Variability of inter-team distances associated with match events in elite-standard soccer

Interpersonal Coordination between Female Soccer Players: Leader-Follower Roles within a Collision-Avoidance Task

Background/Purpose

Return to sport decision-making may be improved by assessing an athlete's ability to coordinate movement with opponents in sport. The purpose was to investigate whether previous injuries associated with female soccer players' interpersonal coordination during a collision avoidance task. The authors hypothesized that external perturbations would disrupt the strength and stability of coordinated movement, and that individuals with a history of injury would be less likely to recover coordinated movement.

Study Design

Cross-Sectional.

Methods

Nine female athletes with a history of lower extremity injuries and nine without injuries were paired into dyads. Each dyad completed twenty trials of an externally paced collision-avoidance agility task with an unanticipated perturbation. Participant trajectories were digitized and analyzed using cross-recurrence quantification analysis (CRQA) to determine the strength and stability of interpersonal coordination dynamics. Trials in which participants with injury history assumed leader or follower roles within each dyad were then used to study how dyadic coordination varied across task stages (early, perturbation, and late) using linear mixed effect models. Cohen's d effect sizes were calculated to demonstrate magnitude of differences. In exploratory analysis, psychological readiness (i.e., self-reported knee functioning, fear of injury, and risk-taking propensity) was evaluated for their association with leader-follower status.

Results

Perturbation disrupted the strength (R2=0.65, p<0.001, early=49.7±1.7, perturbation=41.1±1.7, d=0.39) and stability (R2=0.71, p < 0.001, early=65.0±1.6, perturbation=58.0±1.7, d=0.38) of interpersonal coordination regardless of leader-follower status. Individuals with injury history failed to restore coordination after the perturbation compared to control participants (injury=44.2.0±2.1, control=50.8±2.6, d=0.39). Neither demographic nor psychological measures were associated with leader-follower roles (B=0.039, p=0.224).

Conclusion

Individuals with a history of lower extremity injury may have a diminished ability to adapt interpersonal coordination to perturbations, possibly contributing to a higher risk of re-injury.

Level of Evidence

3.

The keys of pressing to gain the ball - Characteristics of defensive pressure in elite soccer using tracking data

Recently, the availability of big amounts of data enables analysts to dive deeper into the constraints of performance in various team sports. While offensive analyses in football have been extensively conducted, the evaluation of defensive performance is underrepresented in this sport. Hence, the aim of this study was to analyze successful defensive playing phases by investigating the space and time characteristics of defensive pressure.Therefore, tracking and event data of 153 games of the German Bundesliga (second half of 2020/21 season) were assessed. Defensive pressure was measured in the last 10 seconds of a defensive playing sequence (time characteristic) and it was distinguished between pressure on the ball-carrier, pressure on the group (5 attackers closest to the ball), and pressure on the whole team (space characteristic). A linear mixed model was applied to evaluate the effect of success of a defensive play (ball gain), space characteristic, and time characteristic on defensive pressure.Defensive pressure is higher in successful defensive plays (14.47 ± 16.82[%]) compared to unsuccessful defensive plays (12.87 ± 15.31[%]). The characteristics show that defensive pressure is higher in areas closer to the ball (space characteristic) and the closer the measurement is to the end of a defensive play (time characteristic), which is especially true for successful defensive plays. Defensive pressure is a valuable key performance indicator for defensive play. Further, this study shows that there is an association between the pressing of the ball-carrier and areas close to the ball with the success of defensive play.

Investigating the Emergence of Collective States Within Rugby Sevens Gameplay

Rugby sevens is a small-sided variant of rugby union characterised by fast-moving, high-intensity gameplay and is an example of a team invasion sport, where players work together to achieve a shared goal of attacking and defending as a cohesive unit. The dynamics of such sports can be viewed as self-organizing systems, where individual players form collective patterns without a centralized mechanism of control. Inspired by the analysis of collective movement in animals, this novel study investigates the emergent patterns of order and disorder in sub-elite female rugby sevens using order parameters (typically used to analyse particle systems) to characterize the team's collective state during different phases of play. The findings demonstrate that defensive gameplay is more ordered, with more compact formations, compared to attacking play, and there is a correlation between alignment/order in player motion and group speed. The work further suggests that the collective states formed differ between sequences of play with different levels of ground gained by the attacking team. These observations provide a sound justification for player training with a focus on cohesive defensive movements to resist disruptions from opposing attackers, while employing attacking tactics that disrupt the cohesion and order of opposing teams.

Team Behavior and Performance: An Exploration in the Context of Professional Rugby Union

PURPOSE

To explore complex system behavior and subsequent team performance in professional rugby union.

METHODS

Here, we present 2 studies. In the first, we used global positioning system technology to measure player clustering during stoppages in play in nearly 100 games of professional rugby union to explore team (complex system) behavior and performance. In the second, we measured stress hormones (cortisol and testosterone) prior to team meetings and analyzed these relative to amount of time and the frequency with which players looked at peer presenters, as well as subsequent training performance, to explain how stress may lead to behaviors observed in the first study and subsequent match performance.

RESULTS

No link between player clustering during stoppages of play and performance was observed. When players (complex system agents) demonstrated greater levels of stress (as indicated by greater cortisol-awakening response and a greater decline in testosterone-to-cortisol ratio across the morning), they tended to look at peer presenters more; however, training quality declined (P = .02). Correlational analysis also showed that training quality was related to testosterone-to-cortisol ratio (P = .04).

CONCLUSIONS

Team behavior is complex and can be unpredictable. It is possible that under stress, complex system agents (ie, rugby union players) look at (and cluster toward) their teammates more; however, meaningful interaction may not necessarily occur. Furthermore, while complex system (team) analysis may be valuable strategically in rugby union in the context of describing behavior, without understanding "how" or "why" intrateam/interagent behaviors emerge it may have little meaning.

Integrating physical and tactical factors in football using positional data: a systematic review

Background

Positional data have been used to capture physical and tactical factors in football, however current research is now looking to apply spatiotemporal parameters from an integrative perspective. Thus, the aim of this article was to systematically review the published articles that integrate physical and tactical variables in football using positional data.

