What Makes Great Athletes? The Science Behind Performance
When we watch a skilled athlete, performance often looks effortless. Think of Lakshya Sen at the Paris Olympics, executing a backhand shot under pressure with precision and control, or Declan Rice bending a free kick past Real Madrid’s wall with perfect timing and technique. In moments like these, athletes seem to anticipate, decide, and act almost instinctively. What we don’t see is the complex interaction between the brain and body: they read the situation, process information, and translate it into movement in real time.
Psychomotor learning helps us understand this process. A process through which athletes learn to connect their thoughts, perceptions, and memory, to consciously plan and control fine body movements and coordination for effective performance.
What’s Actually Happening During Performance?
Psychomotor learning helps us understand this process. Every movement in sport is underpinned by a chain of processes happening almost instantly:
Attention: what the athlete focuses on
Perception: how they interpret what they see
Memory and Recall: past experiences shaping decisions
Decision-making and Planning: choosing the best action
Movement execution: carrying it out into a response
This sequence is reflected in the four-stage performance cycle proposed by Romiszowski (1981), which expands on the traditional stimulus–response model. It highlights that rather than performance being a simple reaction, athletes constantly perceive, recall, plan, and perform, creating an ongoing loop between the performer and their environment. In fast-paced sports, this entire cycle unfolds in fractions of a second. The difference between levels of performance often comes down to how efficiently an athlete moves through this chain
Let’s try to understand psychomotor learning by comparing novice and expert athletes. Take badminton as an example. A badminton player often focuses on their own technique, how to grip the racket, or position their body. This internal focus slows down their responses because there is an inconsistency between the stages of the performance cycle mentioned above. In contrast, an elite player like Lakshya Sen is not thinking about the mechanics of his backhand in the moment. Instead, he is reading the game, picking up cues from his opponent, anticipating the trajectory of the shuttle, and executing the shot almost automatically. His performance reflects a highly developed connection between perception and action, where decisions and movements are seamlessly linked. The key difference is not just physical skill, but how efficiently they process information.
This ability to anticipate and make quick decisions is rooted in perceptual and cognitive development through experience. Skilled athletes don’t just react to what’s happening; they also predict what is coming next . Over time, they build mental representations of patterns in play, which allows them to recognise situations quickly and respond appropriately. Motor learning theories help explain how these abilities develop. One of the most influential of them is the Schema Theory of Motor Learning Skills (Schmidt, 1975), which suggests that rather than storing individual movements, the brain develops general rules or “schemas”. This allows athletes to adapt their actions and motor movements to different situations. For instance, an experienced badminton player might recognise a familiar attacking setup from their opponent and begin moving into position even before the shuttle is struck.
Instead, research consistently highlights the importance of variability in practice. When athletes practice skills in varied conditions and contexts, they develop more flexible and adaptable movement patterns. This not only strengthens learning but also improves transfer to real performance situations, where conditions are rarely predictable. For coaches and parents, this can sometimes look messy. Practice might seem less controlled, with more errors, but this variability is actually a critical part of the learning process. However, a key factor is to alter the variability of practice with the athletes’ intrinsic motivation variability to encourage the skills development on their part.
As athletes progress, the way they learn and control their movements also evolves, which is highlighted in the three-stage model of psychomotor learning by Fitts and Posner (1967). In the early stages, often referred to as the cognitive stage, performance is effortful and inconsistent as athletes’ cognitive resources are occupied with consciously trying to understand what to do. With practice, they move into more refined stages where coordination improves, and errors decrease. However, variability does not disappear; instead, it becomes more structured and functional. While variability tends to reduce with practice, it is never eliminated and continues to play a role in skilled performance. Therefore, skilled athletes maintain a balance between consistency and adaptability, allowing them to adjust their actions under pressure. At the highest level, movements may appear automatic as with Lakshya Sen, but this automaticity is supported by a system that remains flexible, enabling athletes to respond effectively to changing performance demands. All of these processes, included in the performance cycle: attention, perception, memory, and movement, come together to form what we often describe as tactical awareness. In reality, tactical awareness is not just about understanding the game; it is about being able to perceive relevant information, make quick decisions, and execute the appropriate action. This ability is not simply taught through instruction; it is developed through experience and well-designed practice environments.
For those supporting athletes, whether as coaches, parents, or practitioners, this has important implications. Training should go beyond technique and include opportunities for athletes to make decisions and solve problems. Practice environments should reflect the demands of competition, incorporating variability and unpredictability. It is also important to recognise that learning is not always linear or tidy, and periods of struggle and inconsistency are often where the most meaningful development occurs.
Ultimately, athletic performance is not just about physical ability. It is about how effectively an athlete can process information, adapt to changing situations, and execute skills under pressure. By understanding psychomotor learning, we can better support athletes in developing not only their physical skills, but also the cognitive and perceptual abilities that underpin high-level performance.
References
Caballero, C., Barbado, D., Peláez, M., & Moreno, F. J. (2024). Applying different levels of practice variability for motor learning: More is not better. PeerJ, 12, e17575–e17575. https://doi.org/10.7717/peerj.17575
Fitts, P. M., & Posner, M. I. (1967). Human Performance. Prentice Hall.
Romiszowski, A. J. (1981). Designing Instructional Systems. London : Kogan Page ; New York : Nichols Pub.
Schmidt, R. A. (1975). A schema theory of discrete motor skill learning. Psychological Review, 82(4), 225–260. https://doi.org/10.1037/h0076770
Taylor, J., & Ivry, R. (2012). The role of strategies in motor learning. Annals of the New York Academy of Sciences, 1251(1), 1–12. https://doi.org/10.1111/j.1749-6632.2011.06430.x
Van Rossum, J. H. A. (1990). Schmidt’s schema theory: the empirical base of the variability of practice hypothesis. Human Movement Science, 9(3-5), 387–435. https://doi.org/10.1016/0167-9457(90)90010-b