“Coach to the athlete’s solutions; not yours”

Stu McMillan, Schilly C-P (1)
Stuart McMillan

Stuart McMillan


This is a saying that I probably repeat weekly in some way or another.  It essentially means that each athlete has their own unique way of moving; that our jobs as performance professionals (in this case, coaches, therapists, and sport scientists) is to appreciate and understand athletes’ ‘movement signatures’, and train them in a way that best aligns to this.  

Following along from our theme during the last few weeks, it is my opinion, that it is this ‘authentic’ way of moving that defines what is most ‘efficient’.  

A couple of questions immediately stem from this:

How do we identify authentic movement?

What happens if this authenticity is suboptimal?  I.e. if an athlete has been moving a certain way for X amount of time, and we have identified this as their ‘authentic movement signature’, and we also identify that this is not ‘correct’, or ‘optimal’, how and when do we intervene?  

Firstly, we can argue that very few movement solutions are truly ‘authentic’ any more.  We tend to coach the authenticity out of most athletes long before they finish their developmental pathways.  

If you have spent any time watching young kids play, the first thing you see is the freedom with which they move – authentic and efficient, children ‘just play’ / ‘just run’ / ‘just throw’, etc.  

Then us idiots step in and ruin it all.  

  • ‘Run on your toes!”
  • “Pump your arms!”
  • “Lean forward!”
  • “Pick your pocket!”
  • “Stay low!”

All nonsensical coaching cues that coach the efficiency right out of a kid.  

By the time that these children are in their teens, a vast majority of them have no idea what their ‘authentic’ (i.e. ‘most efficient’) way of moving is anymore.  Rather, they have become robotic systems moving in robotic ways.  

To be fair, many skills actually do have to be coached.  Others, however – the foundational skills of running, jumping, and throwing – are generally innate.  We learn to crawl, walk, run, throw, and jump on our own.  Shooting a free throw, hitting a slap shot, and kicking a soccer ball are different altogether – these are skills that normally require a coach to become proficient at.  The problem is that much of these well-meaning attempts improve proficiency at the expense of authenticity – and thus efficiency.

Let’s look at a real-world example:

Lisa Dobriskey is a former elite middle-distance runner.  2-time Olympic finalist, and silver medalist at the 2009 World Championships in the 1500, Lisa ran with what many coaches and sport scientists would call a ‘unique’ style. Most of these coaches and scientists would also argue that the way in which she ran was ‘inefficient’. 

Researchers started paying attention to running efficiency in the mid 1970s, where it became apparent that there was more to overall performance than pure capacity.  Until that point, the prevailing wisdom was that VO2 max was almost the sole determinant of elite distance running success.  However, in 1975, The Cooper Institute in Dallas, Texas, studied a group of 20 elite distance runners, and found that there was much more to running fast than great capacity.  For example, despite having a VO2 max of 13mL/kg/minute less than that of his compatriot, Steve Prefontaine, American Olympic Champion Frank Shorter actually had almost exactly the same personal best in the 3 mile race – an event assumed to be heavily dependent upon capacity.  (Of the 20 runners studied, Prefontaine had the highest VO2 max at 84.4mL/kg/minute, while Shorter had the lowest, at 71.3mL/kg/minute.  Thanks to Greg McMillan for pointing me towards this study, and the research that came from it).

Once we had an understanding that efficiency was important, the sport science community began to study it in greater detail – digging deeper than simple economy metrics (i.e. measurements of oxygen utilization at a set submaximal velocity), and looking at other measurements of efficiency, including kinematic variables. 

One of the metrics that has been studied is vertical oscillation of the center of mass or pelvis.   In fact, Folland and colleagues, in their 2017 paper Running Technique is an Important Component of Running Economy and Performance, described vertical oscillation of the pelvis as the single strongest correlate to running economy; i.e. the greater the vertical oscillation, the lower the running economy, and vice versa.  Further, running economy “… is known to be an important determinant of distance running performance.”

So greater vertical oscillation = less efficiency = lower performance.  

These findings are consistent with other studies of kinematics and running economy, including Heise, 2001 and Tartaruga, 2012, for example. 

Let’s get back to Lisa:

As you can see in this video of Lisa cooling down (this is at approximately 7:30 mile pace), she runs with a significant amount of vertical oscillation relative not only to the two athletes she is cooling down with, but to almost every other middle- and long-distance runner (in fact, she probably runs with more vertical oscillation than most sprinters do, who are not known for the efficiency of their jogging!)