Methods and Materials

Following the Preferred Reporting Item for Systematic Reviews and Meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to August 2021. The methodological quality of the studies was evaluated using the modified Downs and Black Quality Index (observational and cross-sectional studies) and the Physiotherapy Evidence Database (PEDro) scale (intervention studies).

Results

The literature search returned 982 articles (WoS = 495; PubMed = 232 and SportDiscus = 255). After screening, 26 full-text articles met the inclusion criteria and data extraction was conducted. All studies considered the integration of physical and tactical variables in football using positional data (n = 26). Other dimensions were also reported, such as psychophysiological and technical factors, however the results of these approaches were not the focus of the analysis (n = 5). Quasi-experimental approaches considered training sets (n = 20) and match contexts (n = 6). One study analysed both training and play insights. Small sided-games (SSG) were the most common training task formats in the reviewed studies, with only three articles addressing medium-sided (MSG) (n = 1) and large-sided games (LSG) (n = 2), respectively.

Conclusions

Among the current systematic review, the physical data can be integrated by player's movement speed. Positional datasets can be computed by spatial movement, complex indexes, playing areas, intra-team and inter-team dyads. Futures researches should consider applying positional data in women's football environments and explore the representativeness of the MSG and LSG.

Reliability of spatial-temporal metrics used to assess collective behaviours in football: An in-silico experiment

The purpose of this study was to investigate the reliability of spatial-temporal measurements applied within collective behaviour research in football. In-silico experiments were conducted introducing positional errors (0.5, 2 and 4 m) representative of commercial tracking systems to match data from the 2020 European Championship qualifiers. Ratios of the natural variance ("signal") of spatial-temporal metrics obtained throughout sections of each game relative to the variance created by positional errors ("noise") were taken to calculate reliability. The effects of error magnitude and time of analysis (1, 5 and 15 mins; length of attack: <10, 10-20, >20 s) were assessed and compared using Cohen's f² effect size. Error magnitude was found to exert greater influence on reliability (f² = 0.15 to 0.81) compared with both standard time of analysis (f² = 0.03 to 0.08) and length of attacks (f² = 0.15 to 0.32). the results demonstrate that technologies generating positional errors of 0.5 m or less should be expected to produce spatial-temporal metrics with high reliability. However, technologies that generate errors of 2 m or greater may produce unreliable values, particularly when analyses are conducted over discrete events such as attacks, which although critical, are often short in duration.

Qualitative Team Formation Analysis in Football: A Case Study of the 2018 FIFA World Cup

In this paper, we explore the use of the Static Qualitative Trajectory Calculus (QTC_S), a qualitative spatiotemporal method based on the QTC, for the analysis of team formations in football. While methods for team formation analysis in sports are predominantly quantitative in nature, QTC_S enables the comparison of team formations by describing the relative positions between players in a qualitative manner, which is more related to the way players position themselves on the field. QTC_S has the potential to allow to monitor to what extent a football team plays according to a coach’s predetermined formation. When applied to multiple matches of one team, the method can contribute to the definition of the playing style of a team. We present an experiment aimed at identifying the team formation played by Belgian national football team during the 2018 FIFA World Cup held in France.

Social Network Analysis: Mathematical Models for Understanding Professional Football in Game Critical Moments—An Exploratory Study

Considering the Social Network Analysis approach and based on the creation of mathematical models, the aim of this study is to analyze the players’ interactions of professional football teams in critical moments of the game. The sample consists in the analysis of a 2019/2020 season UEFA Champions League match. The mathematical models adopted in the analysis of the players (micro analysis) and the game (macro analysis) were obtained through the uPATO software. The results of the networks indicated a performance pattern trend more robust in terms of the mathematical model: Network Density. As far as it concerned, we found that the Centroid Players had a decisive role in the level of connectivity and interaction of the team. Regarding the main critical moments of the game, the results showed that these were preceded by periods of great instability, obtaining a differentiated performance in the following mathematical models: Centrality, Degree Centrality, Closeness Centrality, and Degree Prestige. We concluded that the networks approach, in concomitance with the dynamic properties of mathematical models, and the critical moments of the game, can help coaches to better evaluate the level of interaction and connectivity of their players toward the actions imposed by opponents.

Amplifying the effects of adding extra players during association football game-based scenarios

This study aimed to compare under-18 association football players’ performance (age = 17.7±1.0 years; playing experience = 9.0 ± 3.2 years) when manipulating the number of teammates and opponents during football game-based practices. Time-motion, individual and tactical-related variables were monitored when manipulating conditions with different number of teammates and opponents (11vs11, No-Sup, No-Inf; 11vs12, Low-Sup, Low-Inf; 11vs13, Mod-Sup, Mod-Inf; and 11vs14, High-Sup, High-Inf). Results showed that adding teammates promoted increases in the longitudinal synchronization from No-Sup to Mod-Sup (Cohen’s d with 95% of confidence intervals: 0.25 [0.12; 0.39]; p < .001) and High-Sup (0.61 [0.41; 0.82]; p < .001), while decreases in the distance to the nearest teammate, both in the offensive and defensive phases (p < .001 and p = .005, respectively). In addition, it was observed lower distance covered while running when playing in High-Sup compared to No-Sup (0.30 [-0.01; 0.61]; p = .002) during the defensive phase. Attacking in numerical inferiority promoted a higher variability in the distance to the nearest teammate from No-Inf to High-Inf (0.83 [0.27; 1.38]; p = .044), while decreasing the physical demands, specifically distance covered while running (-0.49 [-0.99; 0.01]; p = .039). In turn, defending, mainly in high-inferiority, increased the total distance covered compared to No-Inf (0.61 [0.30; 0.91]; p < .001) and led to a decrease in the distance to the nearest teammate (-0.90 [-1.35; -0.44]; p = .002). Overall, coaches may manipulate the number of teammates and opponents to promote distinct effects at the level of cooperation and opposition dynamical interactions.

