“REOFUT” as an Observation Tool for Tactical Analysis on Offensive Performance in Soccer: Mixed Method Perspective

Performance analysis in complex sports like soccer requires the study of the influence of the interaction between both teams during the game on final performance. The mixed methods approach involves the collection, analysis, and interpretation of qualitative and quantitative data for the same purpose and within the framework of the same study. To build certain observation tools, mixed methods are necessary in order to take advantage of integration between qualitative and quantitative elements. The aim of this study was to develop a new no standard observation tool to analyze soccer offensive performance considering not only the observed team but also some aspects of the opponent behavior, as well as to test its reliability. The process consisted in expert meetings and exploratory observations. Experts carried out several design and re-design steps of the observation tool to its final form which includes two macro-criteria and 31 dimensions. The basic unit of analysis was the “team possession” and the main aims of study were: (a) technical, tactical and spatial characteristics of the start, the development and the end of the team possession and its offensive performance, (b) the behavior of the observed team just after losing the ball possession and its defensive performance. Inter-observer and intra-observer analysis were carried out and kappa coefficient was calculated to test the observation tool reliability and improve the quality of data. Results indicate that optimal inter and intra-reliability levels obtained in this work are high enough as for suggesting that the observation tool for offensive performance in soccer (REOFUT) could be an adequate tool for analyzing offensive play actions and their performance in soccer.

Introduction

Researchers have been mixing qualitative and quantitative approaches since the last 20 years (Tashakkori and Teddlie, 1998; Teddlie and Johnson, 2009), but mixed methods research represents “a new movement, or discourse, or research paradigm (with a growing number of members) that has arisen in response to the currents of qualitative research and quantitative research” (Johnson et al., 2007, p. 113). Many researchers do not mix qualitative and quantitative approaches in optimal ways, according to Powell et al. (2008), even when qualitative techniques can be used to enhance the development of quantitative instruments and vice versa (Collins et al., 2006). The mixed methods potential is very broad, and includes instrument fidelity, “maximizing the appropriateness and/or utility of the instruments used, whether quantitative or qualitative” (Onwuegbuzie et al., 2010, p. 57).

The goal of soccer performance analysis is to provide accurate, clear and objective information to players, coaches and clubs to improve future team performance (McGarry, 2009). In this sense, the development of new technological systems [e.g., Global Positional System (GPS), Prozone-STATS, and OPTA] has contributed to increase the quantitative based knowledge in this sport. Notational analysis, which consists of the technique by which the events that take place during the game are recorded (James, 2006) has provided and continues to provide important information for coaches and players, thus helping to improve the training process (Borrie et al., 2002).

However, there is a need to use a new methodological approach based not only on quantitative methods but also on qualitative ones. Indeed, some authors report a growth and proliferation of new methodological approaches to collect and analyze data (Sarmento et al., 2018a). In soccer, there is a need for methods that add qualitative value to performance analysis in order to increase the validity and possible applications of research. This makes necessary the implementation of a mixed methods approach that involves the collection, analysis, and interpretation of qualitative and quantitative data for the same purpose, and within the framework of the same study, on mixed methods (Anguera et al., 2018).

Soccer is a complex and multifactorial sport where the two opponent teams generate an unexpected and changing context at each moment of the game, having a constant adaptation to the characteristics caused by the confrontation between them (Gréhaigne et al., 1997). A large part of recent literature in soccer notational analysis has focused on studying offensive performance indicators such as starting zone, number of passes, duration or type of attack, and their influence on offensive performance (Hughes and Franks, 2005; Tenga et al., 2010; Wright et al., 2011; Lago-Ballesteros et al., 2012; Sarmento et al., 2018b). However, despite the complex and interdependent nature of the game action in soccer, there are still few studies focused on analyzing the effect of the interaction between offensive factors on performance while considering defensive factors of the opponent team and contextual factors (Mackenzie and Cushion, 2013). These same authors and others underline the need to implement research methodologies that show detailed definitions with the aim of facilitating the understanding of results and comparison with other studies (Mackenzie and Cushion, 2013; Sarmento et al., 2018a).

Therefore, according to reviews of the literature in performance analysis (Mackenzie and Cushion, 2013; Sarmento et al., 2014) the future of game analysis in soccer requires the building of observation instruments that integrate the study of criteria related to the interaction with the opponent. In this type of instruments, the use of qualitative attributes where the interpretation of the events by the observers is necessary for the collection of the data, can increase the ability to describe the actions developed in the game (Hughes and Bartlett, 2002).

Some instruments have been proposed to evaluate individual tactical behaviors. González-Villora et al. (2015) review different instruments for the evaluation of the tactical knowledge of football players. All instruments reported there are used to evaluate the tactical knowledge of the soccer player. We would like to highlight the FUT-SAT (Teoldo et al., 2011), which is conceived to assess the tactical knowledge of the player in game situations, both of training and competition.

However, the difficulty of interpreting the team actions in a complex, dynamic and situational context such as a soccer match makes it necessary to correctly define the criteria to limit the errors of interpretation and codification (James et al., 2007), as well as to assess the validity and reliability of the data collected to be analyzed (Hughes et al., 2004).