Now – addressing the second question above, regarding whether or not we need to make a change when we have identified an apparent case of inefficient movement, and how we go about doing that:

This is what we know:

Running efficiency is an important determinant of running performance 

In elite runners, greater vertical oscillation equals lower efficiency

Lisa runs with significantly greater amounts of vertical oscillation relative to her competitors 

Therefore, Lisa is inefficient

Thus, if we decrease her vertical oscillation, we increase her efficiency, and improve her performance


Hmmm …

I’ll return to this later, but for now, let’s back up a little, and discuss how we normally go about defining what is good and what is bad, and using this information to inform how we work with athletes. 

Biomechanical Modeling 

We have a tendency to apply norm-based models – often based on the average of a population – to all the individuals we work with – regardless of their specific constraints.  

This ‘averagearian’ way of understanding our world has dominated science for decades, and was the topic of an excellent book by Todd Rose written back in 2016.  

The End of Average shows that most of our social and institutional systems over the last couple centuries have been designed around the average person – and this – and the fact that this average person does not actually exist – has had far-reaching implications in the current manifestation of these systems. 

The outline of Rose’s book is built primarily around the critique of the work of four men:

  • Adolphe Quetelet
  • Sir Francis Galton
  • Fredrick Winslow Taylor
  • Edward Thorndike

Rose argues that, primarily due to the influence of the work of these four, our social institutions ignore our individuality, and thus quash many would-be exceptional people and achievements, because they fail to fit into a society-deemed evaluation.  

Evaluating people through average measures is fallacious.  He goes on to identify many exceptions where people have succeeded by straying from the norm, and instead, embracing their individuality.  

Early in the book, Rose details an example of averagerian thinking gone wrong:

In 1950, the US Air Force measured 140 dimensions of over 4,000 different pilots and used the average of these measurements to design their first-ever standard airplane cockpit.

Not one pilot fit the dimensions of the cockpit. 

In fact, when using just three of these dimensions – neck, thighs and wrists – only 3.5 percent of pilots fit these averages. 

So, by using 140 dimensions, the Air Force were essentially ensuring their cockpit would fit no one.  

The Air Force were quick to remedy this, and led the way into building adaptable cockpits, which became adjustable seats in vehicles, and thus saved many a pilot’s – and driver’s – life; by simply allowing each individual to comfortably use the controls. 

“This assumption (that society should be built around the average) has led us to

Brain models that match no person’s brain

Standardized medical therapies that target nobody’s physiology

Financial credit policies that penalize credit-worthy individuals

College admission strategies that filter out promising students

Hiring policies that overlook exceptional talent”

– Todd Rose

Normative thinking — the belief there is one normal pathway — has fooled a lot of people in a lot of fields for a long time — and sport science (and by association — coaching) is no exception.  

We design sport biomechancal models that match no single athlete, and periodization models that are based on best-guess predictions of the reactions of multiple interacting complex systems that are themselves based on the averages of a population. 

When it comes to technique, rather than appreciating the individuality of the athletes we work with, we attempt to shoe-horn them into some ‘ideal’ — correct — biomechancal model.  

Sometimes this ideal is based on the average, as outlined above, and sometimes it is based on the ‘best’ – i.e. those in the sport who are the best performers (or in some cases, who adhere to some sort of assumed ‘efficiency’, based on how ‘smooth’ they look). 

For example, we see this in sprinting all the time.  The following is the general sequence of events:

  • Observe the best in the world
  • Pick an outlying mechanical aberration (something that is somewhat unique to that performer)
  • Assume that this aberration is the key to their success
  • Copy and apply to everyone

Think back to Ben Johnson – wide hands on the track in ‘set’, and jump out of the blocks to an upright position as soon as possible.  That must be the key to a fast start!

Maurice Greene – run the first 40m like you’re running through a tunnel, bent over at the waist looking at the ground.  He’s the best in the world – so we all should run through tunnels. 

Michael Johnson has a truncated arm stroke.  He’s the best in the world.  Let’s have all our athletes run with short arms and short strides.

Maybe you prefer the toe-drag: Asafa Powell drags his toe.  That must be the key to running 9.7  Let’s have everyone drag their toe.  