Graph representations for the analysis of multi-agent spatiotemporal sports data

Analyzing tactical patterns in invasion games using multi-agent spatiotemporal data is a challenging task at the intersection of computer and sports science. A fundamental yet understudied problem in this area is finding an optimal data representation for processing athlete trajectories using machine learning algorithms. In the present work, we address this gap by discussing common representations in use and propose Tactical Graphs, an alternative graph-based format capable of producing integrative, contextualized models for machine learning applications. We provide an in-depth, domain-specific motivation of the proposed data representation scheme and show how this approach exploits inherent data traits. We propose Tactical Graph Networks (TGNets), a light-weight, hybrid machine learning architecture sensitive to player interactions. Our method is evaluated with an extensive ablation study and the first comprehensive state of the art comparison between standard feature, state vector, and image-based methods on the same dataset. Experiments were conducted using real-world football data containing short sequences of defensive play labelled according to the outcome of ball winning attempts. The results indicate that TGNets are on par with state-of-the-art deep learning models while exhibiting only a fraction of their complexity. We further demonstrate that selecting the right data representation is crucial as it has a significant influence on model performance. The theoretical findings and the proposed method provide insights and a strong methodological alternative for all classification, prediction or pattern recognition applications in the areas of collective movement analysis, automated match analysis, and performance analysis.

The Effect of Substitutions on Team Tactical Behavior in Professional Soccer

Player substitutions are one of the main options for the coach to change tactical behavior of his team. Purpose: The present study therefore investigates the effect of player substitutions on tactical behavior in high-performance soccer using positional data. Method: The sample consisted of 659 substitutions from 234 matches played in the German Bundesliga during the season 2016-2017. Substitutions were classified either as neutral (n = 485), defensive (n = 45), or offensive (n = 129) according to the player's roles. The teams' tactical behavior before and after each substitution was analyzed using team centroid, inter-team centroid distance, team length and width, length per width (LpW) ratio, stretch index, and space control for the whole pitch and for each third as the dependent variables. Results: The linear mixed model analysis showed different effects for neutral, defensive, and offensive substitutions. Teams displayed significantly lower stretch index after defensive substitutions. LpW ratio increased with neutral and offensive substitutions, while inter-team distance decreased. The position of the team centroid, space control in the middle third and in the attacking third were also greater following an offensive substitution. Conclusions: These findings demonstrate that player substitutions effectively change tactical behavior of teams. Soccer coaches should perform more offensive substitutions to elicit a higher defensive pressure and improve goal-scoring opportunities, especially due to greater space control in the attacking third. In contrast, defensive substitutions can be used to increase defensive effectiveness through increases in team compactness.

Reference values for collective tactical behaviours based on positional data in professional football matches: a systematic review

Match collective tactical behaviours can be used as a reference to design and select training strategies to improve individual and team performance in professional football. The aim of the systematic review was to cluster the collective tactical variables used to highlight and compare male soccer teams’ collective behaviour during professional official matches, providing reference values for each of them. A systematic review of relevant articles was carried out using three electronic databases (PubMed, SPORTdiscus and Web of Science). From a total of 1,187 studies initially found, 13 original articles were included in the qualitative synthesis. The articles found concerned studies carried out on the Spanish, Portuguese, English and Brazilian 1^st divisions and during the European UEFA Champions League. The team length and width ranged from 31 to 46 m and from 35 to 48 m, respectively. The distance from a defending team’s goalkeeper to the nearest teammate ranged from 9 ± 6 to 30 ± 7 m, the goal line-recovery location from 27 to 37 m, and the opponent’s goal line from 42 to 50 m. The stretch index ranged from 7 to 16 m. Mean team area was ~900 m² and the area of the pitch which included all outfield players divided by the 20 outfield players ranged from 79 ± 15 to 94 ± 16 m². All studies provided greater distance and area values during the team-possession phase in comparison to the non-possession one. The ball location on the pitch determined the collective tactical behaviour of the teams. The differences between halves in the distance and area values were contradictory. Further studies should assess the effect of the interaction between the contextual factors on the collective tactical behaviour to obtain more accurate references. This could help football coaches in the design of suitable training tasks to optimize tactical performance.

Defending in 4-4-2 or 5-3-2 formation? small differences in footballers' collective tactical behaviours

This study explored footballers' tactical behaviours, based on their position data, as an effect of two defending formations, 4-4-2 and 5-3-2, using an experimental approach. Sixty-nine youth footballers participated in this 11-versus-11 study, performing 72 trials of attack-versus-defence. Players' position data were tracked using a local positioning system, and processed to calculate measures of collective movement. This was supplemented by the analysis of passing networks. The results showed small differences between the two conditions. Compared to a 4-4-2 formation, defending in 5-3-2 reduced dispersion (-0.69 m,p=0.012), midfield-forward distance (-0.81 m, p=0.047), and defence-forward distance (-1.29 m, p=0.038); the consequent effects on attacking teams included reduced team widths (-1.78 m, p=0.034), reduced necessity for back-passes to the goalkeeper, and less connectivity in the passing network. The effects of the two defending formations seem to have the greatest impact on fullbacks of the attacking teams, since they were main contributors of the reduced team widths, received more passes, and had higher betweenness centrality in the right-back position during 5-3-2 defending. In summary, the present study potentially demonstrates how the underlying mechanisms in players' collective movements and passing behaviours show that the 5-3-2 is more conservatively defensive than the 4-4-2.

Team numerical advantage in Australian rules football: A missing piece of the scoring puzzle?

The primary aim of this study was to determine the relationship between a team numerical advantage during structured phases of play and match event outcomes in professional Australian football. The secondary aim was to quantify how players occupy different sub-areas of the playing field in match play, while accounting for match phase and ball location. Spatiotemporal player tracking data and play-by-play event data from professional players and teams were collected from the 2019 Australian Football League season played at a single stadium. Logistic regression analysed the relationship between total players and team numerical advantage during clearances and inside 50's. Total players and team numerical advantage were also quantified continuously throughout a match, which were separated into three match phases (offence, defence, and stoppage) and four field positions (defensive 50, defensive midfield, attacking midfield, and forward 50). Results identified an increased team numerical advantage produced a greater likelihood of gaining possession from clearances or generating a score from inside 50's. Although, an increased number of total players inside 50 was likely associated with a concomitant decrease in the probability of scoring, irrespective of a team numerical advantage. Teams were largely outnumbered when the ball was in their forward 50 but attained a numerical advantage when the ball was in the defensive 50.