Therefore, in order to maximize the appropriateness and/or utility of the instruments used, whether quantitative or qualitative, the aim of this work is to describe the process of building and optimizing the development of a qualitative instrument, which will enable to integrate qualitative records with a quantitative analysis. Thus, this work developed a new observation instrument from a mixed method perspective to analyze the offensive collective performance and the tactical characteristics of the action of collective offensive game in soccer, considering the behavior of the opponent team and also contextual dimensions, it also verified the reliability of such instrument, bearing in mind that this methodology is ideal for research on behaviors that occur in soccer (Anguera and Hernández-Mendo, 2013, 2014).

Materials and Methods

Participants

No experimental analysis involving human studies is performed in the study. Six experts were included in this process, who met the following criteria: (1) graduate in physical activity and sport sciences, (2) soccer coach license UEFA A, (3) more than 1 year as a soccer coach in a soccer team of an official competition, (4) postgraduate master in sports sciences or PhD in sports sciences, and (5) experience in performance analysis research (final master’s thesis, doctoral thesis or scientific publication).

The six experts provided written informed consent after details of the study were communicated verbally and in written form prior to participate in the study and it was approved by the Ethics Committee of the University of Barcelona (IRB00003099). In order to carry out the second, third, and fifth stage of the study, in which observation was necessary, a direct, non-participatory, systematic, and natural observational methodology was used (Anguera et al., 2011) (see the “Procedures” section). Matches were recorded from TV broadcasters and were registered and analyzed post-event. Because the video recordings were public, confidentiality was not an issue, and authorization was not required from the players observed or their representatives. Furthermore, the information cannot be considered either personal or intimate, as the research consisted solely of naturalistic observations in public places, and it was not anticipated that the recordings would be used in a manner that could cause personal harm (The American Psychological Association’s [APA’s], 2010).

FIGURE 1

Figure 1. Scheme of the macro-criteria and dimensions that REOFUT record.

Procedures

The design of the research instrument was carried out in five stages:

In the first stage, a literature review on tactical analysis in soccer was carried out in order to know the performance analysis methods used in previous studies. Afterward, the group of experts held an initial meeting where the basic objectives of the instrument were defined, as well as the innovative aspects that were intended to be included. In this sense, it was decided that the main objective of the observation instrument was to analyze the tactical dimensions that could influence the attainment of offensive performance in soccer. Another objective was to study the behavior carried out by a team after losing possession of the ball in play in order to know the tactical behavior in the transition between offensive and the subsequent defensive action. It was decided that the basic unit of study was the “possession” of the team’s ball according to the definition of Pollard and Reep (1997) but also to observe some dimensions of the immediately subsequent possession carried out by the opponent team if the “possession” ends but the game continues. Pollard and Reep (1997) define “possession” as:

“A team possession starts when a player gains possession of the ball by any means other than from a player of the same team. The player must have enough control over the ball to be able to have a deliberate influence on its subsequent direction. The team possession may continue with a series of passes between players of the same team but ends immediately when one of the following events occurs: a) the ball goes out of play; b) the ball touches a player of the opposing team (e.g., by means of a tackle, an intercepted pass or a shot being saved). A momentary touch that does not significantly change the direction of the ball is excluded, or c) the regulation is violated (out of play or foul).”

In the second stage, the design and development of the dimensions and their respective categories were carried out. This stage was characterized by several meetings based on the definition, discussion and re-definition of the dimensions and categories of the instrument separated by individual exploratory observation practices where the experts collected, suggestions or contributions resulting from the application of the preliminary research instrument. All those considerations were discussed in the following meetings in order to re-design the proposed dimensions and categories, or to add new ones that will complete a better analysis. In these observation practices soccer matches of the Spanish national team corresponding to the final phase of the South Africa 2010 FIFA World Cup (Spain-Portugal, Spain-Paraguay and Spain-Holland) were used. The first version of REndimiento Ofensivo en FÙtbol (REOFUT; in English: offensive performance in soccer) ended when each category system met the requirements of completeness and mutual exclusivity (Anguera et al., 2007) and the experts did not consider necessary new dimensions. In this sense, the completeness was considered when any behavior under analysis could be assigned to one of the categories proposed in each dimension while the mutual exclusivity was fulfilled when there was no overlap of the categories and each analyzed behavior was assigned to a single category.

In the third stage, a study was carried out by one of the researchers for the analysis of the offensive game of the Spanish soccer national team in the FIFA World Cup in South Africa 2010, the champion team (852 possessions were analyzed from 7 played matches), using the newly designed first version of REOFUT (González-Ródenas, 2013). The reliability was verified through the analysis of 20 randomly selected possessions of the Spain-Germany match.