But we totally ignore the context behind why these athletes moved this way. 

Falling for this fallacy isn’t just for developing coaches by the way.  

Consider the following article from ten years ago (thanks to Mario Fraioli for sending it to me): The Perfect Stride.

If you don’t have the time to read the article, it essentially details American distance runner Dathan Ritzenhein’s first season with Nike Oregon Project coach Alberto Salazar.  

The following two paragraphs from early in the piece outline the dilemma faced by both runner and coach:

“For Ritzenhein, initiation into Salazar’s group proceeded roughly. As a coach, Salazar had become obsessed with optimizing his runners’ form, and Ritzenhein did not escape that scrutiny. During the athletes’ regular track workouts, Salazar criticized both the cant of Ritzenhein’s pelvis and his nearly horizontal forearm carriage, which he argued was wasting energy. He also criticized him for his tendency to run with his thumbs pointing up, rather than curled over in a fist. (According to Salazar, this strained the forearm, and thus, through a long chain of physiological connections, the leg muscles.) Though the objections puzzled Ritzenhein, he didn’t question them. “Alberto told me, ‘It’s imperative that you believe completely in what we’re going to do,’ ” he recalled, “ ‘because it will be completely different from anything you’ve been taught.’ ”

Salazar’s tinkering was controversial. Among élite coaches and competitors, tampering with an athlete’s natural running style is recognized as a risky enterprise. Many top distance runners have idiosyncratic form, and adjusting even a minor detail of a racer’s alignment can trigger a cascade of changes: subtle shifts in knee or foot position that can make the runner vulnerable to injury. This was particularly true for Ritzenhein, who was prone to developing stress fractures in the metatarsal bones of his feet. “When you run a hundred miles a week, your body finds natural positions that work,” the élite Australian runner Craig Mottram points out. “It’s flirting with disaster to mess with that.”

Interesting article.  

With predictable results, to be honest.  

What was almost certainly well-intentioned – improve running efficiency, and thus improve performance – pretty much manifested into three years of injuries, before Ritzenhein left the Program.  

**An aside: while it is generally easier in hindsight to identify what went wrong and what went right with any Program, it is far more challenging to understand the right path within the day-to-day chaos that is high performance sport – in real-time.**

The article details Salazar contrasting Ritzenheim’s mechanics with those of World Record Holder Kenenisa Bekele, and how they went about trying to rewire these mechanics so that they were more in-line with the Ethiopian –  including attempting to change his foot strike position, arm carriage, and leg cycle – in effect, trying to harness “the same advantages as a sprinter.”

On the one hand, there is some sense to this.  Salazar and his team had identified that running mechanics were a primary limiting factor to overall efficiency – and success, and went about trying to positively affect it.  But, there is always danger with this, as was outlined by Salazar at the time: 

“When you start changing an athlete’s form, there’s always a risk … Dathan knows that. And he’s willing to take that risk, because he doesn’t want to be the guy that’s just trying to get a bronze medal. Not this time. This time, he wants to be the winner.”

– Alberto Salazar

He said to Ritzenhein that “realistically, if we don’t change your biomechanics, I don’t think I can get you there.’”

So what would you have done??

The first question we must ask ourselves before attempting to affect a technical change is “is this a thing that truly requires changing?” – or is what we observe simply the athlete’s unique manifestation of the task based upon his or her own unique morphology and experience? 

(Actually, before we even get to asking this question, we must understand what it is we even mean when we refer to efficient, optimal, correct, etc. in the first place – thus this little series of posts)

Secondly, we must fully appreciate the magnitude of the change we would like to implement, the time required to implement it, and the potential impact this will have on both health and performance.  

Before committing to this process, the coach and athlete should go through a significant period of analysis to “consider the need for and direction of change”. Collins (2016) has identified a useful 5-stage model that outlines how the coach-athlete-support staff can identify and potentially manipulate technical change, which includes the following stages:

  • Analysis
  • Awareness
  • Adjustment 
  • (Re)automation
  • Assurance

Perhaps most-importantly, Collins differentiates between the acquisition of a skill and the refinement of a skill – i.e. changing versus tweaking.  Understanding what is required is imperative before moving onwards – thus the requisite period of analysis prior to any implementation of this process.  