The porous high-press? An experimental approach investigating tactical behaviours from two pressing strategies in football

The aim of this study was to analyse footballers' tactical behaviours from their position data, as an effect of two contrasting pressing strategies, high-press defending and deep-defending, using a trial-based experimental approach. Sixty-nine youth footballers participated in this 11 versus 11 study, performing 72 trials of attack versus defence, in a counterbalanced crossover study design. Players' position data were captured using a local positioning system, and processed to calculate measures of inter-team distance, trial duration, distance to nearest opponent, dispersion, team length, team width, team shape, space control gain, inter-line distance, and individual area. This was augmented by the notational analyses of passes. The findings showed that using a high-press defending strategy leads to: closer inter-team distance; larger dispersion, due to a longer team length; and larger inter-line distances between defenders, midfielders, and forwards. The resulting effects on the attacking team include reduced ball possession time; larger individual areas for attacking midfielders and forwards; longer team length; and more penetrative passes performed. Some differences in marking behaviour were also observed. Consequently, the study recommends that high-press defending be used sparingly due to these trade-offs.

The tactics of successful attacks in professional association football: large-scale spatiotemporal analysis of dynamic subgroups using position tracking data

Association football teams can be considered complex dynamical systems of individuals grouped in subgroups (defenders, midfielders and attackers), coordinating their behaviour to achieve a shared goal. As research often focusses on collective behaviour, or on static subgroups, the current study aims to analyse spatiotemporal behaviour of dynamic subgroups in relation to successful attacks. We collected position tracking data of 118 Dutch Eredivisie matches, containing 12424 attacks. Attacks were classified as successful (N = 1237) or non-successful (N = 11187) based on the potential of creating a scoring opportunity. Using unsupervised machine learning, we automatically identified dynamic formations based on position tracking data, and identified dynamic subgroups for every timeframe in a match. We then compared the subgroup centroids to assess the intra- and inter-team spatiotemporal synchronisation during successful and non-successful attacks, using circular statistics. Our results indicated subgroup-level variables provided more information, and were more sensitive to disruption, in comparison to team-level variables. When comparing successful and non-successful attacks, we found decreases (p < .01) in longitudinal inter- and intra-team synchrony of interactions involving the defenders of the attacking team during successful attacks. This study provides the first large-scale dynamic subgroup analysis and reveals additional insights to team-level analyses.

Linking Tensegrity to Sports Team Collective Behaviors: Towards the Group-Tensegrity Hypothesis

Collective behaviors in sports teams emerge from the coordination between players formed from their perception of shared affordances. Recent studies based on the theoretical framework of ecological dynamics reported new analytical tools to capture collective behavior variables that describe team synergies. Here, we introduce a novel hypothesis based on the principles of tensegrity to describe collective behavior. Tensegrity principles operate in the human body at different size scales, from molecular to organism levels, in structures connected physically (biotensegrity). Thus, we propose that a group of individuals connected by information can exhibit synergies based on the same principles (group-tensegrity), and we provide an empirical example based on the dynamics of a volleyball team sub-phase of defense.

Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review

In professional soccer, increasing amounts of data are collected that harness great potential when it comes to analysing tactical behaviour. Unlocking this potential is difficult as big data challenges the data management and analytics methods commonly employed in sports. By joining forces with computer science, solutions to these challenges could be achieved, helping sports science to find new insights, as is happening in other scientific domains. We aim to bring multiple domains together in the context of analysing tactical behaviour in soccer using position tracking data. A systematic literature search for studies employing position tracking data to study tactical behaviour in soccer was conducted in seven electronic databases, resulting in 2338 identified studies and finally the inclusion of 73 papers. Each domain clearly contributes to the analysis of tactical behaviour, albeit in - sometimes radically - different ways. Accordingly, we present a multidisciplinary framework where each domain's contributions to feature construction, modelling and interpretation can be situated. We discuss a set of key challenges concerning the data analytics process, specifically feature construction, spatial and temporal aggregation. Moreover, we discuss how these challenges could be resolved through multidisciplinary collaboration, which is pivotal in unlocking the potential of position tracking data in sports analytics.

Analysis of the Variability of the Game Space in High Performance Football: Implementation of the Generalizability Theory

The analysis of variability in sport has shown significant growth in recent years. Also, the study of space management in the game field has not been object of research yet. The present study pretends to describe the variability in the use of strategic space in high performance football. To do this, the spatial management of the Spanish men’s soccer team when it is in possession of the ball has been analyzed, during its participation in the UEFA Euro 2012 championship. Specifically, 6861 events have been collected and analyzed. Different zoning of the field have been used, and the location of the ball has been recorded in each offensive action. Using the observational methodology as a methodological filter, two types of analysis have been carried out: first, a General Linear Model was implemented to know the variability of the strategic space. Models with two, three, four and five variables have been tested. In order to estimate the degree of accuracy and generalization of the data obtained, the Generalizability Theory was implemented. Next, and in order to estimate the degree of accuracy and generalization of the data obtained, the Generalizability Theory was implemented. The results showed that the model that produces greater variability and better explanation is the four-variable model (P = 0.019; r² = 0.838), with the inclusion of the variables match half, rival, move initiation zone and move conclusion zone. Next, an optimization plan was implemented to know the degree of generalization with the Rival, Start Zone (SZ) and Conclusion Zone (CZ) facets. The available results indicate that it is based on an adequate research design in terms of the number of observations. The results of the present study could have a double practical application. On the one hand, the inclusion of the game’s space management in training sessions will potentially conceal the true tactical intention. On the other hand, knowing the variability of the strategic space will allow to exploit areas of the optimal playing field to attack the rival team.

A Systematic Review of Collective Tactical Behaviours in Football Using Positional Data

BACKGROUND

Performance analysis research in association football has recently cusped a paradigmatic shift in the way tactical behaviours are studied. Based on insights from system complexity research, a growing number of studies now analyse tactical behaviours in football based on the collective movements of team players.

