged endurance exercise and resistance training sessions, as well as following a 12-week training block. Perhaps even more importantly—from a biomarker perspective—cfDNA changes appear proportional to both exercise intensity and duration, and are transient, often returning to baseline with 24 hours, even after highly exhaustive exercise.

In addition, cfDNA may also be a potential marker of fatigue; in a 12-week resistance training program, increases in cfDNA correlated with increases in mean training load within each three-week sub-block, with the highest concentrations associated with a decrease in physical performance. Furthermore, some research has demonstrated that the correlations between cfDNA and rating of perceived exertion (RPE, a subjective—but reliable—marker of training load) are stronger than those for lactate and RPE. It also showed that increases in cfDNA concentrations are greater than any other biomarker, potentially suggesting enhanced sensitivity compared to more traditional biomarkers.

In Part 3 of this series, I’ll discuss the prediction of training response; looking at how miRNAs may play a role, with specific miRNAs associated with an increased chance of being a responder to a certain type of training. miRNAs may also act as a useful biomarker of exercise response. For example, a number of studies have demonstrated that specific miRNA concentrations change in response to a single aerobic training session, as well as a longer-term aerobic training program.

Similar to cfDNA, miRNA concentrations appear sensitive to training intensity and duration. Potentially even more important, miRNA concentrations can plateau if there is insufficient training progression, demonstrating miRNA’s potential as a method to monitor training. Finally, the extent of miRNA changes following aerobic training are proportional to the training load, with specific miRNAs associated with post-exercise inflammation—information that may potentially guide recovery techniques.

Alongside miRNA and cfDNA, which appear to offer promise as markers of how well the athlete is adapting to and tolerating a training load, there is the potential that we can measure specific adaptations. There are a number of ways that this may be possible, including measuring the proteins produced by specific genes (proteomics), along with measuring specific epigenetic changes at particular points within a gene. As an example, the body is able to add a type of tag to certain points within DNA, which make that specific region of DNA harder to read. These tags are methyl (-CH₃) chemical groups; hence, this process is termed “methylation.” DNA methylation can potentially be passed from generation to generation, although the majority of methylation markers are transient, and can be added and removed (termed “de-methylation”) according to different stimuli.

One potent stimulus of DNA methylation and de-methylation is exercise. For example, sedentary individuals are far more likely to have methylation markers on a gene called PPARGC1A, which is involved in the promotion of mitochondrial biogenesis—an important aspect of improvements in aerobic fitness. If these sedentary subjects start to exercise more frequently, however, this methyl group gets removed, allowing the subsequent exercise adaptations to occur. This raises the potential for monitoring of specific DNA methylation patterns, which may be indicative of the types of adaptation that are occurring, so that training can be adjusted to target the specific adaptations that are required.

A limitation, at present, is that these tests are likely to be highly invasive. Epigenetic changes, such as methylation, histone modifications, and miRNA concentrations, tend to be tissue-specific. As such, if you want to understand what is occurring in the muscles of your athletes, then you need a muscle tissue sample. You get this through a muscle biopsy—a somewhat invasive procedure that has the potential to cause damage, making its adoption by elite athletes unlikely. Furthermore, cfDNA testing appears to require the collection of blood almost immediately following exercise, which again has practical issues. Ideally, we will be able to develop saliva collection techniques for cfDNA, miRNA, and similar; at present, there are some methylation markers that can be collected via saliva.

Ideally, we will be able to develop saliva collection techniques for cfDNA, miRNA, and similar, says @craig100m. Share on X

Of course, the danger with such an approach is that coaches become over-reliant on the data, seeking to derive specific, very narrow adaptations, such as increases in mitochondrial biogenesis or type-II muscle fiber hypertrophy. While it is tempting to go hunting for these adaptations, training as a whole is often more than the sum of its parts. So, while a different exercise may not drive the specific adaptation required to the same extent, it may enhance competition performance to a greater extent. As such, if these real-time markers of exercise adaptation are developed, then coaches and support staff will need to take a holistic, pragmatic approach to such information, using it to guide their decisions, but not making it the sole basis of what they do.

Why Does This Matter? 

The purpose of training is to enhance performance, and so coaches have to develop training plans that they believe will do so. This can be difficult—if the training load is too high or too low, optimal adaptation will not occur, and injury or fatigue is more likely. As such, if we can develop sensitive, real-time markers that allow us to better understand the impact of specific sessions and training programs on an athlete, then we can make small adjustments to training sessions on the fly, hopefully improving performance to a greater extent.

Can We Use Genetic Testing to Predict Talent?

