Capturing complex processes of human performance:Insights from the domain of sports

Het leveren van prestaties is een complex en dynamisch proces, waarbij psychologische-, lichamelijke- en omgevings factoren elkaar continue beïnvloeden en veranderen over tijd. Het is daarom moeilijk om specifieke factoren te identificeren die prestatieprocessen in de sport en daarbuiten verklaren. Mijn proefschrift heeft zich gericht op het begrijpen van prestatieprocessen vanuit het complexe samenspel tussen allerlei factoren. Hoe komen sporters bijvoorbeeld in een positief momentum (positieve spiraal) of negatief momentum? Dit gebeurt vaak wanneer sporters het gevoel hebben dat de winst dichterbij komt, of juist verder weg raakt, wat gepaard gaat met verschillende motorische en psychologische veranderingen. Wanneer teams van twee roeiers werden ingehaald door een tegenstander, vonden wij dat hun coordinatie relatief zwak werd en dat de kracht van de roeislagen relatief snel afnam, vergeleken met een periode waarin de roeiers zelf inliepen. Psychologisch gezien kwamen roeiers ook relatief snel in een “dip” als hun positie in de race verslechterde, terwijl een positief momentum zich juist vrij langzaam ontwikkelde. Daarnaast hebben we ook gevonden dat roeiers minder snel in een dip kwamen als zij daarvoor al een aantal successvolle races geroeid hadden. Momentum kan dus ook overgedragen worden naar toekomstige wedstrijden. Als we kijken naar prestatieprocessen van sporters, musici en wetenschappers over de jaren heen, vonden we dat er geen algemeen traject is naar de top. Ieder persoon ontwikkelt zich op een andere manier, wat verklaard kan worden vanuit een model waarin verschillende factoren (steun van ouders, hoeveelheid oefening, iemands motivatie, etc.) veranderen over tijd én elkaar op verschillende manieren beïnvloeden voor verschillende individuen

Capturer les processus complexes de la performance humaine : éclairages à partir du domaine sportif

La performance sportive est influencée par de nombreux facteurs, lesquels s’influencent eux-mêmes réciproquement. La complexité de ces facteurs et de leurs relations ayant été négligée par les chercheurs, l’objet de la présente thèse était de rendre compte de cette complexité, à l’aide de méthodes empruntées à l’approche dynamique. Nous avons pu montrer que (a) les joueurs de football les plus experts construisent leur représentations du jeu en cours (les liens entre actions réalisées sur le terrain) avec des niveaux de complexité les plus élevés; (b) en aviron, une organisation motrice complexe, impliquant des interactions entre de nombreuses composantes, sous-tend la génération des mouvements de rame en cours; (c) le momentum psychologique en aviron se caractérise par des changements psychologiques et de performance qui s’inscrivent dans l’histoire de la performance; et (d) la performance excellente se développe à partir des interactions en cours entre les facteurs personnels et environnementaux couplés. Ces différents éclairages montrent l’intérêt d’une approche de la complexité pour comprendre les processus de performance.The processes involved in human performance seem inherently complex and dynamic. For example, in order to “read the game”, a soccer player must integrate all the information from the ongoing movements and positions of team members, the opponents, the relative positions between them, where the ball is located, etc. Furthermore, an individual’s motor performance, which is particularly crucial in sports, depends on various simultaneous processes at different levels of the motor system: Cells, muscles, limbs, the brain, etc. In addition, individuals and teams do not perform in a void, but in achievement contexts, in which they strive for their goals, and their psychological states and performance may fluctuate as a function of many personal and environmental factors. For example, an athlete may enter a positive or negative spiral when perceiving that he or she is progressing or regressing in relation to the preferred goal or outcome (e.g., the victory). This perception of progress and regress, and the positive and negative psychological and behavioral (performance) changes accompanying this perception, are called positive and negative psychological momentum (PM; e.g., Gernigon, Briki, & Eykens, 2010). Positive and negative PM can emerge from one’s (or the opponent’s) mistakes, referee decisions, crowd behaviors, one’s psychological and physical state at a certain moment, and the interactions between these factors (Taylor & Demick, 1994). In addition, switching from performance on a relatively short time frame to a long-term process, individuals develop their abilities over multiple years, and hence over many practice or competition occasions. Ultimately, very few individuals develop world-class performance (e.g., winning Olympic medals), and their excellent abilities develop out of a combination of a variety of personal and environmental factors in interaction (e.g., motivation, coaching, family support, practice; Simonton, 1999). The current dissertation aims to capture complex dynamic performance-related processes, including the topics illustrated above. This means that we examine complexity at different levels (psychological, behavioral), time scales (from one training or competition session up to a career), as well as the interrelation between the processes across different levels and time scales

A Dynamical Systems Explanation of Talent Development in Sports

For decades, research on talent development in sports has attempted to detect the mechanisms explaining excellent performance. Although researchers generally agree that different personal and environmental factors play a role (e.g., genetic endowment, practice, family support), how these factors combine to shape athletes’ routes to excellence remains largely undefined. In line with the proposition to apply a dynamical systems approach to study talent (Abbott, Button, Pepping, & Collins, 2005; Phillips, Davids, Renshaw, & Portus, 2010), we aimed to test whether typical properties of talent development can be explained by a dynamical systems model. For this aim, we built a model in which an athlete’s ability growth is dependent on relatively stable resources (genetic endowment) and variable resources (e.g., environmental variables). Furthermore, the variable resources are directly or indirectly influenced by the athlete’s ability and by each other, thereby shaping each other’s changes over time. Graphically, this can be envisioned as a dynamic network of talent-related components, and mathematically it corresponds to a coupled logistic growth equation (Van Geert, 1991). We simulated the model on a computer in order to see whether it generates typical properties of talent development and excellence. Simulations of many athletes revealed idiosyncratic trajectories towards excellence and a low correlation between early indicators and later excellence, which is often observed in sports (Abbott et al., 2005). Furthermore, the simulations showed that the distribution of performance attainments is highly right skewed across the (simulated) population of athletes, which is typical in virtually any sports (e.g., many Olympic swimmers won no medal, whereas Phelps won 22 medals). Our results thus suggest that excellence in sports develops out of dynamic network structures, which supports the proposition that the dynamical systems perspective has much to offer to the study of talent development