In the fourth stage, a series of meetings of the 6 participating experts took place to analyze and discuss the results obtained in the first study in order to verify the usefulness of the criteria and categories of the first REOFUT design. These meetings allowed to eliminate, redesign, redefine criteria, as well as to add other criteria that might be necessary for a better understanding of tactical performance analysis in soccer. As a result of these meetings, the REOFUT was modified from its initial design of 3 macro criteria and 45 dimensions to two macro criteria and 31 dimensions that make up the second version of the instrument. Additionally, several dimensions were redefined as well as categories were grouped or eliminated in order to make the process of data collection and analysis of results more operative and effective.

Finally, once the final design of the instrument was built, the fifth stage was reached where a macro study was carried out in order to analyze the tactical dimensions related to offensive performance, using a sample of Major League Soccer matches. In this macro study, the verification of the reliability of REOFUT took place through the assessment of the agreement between observers (inter-observers) and the analysis of interpretative stability (intra-observer). For the study of the inter-observer agreement, apart from the analysis carried out by the main researcher, a person was trained (Bachelor of Science in Physical Activity and Sport, Master in Research in Sports Science and UEFA A coaching license) during 4 weeks (40 h) in the analysis of the offensive collective game with REOFUT. After the training period, the two observers separately analyzed a game composed of 128 “possession units” of a Major League Soccer professional team in the United States. Regarding the intra-observer agreement, the principal investigator performed the same analysis, 4 weeks after the first analysis, to minimize task familiarity (Robinson and O’Donoghue, 2007), without performing any type of analysis during this time, to check the temporal stability of the analysis performed. To assess the levels of agreement, Kappa correlation coefficients (k) were calculated and analyzed according to the classification by Altman (1991), where the values between 0.8 and 1.0 were considered very good agreement, 0.61–0.80 good, 0.41–0.60 moderate, 0.21–0.40 low and <0.21 very low.

Observational Instrument

The REOFUT observational instrument is a combination of field format and category systems (Anguera et al., 2007). As it is shown in the conceptual approach, the field format allows the appropriate location of the qualitative dimensions. Based on each of these dimensions, when the criteria of having a theoretical framework and timelessness are fulfilled, a system of qualitative categories has been developed. That obeys the double requirement of completeness and mutual exclusivity. In addition, as suggested by Mackenzie and Cushion (2013) and Sarmento et al. (2014) this instrument includes contextual dimensions such as location of the match (home, away, neutral), momentary result (winning, losing, drawing), team and opponent level (high, medium or low depending on their position in the classification) and time of game (first part, second part, extra time).

As it is shown in Figure 1, the REOFUT analyzes two large macro-criteria, the offensive where the observed team has possession of the ball and the defensive only in case the rival team manages to recover the ball in play and initiate a subsequent attack. In this way the REOFUT allows us to study four out of the five important moments of the game according to the classification of Hewitt et al. (2016), such as the offensive transition, the positional attack, the offensive set pieces and the defensive transition. Within the macro offensive criterion, 5 temporary successive moments from each possession are analyzed: start of the possession (Table 1), development of the possession (Table 2), penultimate action of the possession (Table 3), end of the possession and performance outcome (Table 4) and the following possession (Table 5), with the singularity that the moment relative to “penultimate action” will only be studied in the case of the existence of a goal or goal opportunity, with the aim of deepening the analysis of the tactical factors related to the attainment of offensive success. For the defensive macro-criterion, four temporary successive moments of the game action subsequent to the loss of the ball are analyzed, with dimensions relative to the start (Table 1), development (Table 2), final (Table 4), and performance outcome of the opponent subsequent team’s possession (Table 5).

TABLE 1

Table 1. Description and categories for the dimensions related to the start of the possession.

TABLE 2

Table 2. Description and categories for the dimensions related to the possession development.

TABLE 3

Table 3. Description and categories for the dimensions related to the penultimate action of the possession.

TABLE 4

Table 4. Description and categories for the dimensions related to the end of the possession.

TABLE 5

Table 5. Description and categories for the defensive dimensions if the following possession is against.

The REOFUT contains qualitative spatial localization criteria in the different moments of the game. On the one hand, the formal static space is considered where the game rectangle is subdivided into four transversal sectors (defensive, pre-defensive, pre-offensive, and offensive) and four longitudinal lanes (Mombaerts, 2000). In this formal space, an area called “score pentagon” is delimited (Corberán, 2009), which is the selected space from where there is a distance of less than 20 m from the goal and a high shooting angle, factors that are key for the achievement of the goals (Pollard and Reep, 1997; Ensum et al., 2005). From the completion pentagon, different areas are subdivided into zones 13 (13a and b), 14 (14a, b, c, and d), 15 (15a, b, c, and d) and 16 (16a and b) in order to be able to perform a more specific analysis of the categories of goal and goal scoring opportunities (Figure 2).

FIGURE 2

Figure 2. Zones of the field and “score pentagon.” The “score pentagon” is subdivided into different zones in order to perform a more specific analysis of the dimensions related to goals and goal scoring opportunities.

