“It is a general principle of Psychology that consciousness deserts all processes where it can no longer be of use…” William James, 1890.1
One of the hardest things to do in sport is to perform under pressure. Anyone who has played tennis competitively will attest to this; the effortless forehands and backhands from practice have a habit of deserting players right when they need them the most. With its unique scoring system, tennis is often a game of which points you win, rather than how many. To highlight this, in Novak Djokovic’s incredible 2011 season—widely regarded as one of the most dominant ever—he ‘only’ won 56% of all points played. Being the best often means winning 1 or 2 crucial, pressure-filled points.
The ability to excel under pressure is rare. Much like confidence, it is an elusive trait. Why certain athletes perform on the big stage when it counts—Jordan, Woods, Nadal, Kyrgios—is not yet fully understood. However, research in motor learning does lend some clues.
“The trick is getting people to learn to move without knowing that they’re learning.”2
The ‘theory of reinvestment’ was coined by Professor Rich Masters, a psychologist interested in skilled performance. The theory is operationalized as follows: “an inward focus of attention in which an attempt is made to perform the skill by consciously processing explicit knowledge of how it works.”3 You can probably relate to this idea: who hasn’t overthought that easy forehand or second serve on a big point? By consciously controlling your movement, you undo the automatization of all your training. You miss. Reinvesting all that explicit knowledge you built up over years of practice and training ended up hurting your performance in the moment.
To address this, Masters advocated for an implicit learning protocol, even for beginners. By learning motor skills without understanding how you were doing it, it was harder for you to overthink the skill when under pressure. Many studies have supported implicit learning over explicit learning in numerous domains: golf putting, baseball hitters, table tennis forehands, basketball free throws, rehabilitation, and surgery. The ‘hard’ evidence for why this occurs may be revealed in electroencephalography (EEG) studies. EEG reveals the electrical activity of your brain. ‘Co-activation’ means parts of the brain are working in tandem, or are ‘coherent’. Low coherence indicates autonomous brain function. High coherence indicates a mutual reliance on another brain region. In a nutshell, “expert performers show greater cortical efficiency than novices, characterized by attenuation of nonessential brain functions (the reduction of neuromotor ‘noise’).”4 Experts have less ‘noise’ between verbal-analytic left brain regions and motor planning frontal regions of the right brain when performing. This supports the notion of automaticity and the opening quote from James way back in 1890.
“Almost everything we do, we do better unconsciously than consciously.”5
The video below, from Intuitive Tennis, advocates for the repetition of fundamentals to achieve instinctive strokes (which I agree with).
He is absolutely correct in suggesting that good players do not think about their strokes when playing well and that some professionals may be unaware of how they hit the ball on certain shots. This forehand lesson from David Nalbandian is quite vague in exactly how you hit a world-class forehand.6
The challenge for coaches is teaching fundamentals that will become instinctive. It’s easy to unload a thousand cues and tips and show off your technical knowledge of a stroke. It’s hard to teach a complex motor pattern in a way that becomes quickly unconscious. Two methods of implicit motor learning that I found interesting are outlined below.
Implicit Learning Protocols
Teaching by analogy: provide learners with an analogy of the movement. E.g., researchers in China instructed novice table tennis players to ‘hit up the hypotenuse of a right-angled triangle’ to teach them the topspin forehand (emphasis added):7
“Unlike literally instructed participants, analogy learners accrued little conscious knowledge of how they executed shots, and performed without disruption in attention-demanding or pressured conditions.”8
The researchers concluded that analogy can be used to create ‘biomechanical metaphors’ that provide learners with knowledge of the skill as a whole, rather than the individual pieces. Many other studies have found a similar effect for analogous teaching. Another example—researchers instructed novice basketball participants to try and “put cookies into a cookie jar on a high shelf” when shooting.
Errorless Learning: provide learners with a very easy initial task where they seldom make mistakes. E.g., researchers gave novice golfers putting practice from very short distances (25cm), and then gradually increased the distance (errorless condition). A second group practiced putting from difficult long distances (175cm) and then gradually decreased the distance (errorful condition). The errorless learners made fewer errors overall, performed more accurately on retention tests, and maintained performance when given a dual tone-counting task while putting, hinting that working memory was not employed when putting by the errorless group. Interestingly, further experiments showed that explicit hypothesis testing (visible adjustments to putting technique) increased for the errorless participants when distances increased to around 100cm, yet they still performed better than the errorful participants on accuracy and dual tasks. Perhaps that initial implicit learning may provide a protective buffer to performance, even if explicit task-relevant knowledge is learned after. This is important in technical domains like tennis and golf, where explicit knowledge of a swing will nearly always be taught to ensure efficient technique.
As athletes and coaches seek methods to ‘nurture the nature’ of automatic and instinctive performance in learners, implicit motor skill techniques may be of use.
James, W. (1890). The Principles of Psychology
Masters, R. (1992). Knowledge knerves and know-how: The role of explicit versus implicit knowledge in the breakdown of a complex motor skill under pressure. British Journal of Psychology, 83, 343–358.
Rich Masters & Jon Maxwell (2008) The theory of reinvestment, International Review of Sport and Exercise Psychology, 1:2, 160-183,
Baars, B. J. (1998). A cognitive theory of consciousness. New York: Cambridge University Press
The language barrier may have been another reason.
Liao, C.-M., & Masters, R. S. W. (2001). Analogy learning: A means to implicit motor learning. Journal of Sport Sciences, 19, 307–319.
Hodges, Williams, A. M., & ProQuest. (2012). Skill acquisition in sport research, theory and practice (2nd ed.). Routledge
This post seems a bit contradictory to your previous post “Death of a Forehand – Part II”. You mention here that errorless learning, or learning by starting off with much easier goals, has better results for intuitive learning. However, in your previous post, you also mention that red ball to green ball progression is contributing to the “death of a forehand” because players aren’t getting the “desirable difficulty” which can be difficult in the short-term but “proved greater long-term benefits”. In my experience, using the red ball progression is a great way for errorless learning in that the ball is much easier to hit for players (the bounce is at hip level height, and the balls are coming in slower, for example). My questions are: (1) why the contradiction? And (2) how would you recommend for junior players to start if not with the red ball to green ball progression?
This is absolutely great content, by the way, and I’m enjoying making my way through your blog!
This is super interesting stuff mate. Glad I came across it.