Observational methodology in sport: performance key elements
Date
2020-11-12Keyword(s)
Performance analysisObservational methodology
Performance indicator
Tactical
Strategic behavior
Abstract
Observational methodology is an inventive approach for performance analysis in sport that has
opened up a new panorama of useful and productive research in recent years (Preciado et al.).
This Research Topic (RT) responds to the need for practitioners to understand athlete and team
performance in individual, dual, and team sports. This RT presents a collection of scientific articles
that use observational methods, enlightening the search for performance indicators in sports,
particularly how the selection and combination of Performance Key Elements (PKE) positively
impact the achievement of the best performances (Brito de Souza et al.; Pérez-Turpin et al.).
Additionally, the analysis of contextual variables, such as opponent level, match location or
match status, provides insights into how PKE perform and consequently, impact success in sport
(Valldecabres et al.).
Preciado et al. present a systematic review that provides evidence of several research lines and
how they have used observational methodologies. As a rigorous and flexible scientific method,
observational research allows for the analysis of spontaneous behavior in a natural context.
Advances in technology and innovations in research methodology have facilitated the processes
of observing, collecting, analyzing, and interpreting data, in loco and real-time during training
sessions and competitions, as well as in post-hoc approaches. Strategies to measure the reliability
and validity of observational instruments mean that we can perceive behaviors in different scales
of performance (Lavega-Burgués et al.). We are now able to use innovative software that reduces
errors and the time spent gathering data (e.g., the AMISCO system, in Fernandez-Navarro et al.),
promoting novel techniques that increase possibilities of analysis (e.g., polar coordinate analysis, in
Prudente et al.; or network analysis, in Praça et al.).