On the other hand, the functional and dynamic concept of space of defensive occupation (SDO) of the rival team is used, which we also call “invasive space” (Figure 3). The SDO is defined by Gréhaigne (2001) as the “space that is constituted by the positions of the players located, at a given moment, in the periphery of a team in play, except the goalkeeper” (positions are showed in Figure 4). The interrelated positions draw a polygonal surface defined as the SDO. The location of the player holding the ball in relation to the SDO of the opposing team during the possession observed has been taken into account based on subdivisions made by previous works (Castellano and Hernández Mendo, 2001; Seabra and Dantas, 2006; Aranda et al., 2009) and 10 categories have been defined in the form of subspaces that show the degree of tactical penetration or invasion of the player in possession of the ball into the SDO drawn by the opposing team at a given time, as well as the situation of that player in the inside or outside of the adversary SDO (Figure 5). The location of the player in possession of the ball in relation to the position of the opponents constitutes a fundamental concept in the definition of many criteria included in the REOFUT (Figure 3).

FIGURE 3

Figure 3. Space of defensive occupation that define the level of invasion over the opponent (Adapted from previous studies, Castellano, 2000; Gréhaigne, 2001; Seabra and Dantas, 2006; Aranda et al., 2009). These zones are dynamic and change every second depending on the positioning on the opposing players.

FIGURE 4

Figure 4. Specific positions within the system of play used by the team in order to determine the player that performs the action. This characterization depends on the system used by each analyzed team.

FIGURE 5

Figure 5. Example of different tactical behaviors related to the penetration over the opponent and their tactical performance.

Recording Instrument

The fifth stage, which was carried out to analyze the tactical dimensions related to offensive performance of Major League matches, was carried out using the recording instrument LINCE (v.1.2.1) (Gabín et al., 2012). Dimensions and categories of REOFUT were coded and the observation of behaviors by the two observers was done using this software.

Statistical Analysis

To assess the inter- and intra-observer concordance of the REOFUT, kappa index Cohen’s (1960) was calculated using SPSS 21.0 for Windows (SPSS, Chicago, IL, United States).

Results

Given the objective of this article, oriented to the construction of an observation instrument, the results refer to the quality control of the data, focused on the intra-observer and inter-observer concordance.

Table 6 shows the Kappa values for each of the dimensions of the observation instrument. We can observe how the values for the intra-observer analysis are higher than those obtained in the inter-observers. In this sense, according to the criterion of Altman (1991) the intra-observer analysis shows how 83.9% of the dimensions present very good reliability (0.81–1.0) and 16.1% good (0.61–0.80). On the other hand, the intra-observer analysis shows how 96.8% of the dimensions present a very high reliability (0.81–1.0) and the remaining 3.2% show a good reliability (0.61–0.80).

TABLE 6

Table 6. Kappa values obtained for the dimensions of the REOFUT observation tool.

Discussion

The central axis of the work has been to present the process of construction of the observation instrument REOFUT, from the qualitative behavior of the soccer team, to the quantitative recording of data, demonstrating that this tool is suitable and consistent for the analysis of offensive possessions in soccer.

First, this study has presented the design process of REOFUT, which aims to provide a greater contextualization of tactical behavior and offensive performance in soccer supported by a broad theoretical framework as claimed by different authors (Mackenzie and Cushion, 2013; Sarmento et al., 2018a). It is remarkable the fact that it incorporates the concept of SDO as well as the position, numerical balance and pressure of the opponent to analyze the interaction between both teams during different phases of the game. In addition, one of the most novel aspects of the REOFUT is to describe in detail the type of technical-tactical actions that can be carried out during the possession, emphasizing its tactical functionality with respect to the opponent rather than its execution, as some recent studies suggested (McLean et al., 2017). Also, the concept of type of progression in attack of the offensive process is used considering previous studies (Tenga et al., 2009; Sarmento et al., 2010; Lago-Ballesteros et al., 2012) and as main novelty, the offensive performance dimension has been defined by four categories that reflect the degree of offensive penetration achieved by the team observed on the opponent during possession (no depth, deep attack, goal scoring opportunity and goal). Therefore, the REOFUT provides a methodological framework of analysis that allows future researchers the possibility of studying globally or specifically different dimensions of the game, such as possessions that originate goals or goals, defensive transitions, as well as the study of game patterns at different times of possession.

The first step is to correctly record and code the data, and this is where the ad hoc observation instrument (REOFUT) is used. The record can be managed and processed systematically within an empirical research setting that ensures replicability. The recorded data can be transformed into a series of complete or incomplete code matrices containing purely qualitative information (Anguera et al., 2017). This transformation is achieved by organizing the dimensions into columns and adding the behavioral units (possessions) to the corresponding rows, ready for quantitative analysis.

Once the necessary data controls (as Kappa coefficient for inter-observers agreement) has been performed, the researcher now has access to a series of code matrices perfectly suited for analysis using different techniques.