OBJECTIVE

The aim of this systematic review is to provide a summary of empirical research on collective tactical behaviours in football, with a particular focus on organising the methods used and their key findings.

METHODS

A systematic search of relevant English-language articles was performed on one database (Web of Science Core Collection) and one search engine (PubMed), based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines. The keywords 'football' and 'soccer' were each paired with all possible combinations of the following keywords: 'collective movement behaviour', 'collective behaviour', 'tactical behaviour', 'interpersonal coordination', 'space', 'Voronoi', 'synchronisation', 'tactical analysis', 'constraints', 'ecological dynamics', and 'dynamic positioning'. Empirical studies that were related to tactical analyses of footballers' positional data were sought for inclusion and analysis.

RESULTS

Full-text articles of 77 studies were reviewed. A total of 27 tactical variables were identified, which were subsequently organised into 6 categories. In addition to conventional methods of linear analysis, 11 methods of nonlinear analysis were also used, which can be organised into measures of predictability (4 methods) and synchronisation (7 methods). The key findings of the reviewed studies were organised into two themes: levels of analysis, and levels of expertise.

CONCLUSIONS

Some trends in key findings revealed the following collective behaviours as possible indicators of better tactical expertise: higher movement regularity; wider dispersion in youth players and shorter readjustment delay between teammates and opponents. Characteristic behaviours were also observed as an effect of playing position, numerical inequality, and task constraints. Future research should focus on contextualising positional data, incorporating the needs of coaching staff, to better bridge the research-practice gap.

Performance Analysis in Rugby Union: a Critical Systematic Review

BACKGROUND

Performance analysis in rugby union has become an integral part of the coaching process. Although performance analysis research in rugby and data collection has progressed, the utility of the insights is not well understood. The primary objective of this review is to consider the current state of performance analysis research in professional rugby union and consider the utility of common methods of analysing performance and the applicability of these methods within professional coaching practice.

METHODS

SPORTDiscus electronic database was searched for relevant articles published between 1 January 1997 and 7 March 2019. Professional, male 15-a-side rugby union studies that included relevant data on tactical and performance evaluation, and statistical compilation of time-motion analysis were included. Studies were categorised based on the main focus and each study was reviewed by assessing a number of factors such as context, opposition analysis, competition and sample size.

RESULTS

Forty-one studies met the inclusion criteria. The majority of these studies measured performance through the collection and analysis of performance indicators. The majority did not provide context relating to multiple confounding factors such as field location, match location and opposition information. Twenty-nine performance indicators differentiated between successful match outcomes; however, only eight were commonly shared across some studies. Five studies considered rugby union as a dynamical system; however, these studies were limited in analysing lower or national-level competitions.

CONCLUSIONS

The review highlighted the issues associated with assessing isolated measures of performance, lacking contextual information such as the opposition, match location, period within match and field location. A small number of studies have assessed rugby union performance through a dynamical systems lens, identifying successful characteristics in collective behaviour patterns in attacking phases. Performance analysis in international rugby union can be advanced by adopting these approaches in addition to methods currently adopted in other team sports.

Effects of Temporary Numerical Imbalances on Collective Exploratory Behavior of Young and Professional Football Players

The aim of this study was to explore how the use of temporary numerical imbalances during small-sided Game SSGs affects team’s exploratory behaviors (i.e., variety and quantity of responses given in an ever-changing game context and its rate of change) in different age groups. Two different age groups (under−15 and under−23) of football players participated in the study. For each age group, three teams of five players played six small-sided games of 5 min duration in different conditions: (i) numerical balance (GK + 4 vs. 4 + GK); (ii) temporary numerical imbalance, which consisted of a numerical change of teammates and opponents every one minute. Latitude and longitude GPS coordinates were used to determine the positioning-derived variables. The dynamic overlap (i.e. the measure of average similarity of the game patterns that take place in increasingly larger time intervals) was used to provide information of the rate and breadth of exploratory behavior. The results revealed that the long-term exploratory breadth increased for the under−23 age group. Non-clear effects were found for the short-term rate of exploration, but with an increasing trend. In the under−15 group, the exploratory behavior was more likely to increase in the long term. The increase for the short-term rate of exploration was unclear, but it follows an increasing trend. These results suggest that the use of temporary numerical imbalances could offer coaches more dynamic training situations and different adaptive training environments similar to matches.

A Match-Derived Relative Pitch Area Facilitates the Tactical Representativeness of Small-Sided Games for the Official Soccer Match

Olthof, SBH, Frencken, WGP, and Lemmink, KAPM. A match-derived relative pitch area facilitates the tactical representativeness of small-sided games for the official soccer match. J Strength Cond Res 33(2): 523–530, 2019—Small-sided games (SSGs) are a promising training format in soccer to replicate (situations of) the official match across all age groups. Typically, SSGs are played on a smaller relative pitch area (RPA; i.e., <150 m²) than the match (320 m² RPA), which results in different tactical demands. To create a more precise replication of tactical match demands in SSGs with less than 11 players per team, a match-derived RPA (320 m²) may be considered because this affords a similar playing area per player. In addition, subgroup analysis is necessary to deal with the different number of players in match and SSGs. Therefore, this study aims to investigate tactical demands of matches and various SSGs—with a different number of players and played on 320 m² RPA—in talented youth soccer players. Twelve elite soccer teams in 4 age categories (under-13, under-15, under-17, and under-19) played official matches and 4 vs. 4 + goalkeepers (GKs), 6 vs. 6 + GKs, and 8 vs. 8 + GKs. Positional data were collected to calculate tactical variables (interpersonal distances, length, width, and surface areas) for all players and for 2- and 4-player subgroups. Corresponding tactical variability (coefficients of variation expressed as percentages) was determined for all players. Results demonstrated that in each age category, with an increase in number of players, team distances increased and tactical variability decreased. Subgroup analyses revealed similar team distances in matches and SSGs with the exception of larger interpersonal distances in 4 vs. 4 + GKs than the match in under-13, under-15, and under-17. Match-derived RPA in SSGs facilitates the tactical representativeness for the match. Soccer coaches can use such SSGs for an optimal tactical match preparation.