From Carson & Collins 2016:  

“sub-optimal performance is not necessarily rooted in consistent technical errors (e.g., Cresswell & Eklund, 2006; Wanlin, Hrycaiko, Martin & Mahon, 1997), nor do circumstances always permit the time required to implement technical refinements with long-term permanence and pressure resistance, a process that may take up to 12 months depending on the complexity of the sport.”

Perhaps the most well-known – and least-understood – instance of making fairly major changes to a technical model that didn’t seem to require more than minor tweaking is that of golfer Tiger Woods.  His desire to constantly challenge himself is undoubtedly a major determinant to his success – but as happens so often, our greatest strengths are often our greatest weaknesses; perhaps if Woods – instead of making wholesale changes to his swing in search of some mythic ‘perfection’ – performed minor tweaks over time, he would still be playing at a consistently high level, and not spent the last decade fighting one injury after another.  

Total conjecture on my part – but from the outside looking in, I feel there is a good lesson here.  That being said, we must respect the dynamical nature of the human complex system, and understand that the athlete who learned to move a certain way at the age of 20 is a very different athlete at the age of 30.  

The take-home: be SURE that the change you seek is not just for the sake of fitting the individual athlete’s technical model into your pre-existing norm-based understanding of what you think it should look like; and, if you can – proceed patiently; introduce technical changes in small, manageable chunks that an athlete can efficiently and effectively integrate into their pre-existing technique.  Select the appropriate technical micro-challenges at the appropriate time, and organize training such that the athlete will realize their own solutions to the puzzles you provide. 

Efficient & Effective

Earlier, I wrote about the differences between ‘efficient’, ‘optimal’, and ‘correct’.  One term that I did not address, however, is ‘effective’.

And at the end of the day, doesn’t it just come down to this?

My friend Dr. Fergus Connolly writes about the differences between efficient and effective in his book ‘Game Changer’ – where ‘effective’ asks “does it achieve the desired outcome”? And efficient asks whether it achieves the desired outcome at a minimal cost.

Prior to moving forward with ‘effective’, however, let’s briefly discuss what we mean by ‘outcome’, and in fact, whether this should be the metric we judge something by – as whether we analyze a movement through its outcome, or its intention, is probably something we need to give some more thought to.  

As an analogy – 

If I tripped in the street, and accidentally smacked a person’s forearm and knocked the cup of coffee out of their hands, chances are that person would be kind of annoyed for a minute or two, but would recognize that the outcome (forearm smacking —> coffee dropped) was an accident.  If I purposefully knocked the coffee out of the person’s hands by smacking them on the forearm, then chances are I’m about to get into a fight with someone over their spilt coffee.  

The OUTCOME is the same, but the INTENTION is very different.  And if I was to retroactively analyze these two movements without understanding this difference, then my analysis will be challenged. 

Similarly, in sport, I may have the intention of moving a certain way, but the outcome is significantly different.  Any analysis of a movement is dependent not only on the outcome of the movement, but also upon the intent; “we are not only movement observers, we are movement interpreters.” (Fdili Alaoui, 2015). Only through acknowledging the athlete’s intention as it relates to the movement task, can we identify any gaps in the execution of the task.   

Once we identify the gap (the ‘artifact of the movement’) we can move on to classifying whether it is related to the behavior (attention), or the biomechanics (a morpho-functional aberration).  

You can see the manifestation of this in the real world every day while you’re walking down a busy street.  Either watch how the person in front of you is walking, or pay attention to how you, yourself, are walking.  Along with a host of other mechanical aberrations, chances are there will be some degree of external rotation of one or both feet through the forward swing of the leg or at touch-down (or both).  This external rotation is the ‘artifact’ – the gap between the intention (in this case walking in a straight line with our feet pointed forward – because why would we purposefully -consciously – walk externally rotated?) and the outcome (in this case walking with our feet externally rotated).  

If we observe closely, we will also see that every individual has a slightly unique way of walking – despite the intention being the same.  The fact that we all solve the innate task of walking in varying ways, but expect that we can all solve a much more complex task the same way is totally illogical.   

Let’s take block clearance for a sports example:

Many coaches and biomechanists teach one optimal model technique that they apply across the board to all athletes – despite surely understanding that all athletes are different.  