Secondly, quality control of the data was carried out through the analysis of agreement according to the proposal of the Kappa index, considered as an appropriate analytical technique to analyze the measure of agreement for categorical data in the analysis of sports performance (Robinson and O’Donoghue, 2007). In this way, it has been observed how the REOFUT dimensions show very good and good levels of reliability in all the dimensions, according to the criteria of Altman (1991). Intra-observer analysis shows better levels of reliability than inter-observers. This fact may be due to the fact that some of the behaviors analyzed require the interpretation by the observers, which may cause discrepancies in the observations in some cases. In this line, James et al. (2007) and Losada and Manolov (2015) argue that the disparity between two observers can be expected especially when the analytical procedure requires considerable skill and experience. In addition, these authors add that factors such as training in the analytical procedure, operational definitions and the nature of the dimensions should be considered in the interpretation of the results. In the present study, high reliability values were obtained with a training period of the observer of 4 weeks and the operational definitions of the analytical procedure were specially specified and studied both theoretically and practically during the exploratory observation phase of the study.

In terms of the nature of dimensions and categories, some observations may naturally be more difficult to perform without errors than others (James et al., 2007). This study has observed how the behaviors in which the interpretation by the observers was more relevant have obtained lower agreement values than the behaviors with lower interpretative demands. For example, the dimensions referred to the location of the initial action, penultimate and last action in the rival invasive space obtained lower values of agreement than the dimensions related to the location of them in the formal game space, both inter-observers (0.800, 0.776, 0.813 vs. 0.958, 0.963, 0.959) as intra-observer (0.862, 0.845, 0.907 vs. 0.947, 0.951, 0.979), respectively. This result must be understood in relation to the fact that the zones of the opponent SDO are changing with the evolution of the game action, which requires more experience for interpretation by the observers, while the formal field zones are invariable and the references on the field help to draw imaginary lines on the playing field that facilitate location.

In relation to similar studies, our results coincide with previous investigations that found how the spatial categorization considering the SDO of the equipment can be a reliable measure for the analysis of the game space in soccer. For example, Seabra and Dantas (2006) divided the SDO into 7 sub-spaces to analyze the finalization space in soccer and showed values between 0.83 and 0.93 for the intra-observer analysis and between 0.73 and 0.90 for the inter-observers, which approximates the values found in the present study. Also, Castellano et al. (2000) created an observational tool to analyze actions and contexts of interaction in soccer considering the actions of the players and their relationship with the positioning of the team itself and rivals, showing satisfactory levels of inter-observer and intra-observer reliability.

On the other hand, the present study presents higher concordance values in comparison with the study carried out by Tenga et al. (2009), who developed an observation instrument for soccer performance analysis with 22 dimensions. It is worth noting that the defensive dimensions presented by Tenga et al. (2009) based on pressure, coverage and positioning of the defenders obtained a very low reliability. In addition, as it occurs with REOFUT, this study showed greater concordance for the intra-observer analysis (73% of the criteria very good, 23% good and 4% moderate) than for the inter-observers (32% very good, 23% good, 32% moderate, 9% reasonable, and 4% poor).

In addition, our study presents lower reliability values with respect to the instrument designed by Sarmento et al. (2010) for the analysis of the offensive process in soccer, which achieved reliability values above 0.95 in all the dimensions studied. This instrument aims to detect temporary patterns at the start, development and end of the offensive sequences and shares with the REOFUT the importance of the dimension related to the type of attack, which was divided into categories such as rapid attack, positional attack and counterattack.

REOFUT shows several limitations. On the one hand, as it is a tool based on notational analysis and therefore on the observation, interpretation and recording of events that take place during the game. It may not reflect the total complexity and criteria that the offensive play actions represent. On the other hand, this instrument is fundamentally based on the study of the offensive moment. Although it consists of numerous criteria to describe the different moments of the action of open offensive play, which consists of different moments such as the beginning, the development, the penultimate action and the end, it is not considered an instrument of ideal observation for the study of offensive set pieces, which are actions that have different technical and tactical characteristics to open game situations. It would be fantastic to have a single and simple tool to analyze all types of action that are in a game, but given the diversity of actions that occur in football, to analyze the tactical behavior of the team with a single instrument appears almost impossible.

Finally, this instrument has important practical applications. Firstly, the REOFUT tool can be used for researchers to analyze, describe, predict and compare collective offensive performance. Secondly, soccer coaches and match analysts of all levels can use the theoretical framework of REOFUT to evaluate and register the offensive performance of their teams throughout the season, analyzing the tactical progress and using this information for adjusting and improving the coaching process.

In conclusion, the optimal inter and intra-reliability levels obtained in this work are high enough as for suggesting that REOFUT could be an adequate tool for analyzing offensive play actions and their performance in soccer.

Author Contributions

RA developed the project, supervised the design of the study, and drafted the manuscript. JG-R was responsible for the review of the literature and the drafting of the manuscript, codified the data, and contributed to the analysis and the method section. IL-B collected and codified the data, and performed the analysis. RA-M was responsible for the analysis, data collection, and data handling. AT-D codified the data. MA revised the content critically. All authors approved the submitted version of the manuscript.