Not Every Pass Can Be an Assist: A Data-Driven Model to Measure Pass Effectiveness in Professional Soccer Matches

In professional soccer, nowadays almost every team employs tracking technology to monitor performance during trainings and matches. Over the recent years, there has been a rapid increase in both the quality and quantity of data collected in soccer resulting in large amounts of data collected by teams every single day. The sheer amount of available data provides opportunities as well as challenges to both science and practice. Traditional experimental and statistical methods used in sport science do not seem fully capable to exploit the possibilities of the large amounts of data in modern soccer. As a result, tracking data are mainly used to monitor player loading and physical performance. However, an interesting opportunity exists at the intersection of data science and sport science. By means of tracking data, we could gain valuable insights in the how and why of tactical performance during a soccer match. One of the most interesting and most frequently occurring elements of tactical performance is the pass. Every team has around 500 passing interactions during a single game. Yet, we mainly judge the quality and effectiveness of a pass by means of observational analysis, and whether the pass reaches a teammate. In this article, we present a new approach to quantify pass effectiveness by means of tracking data. We introduce two new measures that quantify the effectiveness of a pass by means of how well a pass disrupts the opposing defense. We demonstrate that our measures are sensitive and valid in the differentiation between effective and less effective passes, as well as between the effective and less effective players. Furthermore, we use this method to study the characteristics of the most effective passes in our data set. The presented approach is the first quantitative model to measure pass effectiveness based on tracking data that are not linked directly to goal-scoring opportunities. As a result, this is the first model that does not overvalue forward passes. Therefore, our model can be used to study the complex dynamics of build-up and space creation in soccer.

A Systems Approach to Performance Analysis in Women's Netball: Using Work Domain Analysis to Model Elite Netball Performance

Netball is a newly professional women’s sport, as such there has been little research conducted investigating performance analysis (PA) in elite netball. The aim of this study was to develop a model of the elite netball performance system to identify the complex relationships among key performance indicators. Eleven elite subject matter experts (SMEs) participated in workshops to produce a systems model of the netball match performance. The model was developed using the work domain analysis (WDA) method. A model of the netball match performance system was produced showing the interrelated objects, processes, functions, values, and purposes involved in elite level netball matches. The model identified the components of elite level netball performance and the interactions and relationships between them. The output of this research has identified novel PA measures including passing and possession measures, measures of cognitive performance, and measures related to physical activity. Netball is a complex sport, involving multiple dynamic and interrelated components. Consequently, there is an opportunity to develop holistic PA measures that focus on interacting components, as opposed to components in isolation.

Interpersonal Coordination in Soccer: Interpreting Literature to Enhance the Representativeness of Task Design, From Dyads to Teams

Interpersonal coordination in soccer has become a trending topic in sports sciences, and several studies have examined how interpersonal coordination unfolds at different levels (i.e., dyads, sub-groups, teams). Investigations have largely focused on interactional behaviors at micro and macro levels through tasks from dyadic (i.e., 1 vs. 1) to team (i.e., 11 vs. 11) levels. However, as the degree of representativeness of a task depends on the magnitude of the relationship between simulated and intended environments, it is necessary to address a discussion on the correspondence between competitive and practice/experimental settings in soccer. The aims of this paper are to: (i) provide a brief description of the main concepts underlying the subject of interpersonal coordination in sports teams; (ii) demonstrate, through exemplar research findings, how interpersonal coordination in soccer unfolds at different scales; and (iii), discuss how coaches and researchers may ensure representativeness for practice and experimental tasks. We observed that papers addressing the analysis of interpersonal coordination tendencies in soccer often resort to dyadic (one vs. one) or sub-group (many vs. many) experimental tasks, instead of full-sized (11 vs. 11) games. Consequently, the extent to which such patterns reflect those observed in competition is somewhat uncertain. The design of practice and/or experimental tasks that rely on sub-phases of the game (e.g., 1 vs. 1, 4 vs. 4) should ensure the preservation of players’ behavior patterns in intended match conditions (11 vs. 11). This can be accomplished by measuring the level of action fidelity of the task, ensuring correspondence and successful transfer across contexts.

What Performance Analysts Need to Know About Research Trends in Association Football (2012-2016): A Systematic Review

BACKGROUND

Evolving patterns of match analysis research need to be systematically reviewed regularly since this area of work is burgeoning rapidly and studies can offer new insights to performance analysts if theoretically and coherently organized.

OBJECTIVE

The purpose of this paper was to conduct a systematic review of published articles on match analysis in adult male football, identify and organize common research topics, and synthesize the emerging patterns of work between 2012 and 2016, according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines.

METHODS

The Web of Science database was searched for relevant published studies using the following keywords: 'football' and 'soccer', each one associated with the terms 'match analysis', 'performance analysis', 'notational analysis', 'game analysis', 'tactical analysis' and 'patterns of play'.

RESULTS

Of 483 studies initially identified, 77 were fully reviewed and their outcome measures extracted and analyzed. Results showed that research mainly focused on (1) performance at set pieces, i.e. corner kicks, free kicks, penalty kicks; (2) collective system behaviours, captured by established variables such as team centroid (geometrical centre of a set of players) and team dispersion (quantification of how far players are apart), as well as tendencies for team communication (establishing networks based on passing sequences), sequential patterns (predicting future passing sequences), and group outcomes (relationships between match-related statistics and final match scores); and (3) activity profile of players, i.e. playing roles, effects of fatigue, substitutions during matches, and the effects of environmental constraints on performance, such as heat and altitude.

CONCLUSION

From the previous review, novel variables were identified that require new measurement techniques. It is evident that the complexity engendered during performance in competitive soccer requires an integrated approach that considers multiple aspects. A challenge for researchers is to align these new measures with the needs of the coaches through a more integrated relationship between coaches and researchers, to produce practical and usable information that improves player performance and coach activity.