Let me ask you a question: If, on the day you were born, you moved to Jamaica to live with Usain Bolt, eating the same foods as him, living the same lifestyle, and doing the same training, do you think you would break the 100m World Record? Most people would answer no (I’m always surprised by the people that answer yes), which illustrates something that we all understand: Elite athletes are intrinsically different than “normal” people.

Research tends to back this up, too: A study from 2007 reported that the heritability estimate for being an elite athlete is around 66%, which we can roughly interpret to say that the difference between Usain Bolt (the elite athlete) and your dad (probably not an elite athlete) is approximately two-thirds due to inherited factors, and these factors are primarily (but not exclusively) genetic. More recently, researchers found that your chances of winning an Olympic medal are higher if you have a family member who has already done so.

Interest in this area has led to the identification of a number of genetic variants that appear more common in elite athletes. An example of one of these is ACTN3, with research showing that variation at a particular point in this gene is more common in elite sprinters than non-elite sprinters. This genetic variant in ACTN3 appears to modify muscle fiber type, with the “sprint” version of this gene associated with an increased proportion of type-II fibers, something that is obviously advantageous to elite sprinters. These findings have been well replicated, and ACTN3 may even have an influence on training adaptations, post-exercise recovery, and injury risk, as I explored in a paper back in 2017. There are other genes that have been shown to impact the attainment of elite athlete status, such as ACE and PPARGC1A, but of them all, ACTN3 appears to lead the way.

So, if we know that genetics play a role in the development of elite athlete status, and we know some of the genes that cause this, can we use genetic testing to predict those individuals who will go on to become elite athletes? At present, no—and there are a number of reasons for this.

The first is that the effect of any individual gene is likely quite low. For example, ACTN3, the gene which likely has one of the largest impacts on elite performance, explains roughly 3% of the variance between individuals. This is not an insignificant amount, but it’s also not huge. Secondly, while individuals with a certain version of ACTN3 are more likely to be elite speed-power athletes, roughly 80% of the population of the world have this same genetic variant. As a result, the vast majority of people on this planet with the “sprint” version of this gene are not elite athletes. Furthermore, research has shown that even if you don’t have the “sprint” version of this gene, you can still be a successful athlete (in addition to this study, I know of two Olympic sprinters—one of whom is an Olympic medalist—who do not have the sprint version of this gene).

We don’t know enough about which genes impact the attainment of elite athlete status, says @craig100m. Share on X

This means that we cannot use a single gene to identify future elite athletes, because no single gene exists with the required predictive ability. Instead, a better approach may be to combine a number of genes into an algorithm. There’s a problem here too—we actually don’t know all that many genes that influence the attainment of elite performance. This is a problem common in medical research, whereby researchers know that genetics explains much of the variance between individuals that get a disease and those that don’t due to the heritability estimates gained from previous research. However, at present they have been unable to identify those specific genetic variants; this is termed the “missing heritability problem.”

A great example is that of height: research suggests that genetic variation explains around 80% of the variation in height between individuals. However, while scientists have discovered around 1,185 genetic variants associated with height, these variants “only” explain around 25% of the difference between individuals. This means that the remaining 55% of variance explained by genetics remains uncovered. We see this with elite athlete status: At present, around 155 genetic markers have been identified to contribute to the attainment of elite athlete status. This likely does not explain enough of the variance between athletes to be used in any predictive capacity. (At the time of writing, I have a paper under review testing this in a small sample of elite athletes.)

Right now, then, the main issue is that we don’t know enough about which genes impact the attainment of elite athlete status. In order to improve the predictive ability of genetic tests for talent, we need to discover a lot more. The problem here is that the discovery of new genetic traits associated with elite athlete status is difficult; because the effect size of any single variant is likely to be very small, researchers require very large sample sizes, well in excess of 1,000 subjects.

Now, there aren’t many elite athletes around, so recruiting 1,000 to a study can be very difficult. This issue is hindering research at present. Nevertheless, if additional genes are discovered, my personal belief is that we will (eventually) be able to develop a threshold score for an algorithm that contains all the required genetic variants: a score above this, and the athlete is more likely to become an elite athlete; a score below, and they are less likely.

However, it still will be the case that some, and perhaps most, individuals with a score above this threshold will not become elite athletes, while some of those with scores below this threshold may. As a result, genetic testing for talent identification will likely never be completely predictive, but it may provide more information on which decisions can be based. It may also be used to guide training prescription in the future, as I wrote in a 2017 paper.