Funding

The authors gratefully acknowledge the support of the two Spanish Government subprojects: Integration ways between qualitative and quantitative data, multiple case development, and synthesis review as main axis for an innovative future in physical activity and sports research (PGC2018-098742-B-C31) (Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema I+D+i), and Mixed method approach on performance analysis (in training and competition) in elite and academy sport (PGC2018-098742-B-C33) (Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Generación de Conocimiento y Fortalecimiento Científico y Tecnológico del Sistema I+D+i), that are part of the coordinated project New approach of research in physical activity and sport from mixed methods perspective (NARPAS_MM) (SPGC201800X098742CV0). The authors also gratefully acknowledge the support of the two Spanish Government projects (Ministerio de Economía y Competitividad): (1) La actividad física y el deporte como potenciadores del estilo de vida saludable: Evaluación del comportamiento deportivo desde metodologías no intrusivas (Grant Nos. DEP2015-66069-P and MINECO/FEDER, UE) and (2) Avances metodológicos y tecnológicos en el estudio observacional del comportamiento deportivo (PSI2015-71947-REDP, MINECO/FEDER, UE). In addition, the authors thank the support of the Generalitat de Catalunya Research Group, GRUP DE RECERCA I INNOVACIÓ EN DISSENYS (GRID). Tecnología i aplicació multimèdia i digital als dissenys observacionals (Grant No. 2017 SGR 1405).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Altman, D. G. (1991). “Some common problems in medical research,” in Practical Statistics for Medical Research, ed. D. G. Altman (London: Chapman y Hall).

Google Scholar

Anguera, M. T., Blanco-Villaseñor, A., Hernández-Mendo, A., and Losada, J. L. (2011). Diseños observacionales: ajuste y aplicación en psicología del deporte [Observational designs: adjust and applications in sports psychology]. Cuad. Psicol. Deporte 11, 63–76.

Google Scholar

Anguera, M. T., Camerino, O., Castañer, M., Sánchez-Algarra, P., and Onwuegbuzie, A. J. (2017). The specificity of observational studies in physical activity and sports sciences: moving forward in mixed methods research and proposals for achieving quantitative and qualitative symmetry. Front. Psychol. 8:2196. doi: 10.3389/fpsyg.2017.02196

PubMed Abstract | CrossRef Full Text | Google Scholar

Anguera, M. T., and Hernández-Mendo, A. (2013). La metodología observacional en el ámbito del deporte [Observational methodology in sport field]. Revista de Ciencias del Deporte 9, 135–160.

Google Scholar

Anguera, M. T., and Hernández-Mendo, A. (2014). Metodología observacional y psicología del deporte. Estado de la cuestión [Observational methodology and sport psychology: the state of the art]. Revista de Psicología del Deporte 23, 103–109. doi: 10.20960/nh.583

PubMed Abstract | CrossRef Full Text | Google Scholar

Anguera, M. T., Magnusson, M. S., and Jonsson, G. K. (2007). Instrumentos no estándar [Non standard instruments]. Avances en Medición 3, 63–82.

Anguera, M. T., Portell, M., Chacón-Moscoso, S., and Sanduvete-Chaves, S. (2018). indirect observation in everyday contexts: concepts and methodological guidelines within a mixed methods framework. Front. Psychol. 9:13. doi: 10.3389/fpsyg.2018.00013

PubMed Abstract | CrossRef Full Text | Google Scholar

Aranda, R., Corberán, C., and Losada, J. L. (2009). Validación de un Instrumento de Registro para Conocer los Espacios a Conquistar en fútbol [Validation of a Recording Instrument to know Target Spaces in Football]. Málaga: X Congreso De Metodología De Ciencias Sociales y De La Salud.

Bangsbo, J., and Peitersen, B. (2000). Soccer Systems and Strategies. Champaign, IL: Human Kinetics.

Google Scholar

Barreira, D., Garganta, J., Guimarães, P., Machado, J., and Anguera, M. T. (2014). Ball recovery patterns as a performance indicator in elite soccer. J. Sports Eng. Technol. 228, 61–72. doi: 10.1177/1754337113493083

CrossRef Full Text | Google Scholar

Borrie, A., Jonsson, G. K., and Magnusson, M. S. (2002). Temporal pattern analysis and its applicability in sport: an explanation and exemplar data. J. Sports Sci. 20, 845–852. doi: 10.1080/026404102320675675

PubMed Abstract | CrossRef Full Text | Google Scholar

Castellano, J. (2000). Observación y análisis de la acción de juego en el fútbol [Observation and analysis of game action in football]. Ph. D thesis, Universidad del País Vasco, Vitoria.

Castellano, J., and Hernández Mendo, A. (2001). La observación de la acción de juego en fútbol. Contextualización de los acontecimientos [Game action observation in football. Events contextualization]. El Entrenador Español 90, 15–20.

Google Scholar

Castellano, J., Hernández-Mendo, A., Gómez, de Segura, P., Fontetxa, E., and Bueno, I. (2000). Sistema de codificación y análisis de calidad del dato en el futbol de rendimiento [Codification system and data quality analysis in top level soccer]. Psicothema 12, 635–641.

Google Scholar

Cohen, J. (1960). A coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20, 37–46. doi: 10.1177/001316446002000104

CrossRef Full Text | Google Scholar

Collins, K. M. T., Onwuegbuzie, A. J., and Sutton, I. L. (2006). A model incorporating the rationale and purpose for conducting mixed methods research in special education and beyond. Learn. Disabil. 4, 67–100.