ForVizor: Visualizing Spatio-Temporal Team Formations in Soccer

Regarded as a high-level tactic in soccer, a team formation assigns players different tasks and indicates their active regions on the pitch, thereby influencing the team performance significantly. Analysis of formations in soccer has become particularly indispensable for soccer analysts. However, formations of a team are intrinsically time-varying and contain inherent spatial information. The spatio-temporal nature of formations and other characteristics of soccer data, such as multivariate features, make analysis of formations in soccer a challenging problem. In this study, we closely worked with domain experts to characterize domain problems of formation analysis in soccer and formulated several design goals. We design a novel spatio-temporal visual representation of changes in team formation, allowing analysts to visually analyze the evolution of formations and track the spatial flow of players within formations over time. Based on the new design, we further design and develop ForVizor, a visual analytics system, which empowers users to track the spatio-temporal changes in formation and understand how and why such changes occur. With ForVizor, domain experts conduct formation analysis of two games. Analysis results with insights and useful feedback are summarized in two case studies.

Current Approaches to Tactical Performance Analyses in Soccer Using Position Data

Tactical match performance depends on the quality of actions of individual players or teams in space and time during match-play in order to be successful. Technological innovations have led to new possibilities to capture accurate spatio-temporal information of all players and unravel the dynamics and complexity of soccer matches. The main aim of this article is to give an overview of the current state of development of the analysis of position data in soccer. Based on the same single set of position data of a high-level 11 versus 11 match (Bayern Munich against FC Barcelona) three different promising approaches from the perspective of dynamic systems and neural networks will be presented: Tactical performance analysis revealed inter-player coordination, inter-team and inter-line coordination before critical events, as well as team-team interaction and compactness coefficients. This could lead to a multi-disciplinary discussion on match analyses in sport science and new avenues for theoretical and practical implications in soccer.

Multiscale coordination between athletes: Complexity matching in ergometer rowing

Complex systems applications in human movement sciences have increased our understanding of emergent coordination patterns between athletes. In the current study, we take a novel step and propose that movement coordination between athletes is a multiscale phenomenon. Specifically, we investigated so-called "complexity matching" of performance measured in the context of rowing. Sixteen rowers participated in two sessions on rowing ergometers: One individual session of 550 strokes and one dyadic session of 550 strokes side-by-side with a team member. We used evenly-spaced detrended fluctuation analysis (DFA) to calculate the complexity indices (DFA exponents) of the force-peak interval series for each rower in each session. The DFA exponents between team members were uncorrelated in the individual sessions (r = 0.06), but were strongly and significantly correlated when team members rowed together (r = 0.87). Furthermore, we found that complexity matching could not be attributed to the rowers mimicking or locally adapting to each other. These findings contribute to the current theoretical understanding of coordination dynamics in sports.

Positional synchronization affects physical and physiological responses to preseason in professional football (soccer)

This study aimed to identify changes in tactical, physical and physiological performances in large-sided games during the preseason of elite footballers. Thirty professional football players participated in several GK+8vs.8+GK large-sided games across the first four weeks of the season. Players were monitored by GPS units and heart rate monitors to quantify physical, physiological and tactical performances. The variables were compared according to the preseason period, players' positioning and professional experience. The training situation promoted similar physiological responses during the first and the last training period. However, players were revealed to have higher levels of positional synchronization during the last preseason period, indicating an improved tactical performance. Tactical variables seem to reflect the improvement of players' performance during the preseason, measured in large-sided games situation, while affecting both physical and physiological demands. These results highlight the potential of positioning derived variables, concurrently to physical and physiological variables, for football training optimization.

Teams as Complex Adaptive Systems: Reviewing 17 Years of Research

At the turn of the century, Arrow, McGrath, and Berdahl portrayed teams as complex adaptive systems (CAS). And yet, despite broad agreement that this approach facilitates a better understanding of teams, it has only now been timidly incorporated into team research. To help fully incorporate the logic of teams as CAS in the science of teams, we review extant research on teams approached from a nonlinear dynamical system theory. Using a systematic review approach, we selected 92 articles published over the last 17 years to integrate what we know about teams as CAS. Our review reveals the evidence supporting teams as CAS, and the set of analytical techniques to analyze team data from this perspective. This review contributes to teams’ theory and practice by offering ways to identify both research methods and managing techniques that scholars and practitioners may apply to study and manage teams as CAS.

Individual ball possession in soccer

This paper describes models for detecting individual and team ball possession in soccer based on position data. The types of ball possession are classified as Individual Ball Possession (IBC), Individual Ball Action (IBA), Individual Ball Control (IBC), Team Ball Possession (TBP), Team Ball Control (TBC) und Team Playmaking (TPM) according to different starting points and endpoints and the type of ball control involved. The machine learning approach used is able to determine how long the ball spends in the sphere of influence of a player based on the distance between the players and the ball together with their direction of motion, speed and the acceleration of the ball. The degree of ball control exhibited during this phase is classified based on the spatio-temporal configuration of the player controlling the ball, the ball itself and opposing players using a Bayesian network. The evaluation and application of this approach uses data from 60 matches in the German Bundesliga season of 2013/14, including 69,667 IBA intervals. The identification rate was F = .88 for IBA and F = .83 for IBP, and the classification rate for IBC was κ = .67. Match analysis showed the following mean values per match: TBP 56:04 ± 5:12 min, TPM 50:01 ± 7:05 min and TBC 17:49 ± 8:13 min. There were 836 ± 424 IBC intervals per match and their number was significantly reduced by -5.1% from the 1st to 2nd half. The analysis of ball possession at the player level indicates shortest accumulated IBC times for the central forwards (0:49 ± 0:43 min) and the longest for goalkeepers (1:38 ± 0:58 min), central defenders (1:38 ± 1:09 min) and central midfielders (1:27 ± 1:08 min). The results could improve performance analysis in soccer, help to detect match events automatically, and allow discernment of higher value tactical structures, which is based on individual ball possession.

