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Biomechanics And Motor Control Of Human Movement

The aims of this paper are to examine the application of performance indicators in different sports and, using the different structural definitions of games, to make general recommendations about the use and application of these indicators. Formal games are classified into three categories: net and wall games, invasion games, and striking and fielding games. The different types of sports are also sub-categorized by the rules of scoring and ending the respective matches. These classes are analysed further, to enable definition of useful performance indicators and to examine similarities and differences in the analysis of the different categories of game. The indices of performance are sub-categorized into general match indicators, tactical indicators, technical indicators and biomechanical indicators. Different research examples and the accuracy of their presentation are discussed. We conclude that, to enable a full and objective interpretation of the data from the analysis of a performance, comparisons of data are vital. In addition, any analysis of the distribution of actions across the playing surface should also be presented normalized, or non-dimensionalized, to the total distribution of actions across the area. Other normalizations of performance indicators should also be used more widely in conjunction with the accepted forms of data analysis. Finally, we recommend that biomechanists should pay more attention to games to enrich the analysis of performance in these sports.

The use of performance indicators in performance analysis

http://www.psy.vanderbilt.edu/faculty/logan/BandLogan_2003_ActaPsy.pdf

Horse-race model simulations of the stop-signal procedure

Models of response inhibition in the stop-signal and stop-change paradigms

The stop-signal task has been used to study normal cognitive control and clinical dysfunction. Its utility is derived from a race model that accounts for performance and provides an estimate of the time it takes to stop a movement. This model posits a race between go and stop processes with stochastically independent finish times. However, neurophysiological studies demonstrate that the neural correlates of the go and stop processes produce movements through a network of interacting neurons. The juxtaposition of the computational model with the neural data exposes a paradox-how can a network of interacting units produce behavior that appears to be the outcome of an independent race? The authors report how a simple, competitive network can solve this paradox and provide an account of what is measured by stop-signal reaction time.

/pdf/inhibitory-control-in-mind-and-brain-an-interactive-race-59pn1vg0of.pdf

Inhibitory Control in Mind and Brain: An Interactive Race Model of Countermanding Saccades

The existence of structure in sport competition is implicated in the widespread practice of using the information gathered from a past contest to prepare for a future contest. Based on this reasoning, we previously analysed squash match-play for evidence of signature traits from among the stochastic relations between the various types of shot. The mixed findings from these analyses led us to re-analyse squash match-play as a dynamical system. Here, we extend this line of investigation with some suggestions as to how various sports might be described further within this theoretical framework. We offer some examples of dynamical interactions in dyadic (i.e. one vs one) and team (e.g. many vs many) sports, as well as some predictions from a dynamical systems analysis for these types of sports contests. This paper should serve to initiate further research into the complex interactions that occur in sport competition.

Sport competition as a dynamical self-organizing system

In this article, we examine the space-time coordination dynamics of two basketball teams during competition. We identified six game sequences at random, from which the movement data of each player were obtained for analysis of team behaviours in both the longitudinal (basket-to-basket) and lateral (side-to-side) directions. The central position of a team was measured using its spatial (geometric) centre and dispersion using a stretch index, obtained from the mean distance of team members from the spatial centre. Relative-phase analysis of the spatial centres demonstrated in-phase stabilities in both the longitudinal and lateral directions, with more stability in the longitudinal than lateral direction. As anticipated, this finding is consistent with the results of an analysis of individual playing dyads (see companion article, this issue), as well as the more general principle of complex systems conforming to similar descriptions at different levels of analysis. Phase relations for the stretch index demonstrated in-phase attraction in the longitudinal direction and no attraction to any values in the lateral direction. Finally, the difference between the two stretch indexes at any instant showed phase transitions between two stable patterns when the difference was represented in binary form. This result is attributed to the reciprocity between teams in their amounts of expansion and contraction when possession of the ball is won and lost.

Space-time coordination dynamics in basketball: Part 2. The interaction between the two teams.

The scientific analysis of sport performance aims at advancing understanding of game behaviour with a view to improving future outcomes. In this article we outline some scientific issues for perfor...

Applied and theoretical perspectives of performance analysis in sport: Scientific issues and challenges

This article addresses the reliability of performance indicators in game sports. In this context, reliability is invariably treated from a technical point of view as a question of observer agreemen...

On the search for reliable performance indicators in game sports

We examined space–time patterns of basketball players during competition by analysing movement data obtained from six game sequences. Strong in-phase relations in the longitudinal (basket-to-basket) direction were observed for all playing dyads, especially player–opponent dyads matched for playing position, indicating that these movements were very constrained by the game demands. Similar findings for in-phase relations were observed for the most part in the lateral direction, the main exception being dyads comprising the two wing players from the same team. These dyads instead demonstrated strong attractions to anti-phase, a consequence perhaps of seeking to increase and decrease team width in tandem. Single instances from select dyads and game sequences demonstrated further evidence of phase stabilities and phase transitions on some occasions. Together, these findings demonstrate that space–time movement patterns of playing dyads in basketball, while unique, nonetheless conform to a uniform des...

Tim McGarry

Papers

Sport competition as a dynamical self-organizing system

Space-time coordination dynamics in basketball: Part 2. The interaction between the two teams.

Applied and theoretical perspectives of performance analysis in sport: Scientific issues and challenges

On the search for reliable performance indicators in game sports

Space-time coordination dynamics in basketball: Part 1. Intra- and inter-couplings among player dyads.