Google Scholar

Corberán, C. (2009). Validación de un Instrumento de Observación para el Análisis Funcional del espacio que precede a la ocasión de gol en fútbol [Validation of an observation instrument for the analysis of the functional space that precedes goal scoring opportunity in football]. Master thesis, Universidad de Valencia, Valencia.

Ensum, J., Pollard, R., and Taylor, S. (2005). “Applications of logistic regression to shots at goal in association football,” in Science and Football V, eds T. Reilly, J. Cabri, and D. Araújo (London: Routledge), 211–2018.

Google Scholar

Gabín, B., Camerino, O., Anguera, M. T., and Castañer, M. (2012). Lince: multiplatform sport analysis software. Proc. Soc. Behav. Sci. 46, 4692–4694. doi: 10.1016/j.sbspro.2012.06.320

CrossRef Full Text | Google Scholar

Gómez, M. A., Gómez-Lopez, M., Lago, C., and Sampaio, J. (2012). Effects of game location and final outcome on game related statistics in each zone of the pitch in professional football. Eur. J. Sport Sci. 12, 393–398. doi: 10.1080/17461391.2011.566373

CrossRef Full Text | Google Scholar

González-Ródenas, J. (2013). Análisis del Rendimiento táctico en el juego colectivo ofensivo en fútbol en la copa del mundo 2010 [Analysis of the Tactical Performance on the Offensive Collective Play in the World Cup 2010]. Unpublished doctoral dissertation, Universidad de Valencia,Valencia, Spain.

González-Villora, S., Serra-Olivares, J., Pastor-Vicedo, J. C., and Teoldo da Costa, I. (2015). Review of the tactical evaluation tools for youth players, assessing the tactics in team sports: football. SpringerPlus 4, 663–680. doi: 10.1186/s40064-015-1462-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Gréhaigne, J. (2001). La organización del juego en el fútbol [Game Organization in Football], 1st Edn. Barcelona: INDE.

Gréhaigne, J., Bouthier, D., and David, B. (1997). Dynamic-system analysis of opponent relationships in collective actions in soccer. J. Sports Sci. 15, 137–149. doi: 10.1080/026404197367416

PubMed Abstract | CrossRef Full Text | Google Scholar

Hewitt, A., Greenham, G., and Norton, K. (2016). Game style in soccer: what is it and can we quantify it? Int. J. Perform. Anal. Sport 16, 355–372. doi: 10.1080/24748668.2016.11868892

PubMed Abstract | CrossRef Full Text | Google Scholar

Hughes, M., Cooper, S. M., and Nevill, A. (2004). “Analysis of notation data – reliability,” in Notational Analysis of Sport, eds M. Hughes and I. M. Franks (London: Routledge), 189–204.

Google Scholar

Hughes, M., and Franks, I. (2005). Analysis of passing sequences, shots and goals in soccer. J. Sports Sci. 23, 509–514. doi: 10.1080/02640410410001716779

PubMed Abstract | CrossRef Full Text | Google Scholar

Hughes, M. D., and Bartlett, R. M. (2002). The use of performance indicators in performance analysis. J. Sports Sci. 20, 739–754.

Google Scholar

James, N. (2006). Notational analysis in soccer: past, present and future. Int. J. Perform. Anal. Sport 6, 67–81. doi: 10.1080/24748668.2006.11868373

CrossRef Full Text | Google Scholar

James, N., Taylor, J., and Stanley, S. (2007). Reliability procedures for categorical data in performance analysis. Int. J. Perform. Anal. Sport 7, 1–11. doi: 10.1080/24748668.2007.11868382

CrossRef Full Text | Google Scholar

Johnson, R. B., Onwuegbuzie, A. J., and Turner, L. A. (2007). Toward a definition of mixed methods research. J. Mixed Methods Res. 1, 112–133. doi: 10.1177/1558689806298224

CrossRef Full Text | Google Scholar

Lago-Ballesteros, J., Lago, C., and Rey, E. (2012). The effect of playing tactics and situational variables on achieving score-box possessions in a professional soccer team. J. Sports Sci. 30, 1455–1461. doi: 10.1080/02640414.2012.712715

PubMed Abstract | CrossRef Full Text | Google Scholar

Losada, J. L., and Manolov, R. (2015). The process of basic training, applied training, maintaining the performance of an observer. Qual. Quant. 49, 339–347. doi: 10.1007/s11135-014-9989-7

CrossRef Full Text | Google Scholar

Mackenzie, R., and Cushion, C. (2013). Performance analysis in football: a critical review and implications for future research. J. Sport Sci. 31, 639–676. doi: 10.1080/02640414.2012.746720

PubMed Abstract | CrossRef Full Text | Google Scholar

McGarry, T. (2009). Applied and theoretical perspectives of performance analysis in sport: scientific issues and Challenges. Int. J. Perform. Anal. Sport 9, 128–140. doi: 10.1080/24748668.2009.11868469

CrossRef Full Text | Google Scholar

McLean, S., Salmon, P. M., Gorman, A. D., Read, G. J. M., and Solomon, C. (2017). What’s in a game? A systems approach to enhancing performance analysis in football. PLoS One 12:e0172565. doi: 10.1371/journal.pone.0172565

PubMed Abstract | CrossRef Full Text | Google Scholar

Mombaerts, E. (2000). Fútbol: Del análisis del juego a la formación del jugador [Football: From Game Analysis to Player Formation], 1st Edn. Barcelona: INDE Publicaciones.

