The main focus of this paper was to review the available literature on match analysis in adult male football. The most common research topics were identified, their methodologies described and the evolutionary tendencies of this research area systematised. A systematic review of Institute for Scientific Information (ISI) Web of Knowledge database was performed according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) guidelines. The following keywords were used: football and soccer, each one associated with the terms: match analysis, performance analysis, notational analysis, game analysis, tactical analysis and patterns of play. Of 2732 studies initially identified, only 53 were fully reviewed, and their outcome measures abstracted and analysed. Studies that fit all inclusion criteria were organised according to their research design as descriptive, comparative or predictive. Results showed that 10 studies focused predominantly on a description of technical, tactical and physical performance variables. From all comparative studies, the dependent variables more frequently used were “playing position” and “competitive level”. Even though the literature stresses the importance of developing predictive models of sports performance, only few studies (n = 8) have focused on modelling football performance. Situational variables like game location, quality of opposing teams, match status and match half have been progressively included as object of research, since they seem to work as effective covariables of football performance. Taking into account the limitations of the reviewed studies, future research should provide comprehensive operational definitions for the studied variables, use standardised categories and description of activities and participants, and consider integrating the situational and interactional contexts into the analysis of football performance.

The present paper describes a new multiplatform software application, LINCE, whose versatility makes it ideally suited to the analysis of sports performance. LINCE (see Figure 1) can be used to observe any episode of physical activity or sport since it has been constructed as a software package that automates the functions of: the design of observational systems, video recording, the calculation of data quality and the presentation of results which can be exported in various formats (THEME, GSEQ, EXCEL and SAS). The application overcomes some of the traditional problems faced in relation to the registration and computation of observational data in the field of physical activity and sports sciences.Peer ReviewedPostprint (published version

Mixed methods studies are been increasingly applied to a diversity of fields. In this paper, we discuss the growing use—and enormous potential—of mixed methods research in the field of sport and physical activity. A second aim is to contribute to strengthening the characteristics of mixed methods research by showing how systematic observation offers rigor within a flexible framework that can be applied to a wide range of situations. Observational methodology is characterized by high scientific rigor and flexibility throughout its different stages and allows the objective study of spontaneous behavior in natural settings, with no external influence. Mixed methods researchers need to take bold yet thoughtful decisions regarding both substantive and procedural issues. We present three fundamental and complementary ideas to guide researchers in this respect: we show why studies of sport and physical activity that use a mixed methods research approach should be included in the field of mixed methods research, we highlight the numerous possibilities offered by observational methodology in this field through the transformation of descriptive data into quantifiable code matrices, and we discuss possible solutions for achieving true integration of qualitative and quantitative findings.

Indirect observation is a recent concept in systematic observation. It largely involves analyzing textual material generated either indirectly from transcriptions of audio recordings of verbal behavior in natural settings (e.g., conversation, group discussions) or directly from narratives (e.g., letters of complaint, tweets, forum posts). It may also feature seemingly unobtrusive objects that can provide relevant insights into daily routines. All these materials constitute an extremely rich source of information for studying everyday life, and they are continuously growing with the burgeoning of new technologies for data recording, dissemination, and storage. Narratives are an excellent vehicle for studying everyday life, and quantitization is proposed as a means of integrating qualitative and quantitative elements. However, this analysis requires a structured system that enables researchers to analyze varying forms and sources of information objectively. In this paper, we present a methodological framework detailing the steps and decisions required to quantitatively analyze a set of data that was originally qualitative. We provide guidelines on study dimensions, text segmentation criteria, ad hoc observation instruments, data quality controls, and coding and preparation of text for quantitative analysis. The quality control stage is essential to ensure that the code matrices generated from the qualitative data are reliable. We provide examples of how an indirect observation study can produce data for quantitative analysis and also describe the different software tools available for the various stages of the process. The proposed method is framed within a specific mixed methods approach that involves collecting qualitative data and subsequently transforming these into matrices of codes (not frequencies) for quantitative analysis to detect underlying structures and behavioral patterns. The data collection and quality control procedures fully meet the requirement of flexibility and provide new perspectives on data integration in the study of biopsychosocial aspects in everyday contexts.