Each of the above silhouettes are of sprinters who are among the 126 humans to have ever completed 100m in under 10 seconds; by definition, a pretty homogenous group.  Each of these sprinters share a similar intention; however, the strategy by which they go about this – as well as the eventual outcome of their intention – depends on a multitude of factors, including force-producing abilities and their inherent morphology – all of which combine to produce an outcome which varies slightly (and in some cases – significantly) from athlete to athlete.

Rather than focusing on a single technical model from which to teach to, or – as discussed last week – fixate on the technical outliers and abnormalities, we should instead identify the basic mechanical principles common to the majority of high performers in the sport (or skill) we are concerned with.  

With block clearance, for example, it is clear that a vast majority of elite performers share the following actions:

  • the front-leg forcefully extends as the foot pushes against the front pedal 
  • the rear-thigh quickly flexes towards the torso 
  • the free-leg ankle flexes in anticipation of initial ground contact
  • the arms flex and extend to counter-balance the legs

The above characterizations will be consistent across a great percentage of the best performers; you may say that these form the ‘first principles’ of block clearance – the ‘foundational anchor points’ (FAPs) to which we teach towards.  We must understand, however, that these FAPs are the intent; and while the intent remains consistent, the outcome is not.  The outcome depends upon individual characteristics, task objectives, and the constraints that exist within the execution of the skill.

For example, ‘forceful front-leg extension’ will manifest in a variety of differing outcomes, with varying degrees of extension at varying levels of projection.  Christian Coleman may project out of the blocks at 35 degrees – because this is what may be most-optimal for him, based on his individual characteristics.  If Usain Bolt projected out at 35 degrees, he would be applying a band aid to his bloodied chin 10 minutes later.  His intention (i.e. clearing the blocks forcefully and efficiently) leads to a significantly different outcome than Coleman.  

Similarly, acceleration within the confines of a team-sport will manifest in an infinite number of outcomes, both from an intra- and inter-individual perspective.  The chaos of team sport means that no two movement outcomes will ever look alike – but that does not mean that the intention varies significantly, as it relates to the FAPs. Whether I am a winger knocking the ball past a fullback and accelerating around him, a baseball player running out an infield single, or a running back attacking the line, I am still forcefully extending my front-leg, flexing the rear thigh towards my torso, flexing my free-leg ankle in anticipation of ground contact, and flexing and extending my arms to counterbalance my legs.  This is what I mean when I say that athletes have to ‘know the rules before they break the rules’ – they need to understand the foundational anchor points at a fundamental level before they are able to stabilize them at more complex levels.  

Our job as coaches is to understand these foundational anchor points relative to the entirety of the skill (i.e. in context), the variable bandwidth of these anchor points relative to each individual athlete, develop teaching methods that work to maximize the stability of the execution of the skill, and – perhaps most-importantly – appreciate that both the outcome and the intention of the movement must be accounted for.  

We must also learn to embrace the variability around the execution of skills in general – especially when these skills are still at a developmental level; the common mantra is that ‘perfect practice makes perfect performance’, but in reality movement is improved not by exploring its core (i.e. ‘perfect technique’), but by exploring its limits (i.e. where it breaks down).

In learning an action, as Bernstein reminds us, an athlete repeats “not the means for solving a given motor problem, but the process of its solution – the changing and improving of the means”.  In other words, we learn not by repeating patterns of movement, but by repeating the process of solving the motor problem.

Bernstein summarized this as ‘repetition without repetition’:

“Repetitive solutions … are necessary because, in natural conditions, external conditions never repeat themselves … consequently, it is necessary to gain experience relevant to all various modifications of the task and external conditions”

– Bernstein

Although the approximate motions of movement are repeated, the manner in which they are solved are in constant flux (and by the way, the better the performer, the more potential efficient solutions to a particular motor puzzle they possess, and thus the more difficult it becomes to identify any artifacts of the movement execution).  

Our appreciation for the individuality of moment execution is not news by the way.  It’s been over 50 years since Bernstein first coined ‘repetition without repetition’; and in fact, you could argue that we have understood this at some level since Heraclitus’ observation that “one cannot step in the same river twice.”  

We are in constant flux

Indeed, in the running literature, we have had an appreciation of the importance of an ‘authentic’ personal style for at least 4 decades; as stated by Cavanagh, et. al, in 1977, while referring to the results of the previously discussed study of elite distance runners: 

“The biomechanical measurements are essentially quantitative expressions of running style and this factor is basically a learned response to a given set of anthropometric and physiological constraints.”

to be continued …


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