Onwuegbuzie, A. J., Bustamante, R. M., and Nelson, J. A. (2010). Mixed research as a tool for developing quantitative instruments. J. Mixed Methods Res. 4, 56–78. doi: 10.1177/1558689809355805

CrossRef Full Text | Google Scholar

Pollard, R., and Reep, C. (1997). Measuring the effectiveness of playing strategies at soccer. J. R. Stat. Soc. 46, 541–550. doi: 10.1111/1467-9884.00108

CrossRef Full Text | Google Scholar

Powell, H., Mihalas, S., Onwuegbuzie, A. J., Suldo, S., and Daley, C. E. (2008). Mixed methods research in school psychology: a mixed methods investigation of trends in the literature. Psychol. Sch. 45, 291–309. doi: 10.1002/pits.20296

CrossRef Full Text | Google Scholar

Robinson, G., and O’Donoghue, P. (2007). A weighted Kappa statistic for reliability testing in performance analysis of sport. Int. J. Perform. Anal. Sport 7, 12–19. doi: 10.1080/24748668.2007.11868383

CrossRef Full Text | Google Scholar

Sarmento, H., Anguera, M. T., Campaniço, J., and Leito, J. (2010). Development and validation of a notational system to study the offensive process in football. Medicina 46, 401–407.

PubMed Abstract | Google Scholar

Sarmento, H., Clemente, F. M., Araújo, D., Davids, K., McRobert, A., and Figueiredo, A. (2018a). What performance analysts need to know about research trends in association football (2012–2016): a systematic review. Sports Med. 48, 799–836. doi: 10.1007/s40279-017-0836-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Sarmento, H., Figueiredo, A., Lago-Peñas, C., Milanovic, Z., Barbosa, A., Tadeu, P., et al. (2018b). The influence of tactical and situational variables on offensive sequences during elite football matches. J. Strength Cond. Res. 32, 2331–2339. doi: 10.1519/JSC.0000000000002147

PubMed Abstract | CrossRef Full Text | Google Scholar

Sarmento, H., Marcelino, R., Anguera, M. T., Campaniço, J., Matos, N., and Leitão, J. C. (2014). Match analysis in football: a systematic review. J. Sports Sci. 32, 1831–1843. doi: 10.1080/02640414.2014.898852

PubMed Abstract | CrossRef Full Text | Google Scholar

Seabra, F., and Dantas, L. (2006). Space definition for match analysis in soccer. Int. J. Perform. Anal. Sport 6, 97–113. doi: 10.1080/24748668.2006.11868376

CrossRef Full Text | Google Scholar

Tashakkori, A., and Teddlie, C. (1998). Mixed Methodology: Combining Qualitative and Quantitative Approaches. Applied Social Research Methods Series, Vol. 46. Thousand Oaks, CA: Sage.

Google Scholar

Teddlie, C., and Johnson, R. B. (2009). “Methodological thought since the 20th century,” in Foundations of Mixed Methods Research: Integrating Quantitative and Qualitative Techniques in the Social and Behavioral Sciences, eds C. Teddlie and A. Tashakkori (Thousand Oaks, CA: Sage), 62–82.

Google Scholar

Tenga, A., Holme, I., Ronglan, L. T., and Bahr, R. (2010). Effect of playing tactics on achieving score-box possessions in a random series of team possessions from Norwegian professional soccer matches. J. Sports Sci. 28, 245–255. doi: 10.1080/02640410903502766

PubMed Abstract | CrossRef Full Text | Google Scholar

Tenga, A., Kanstad, D., Ronglan, L. T., and Bahr, R. (2009). Developing a new method for team match performance analysis in professional soccer and testing its reliability. Int. J. Perform. Anal. Sport 9, 8–25. doi: 10.1080/24748668.2009.11868461

CrossRef Full Text | Google Scholar

Teoldo, I., Garganta, J., Greco, P. J., Mesquita, I., and Maia, J. (2011). Sistema de avaliação táctica no futebol (FUT-SAT): desenvolvimento e validação preliminar. Motricidade 7, 69–84.

The American Psychological Association’s [APA’s] (2010). Ethical Principles of Psychologists and Code of Conduct. Washington, DC: The American Psychological Association’s.

Google Scholar

Wright, C., Atkins, S., Polman, R., Jones, B., and Lee, S. (2011). Factors associated with goals and goal scoring opportunities in professional soccer. Int. J. Perform. Anal. Sport 11, 438–444.

Google Scholar