Even if we could develop a genetic test for talent, it’s not clear whether we should use it, says @craig100m. Share on X

A secondary issue around this is whether it is ethical to utilize a genetic test for talent, should one ever be developed. A number of prominent researchers in the field have expressed doubts as to whether such an approach is ethically justified, and there are certainly a lot of unanswered questions regarding the use of such tests. Here are a few:

• Can a club compel players to undergo a genetic test?
• What happens if an individual is found to possess a genetic variant associated with disease?
• Would such information be used to further discriminate against the player?

As such, even if we could develop a genetic test for talent, it’s not clear if we should even use it.

Why Does This Matter?

Because identifying the next Cristiano Ronaldo or Usain Bolt at a young age can be hugely profitable for sports clubs, there is an interest in methods that might be utilized to support such an approach. The use of genetic testing to identify future elite athletes is a scenario envisioned by many, and the technology is now available for such a test to take place. However, at present, such a test would not be accurate, and, furthermore, it’s hard to envision how it ever would be.

Additionally, such tests have serious ethical questions surrounding their use, and these would need to be rectified before the tests can even be considered for utilization. However, there is some evidence that genetic information could be used to inform training program design, supplement use, and dietary advice, as well as for managing injury risk. As such, this is an area to potentially keep an eye on in the future, to see how it develops.

Do Sports Supplements Have an Additive Effect, or Is There a Ceiling?

These days, we have a pretty good idea of which supplements have the potential to exert a performance-enhancing effect, or at least don’t negatively affect performance when the dosing is correct. For example, as I’ve explored previously, we can be pretty sure that caffeine is performance-enhancing for most people, most of the time. We can also add to that list common ergogenic aids such as sodium bicarbonate, beetroot juice, beta-alanine, and a handful of others.

Of course, when these ergogenic aids are researched, they are commonly studied in isolation: Give a group of subjects some caffeine tablets to see if their performance improves, and if it does, you can easily isolate what drove that performance enhancement. However, athletes rarely take a performance-enhancing supplement in isolation.

For example, many utilize caffeine-containing energy drinks for their pre-training and competition caffeine kick, and these drinks often come with sugar and taurine, two substances that also have ergogenic effects. Interestingly, a recent meta-analysis on the effects of energy drinks on sporting performance concluded that, as the taurine dose of these drinks increased, so too did the ergogenic effects, while this wasn’t the case for the caffeine dose. Additionally, an endurance athlete might consume both beetroot juice and caffeine separately, but close together in terms of timing, during their pre-race preparation. What we need to better understand—and precious few studies actually examine—is the effect of these ergogenic aids when combined.

We need to better understand the effect of ergogenic aids when they’re combined, says @craig100m. Share on X

When two supplements have a similar mechanism, there is the possibility that taking them together could exert no additional effects. For example, beta-alanine and sodium bicarbonate are both cellular buffers; does taking the maximum ergogenic dose of one mean that any additional intake of the second supplement provides no further effects? Or, because the mechanisms are similar but not the same (e.g., beta alanine is an intracellular buffer, while sodium bicarbonate is an extracellular buffer), does taking both together provide an additional benefit? Could ergogenic aids cancel each other, for example?

Similarly, is there a performance ceiling associated with ergogenic aids? If, for example, the most an athlete can improve with nutritional interventions is 3%, and a single ergogenic aid increases performance by 3%, then do additional ergogenic aids, even those working through separate mechanisms, provide no additional benefits? I’ve seen this covered briefly in a number of papers, including this editorial from Shona Halson and David Martin, but the most comprehensive review I’ve come across on the subject was authored by Louise Burke and published in the journal Sports Medicinein 2017.

In her paper, Burke reported on some of the more common supplement co-ingestion strategies, of which the most commonly studied was that of sodium bicarbonate and beta-alanine. The results showed a wide spread of findings: Some studies reported combined benefits, others no effects, and others negative interactions. In part, this is due to both a low number of studies and a low number of subjects in each study—demonstrating why further research in this sphere would be useful.

The short answer to this question, then, is that we don’t know. And yet, it is clearly important to enhance our understanding in this area, because athletes regularly co-ingest ergogenic aids as a means to enhance performance. We can, and must, better understand these potential interactions in order to drive athletic performance forward.

Why Does This Matter?

While we understand that ergogenic aids—when taken in isolation—enhance performance, athletes very rarely consume these ergogenic aids on their own. Instead, they more commonly consume them in combination with other performance-enhancing nutrients. However, the effect of this co-ingestion of ergogenic aids is poorly understood: The potential is that taking two or more such aids together may further enhance performance through additive mechanisms; have no additional benefit; or lead them to compete with one another, reducing the performance enhancement. This area has been very poorly studied, demonstrating a need for further exploration in the future, and for research to accurately mirror how ergogenic aids are used by athletes in real life.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF