Large data and Bayesian modeling-aging curves of NBA players.

Researchers interested in changes that occur as people age are faced with a number of methodological problems, starting with the immense time scale they are trying to capture, which renders laboratory experiments useless and longitudinal studies rather rare. Fortunately, some people take part in particular activities and pastimes throughout their lives, and often these activities are systematically recorded. In this study, we use the wealth of data collected by the National Basketball Association to describe the aging curves of elite basketball players. We have developed a new approach rooted in the Bayesian tradition in order to understand the factors behind the development and deterioration of a complex motor skill. The new model uses Bayesian structural modeling to extract two latent factors, those of development and aging. The interaction of these factors provides insight into the rates of development and deterioration of skill over the course of a player's life. We show, for example, that elite athletes have different levels of decline in the later stages of their career, which is dependent on their skill acquisition phase. The model goes beyond description of the aging function, in that it can accommodate the aging curves of subgroups (e.g., different positions played in the game), as well as other relevant factors (e.g., the number of minutes on court per game) that might play a role in skill changes. The flexibility and general nature of the new model make it a perfect candidate for use across different domains in lifespan psychology.

Gritting One's way to success - Grit explains skill in elite youth soccer players beyond (deliberate) practice.

Practice is one of the most important predictors of skill. To become an expert, performers must engage in practice for a prolonged time to develop the psychological characteristics necessary for outstanding performance. Deliberate practice (DP), that is focused repetitive activities with corrective feedback, is particularly beneficial for skill development. The amount of accumulated DP differentiates experts and novices. However, the predictive strength of DP weakens considerably when it comes to differentiating between differently skilled experts, leaving a way clear for other non-practice related factors to exercise their influence. In this paper, we demonstrate using a large sample (388) of elite youth soccer players that one such factor, the personality trait of grit, predicts expertise level both directly and indirectly. Grittier players accumulated more time in coach-led team practice, the activity, which is arguably closest to DP in team sports, which in turn predicted the skill level. Other practice activities, such as self-led training or playing with peers, were not predictive of skill level, neither were they influenced by grit. Grit, however, continued to exert a direct positive influence on the skill level of players even after accounting for the hours of DP accumulated. Overall, a standard deviation of change in the grit score resulted in at least a third of standard deviation improvement in skill. Our findings highlight the need for the inclusion of additional factors in theoretical frameworks in situations where the predictive power of traditional expertise factors, such as practice, is limited.

Reading the Future from Body Movements -Anticipation in Handball.

In speed-based sports that require fast reactions, the most accurate predictions are made once the players have seen the ball trajectory. However, waiting for the ball trajectory does not leave enough time for appropriate reactions. Expert athletes use kinematic information which they extract from the opponent's movements to anticipate the ball trajectory. Temporal occlusion, where only a part of the full movement sequence is presented, has often been used to research anticipation in sports. Unlike many previous studies, we chose occlusion points in video-stimuli of penalty shooting in handball based on the domain-specific analysis of movement sequences. Instead of relying on randomly chosen occlusion points, each time point in our study revealed a specific chunk of information about the direction of the ball. The multivariate analysis showed that handball goalkeepers were not only more accurate and faster than novices overall when predicting where the ball will end up, but that experts and novices also made their decisions based on different kinds of movement sequences. These findings underline the importance of kinematic knowledge for anticipation, but they also demonstrate the significance of carefully chosen occlusion points.