Influence of gait mode and body orientation on following a walking avatar

Regulating distance with a moving object or person is a key component of human movement and of skillful interpersonal coordination. The current set of experiments aimed to assess the role of gait mode and body orientation on distance regulation using a cyclical locomotor tracking task in which participants followed a virtual leader. In the first experiment, participants moved in the backward-forward direction while the body orientation of the virtual leader was manipulated (i.e., facing towards, or away from the follower), hence imposing an incongruence in gait mode between leader and follower. Distance regulation was spatially less accurate when followers walked backwards. Additionally, a clear trade-off was found between spatial leader-follower accuracy and temporal synchrony. Any perceptual effects were overshadowed by the effect of one's gait mode. In the second experiment we examined lateral following. The results suggested that lateral following was also constrained strongly by perceptual information presented by the leader. Together, these findings demonstrated how locomotor tracking depends on gait mode, but also on the body orientation of whoever is being followed.

Soft-assembled Multilevel Dynamics of Tactical Behaviors in Soccer

This study aimed to identify the tactical patterns and the timescales of variables during a soccer match, allowing understanding the multilevel organization of tactical behaviors, and to determine the similarity of patterns performed by different groups of teammates during the first and second halves. Positional data from 20 professional male soccer players from the same team were collected using high frequency global positioning systems (5 Hz). Twenty-nine categories of tactical behaviors were determined from eight positioning-derived variables creating multivariate binary (Boolean) time-series matrices. Hierarchical principal component analysis (PCA) was used to identify the multilevel structure of tactical behaviors. The sequential reduction of each set level of principal components revealed a sole principal component as the slowest collective variable, forming the global basin of attraction of tactical patterns during each half of the match. In addition, the mean dwell time of each positioning-derived variable helped to understand the multilevel organization of collective tactical behavior during a soccer match. This approach warrants further investigations to analyze the influence of task constraints on the emergence of tactical behavior. Furthermore, PCA can help coaches to design representative training tasks according to those tactical patterns captured during match competitions and to compare them depending on situational variables.

Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science

Until recently tactical analysis in elite soccer were based on observational data using variables which discard most contextual information. Analyses of team tactics require however detailed data from various sources including technical skill, individual physiological performance, and team formations among others to represent the complex processes underlying team tactical behavior. Accordingly, little is known about how these different factors influence team tactical behavior in elite soccer. In parts, this has also been due to the lack of available data. Increasingly however, detailed game logs obtained through next-generation tracking technologies in addition to physiological training data collected through novel miniature sensor technologies have become available for research. This leads however to the opposite problem where the shear amount of data becomes an obstacle in itself as methodological guidelines as well as theoretical modelling of tactical decision making in team sports is lacking. The present paper discusses how big data and modern machine learning technologies may help to address these issues and aid in developing a theoretical model for tactical decision making in team sports. As experience from medical applications show, significant organizational obstacles regarding data governance and access to technologies must be overcome first. The present work discusses these issues with respect to tactical analyses in elite soccer and propose a technological stack which aims to introduce big data technologies into elite soccer research. The proposed approach could also serve as a guideline for other sports science domains as increasing data size is becoming a wide-spread phenomenon.

The influence of scoring targets and outer-floaters on attacking and defending team dispersion, shape and creation of space during small-sided soccer games

The effect of altered game formats on team performances during soccer practice can be harnessed by coaches to stimulate specific tactical behaviours. The aim of the present study was to analyse the influence of using (i) small goals [SG], (ii) goalkeepers [7G] and (iii) floaters [7GF] on the dispersion, shape and available space of teams during small-sided games (SSGs). Twenty-four male soccer players were distributed into four teams composed of five players, two goalkeepers and two floaters that performed six SSG bouts of 6 min, interspersed with 6 min of passive recovery. Offensive and defensive phases were also analysed separately in order to verify the preservation of basic principles of attacking (teams more stretched to create free space) and defending (teams more compact to tie-up space) during SSGs. The variables used to characterize the collective behaviour were: length [L], width [W], team shape [Sh], and team separateness [TS]. Results revealed that the teams showed different collective behaviours depending on SSG format and a playing phase: a) L and W were higher in attack than in defence in all SSGs; b) team shapes were more elongated in defence in all SSGs except SG; c) the space separating players from their closest opponents (TS) was shorter in 7G; and d) SG and 7GF elicited greater defensive openness due to increased team width. The results suggest that manipulating task constraints, such as goal size, presence or absence of goalkeepers and floaters can be harnessed by coaches to shape distinct team tactical behaviours in SSGs while preserving the basic principles of attacking and defending.

Footballers' movement behaviour during 2-, 3-, 4- and 5-a-side small-sided games

The aim of this study was to compare footballers' movement behaviour during 2-, 3-, 4- and 5-a-side small-sided games. Ten young professional players (age = 18.0 ± 0.67 years) participated in 3 bouts of each small-sided games for 6 min with 1 min of active rest between bouts. Positional data were collected using GPS system units and used to calculate the following variables: team centroid, distance between each player and own and opponent team centroids and distance between centroids. Approximate entropy was used to identify the time series regularity for each variable. The distance to own team centroid increased with the number of players (effect sizes from moderate to perfect). The results from the distance to the opponent's centroid exhibited a similar trend. The distance between centroids decreased from 2- to the 4-a-side, but then increased in 5-a-side. A higher number of players were associated with lower approximate entropy values, suggesting higher positional organisation in small-sided games with more players. The highest movement regularity found in 4- and 5-a-side identified these formats as more adequate to promote team-related emergent and self-organised behaviours.

Does the recent internal load and strain on players affect match outcome in elite Australian football?

OBJECTIVES

To compare recent internal training load and strain of elite Australian football players for match outcome.

DESIGN

Case study.

METHODS

Load was quantified from session rating of perceived exertion (sRPE) for individual players from one team in 141 professional Australian football matches over six seasons, then averaged for players that competed for the team each week. Internal weekly-load and weekly-strain (load×monotony) was compared to recent-load and recent-strain (four-week rolling average) as a marker of training-stress balance for each player against the match outcome. Covariates for relative position of teams in the competition and days between matches were modelled. Differences were standardised (effect size; ES) and interpreted using magnitude based inferences.

RESULTS

Weekly-load was likely higher for match wins (ES±90% confidence limits; 0.43±0.27), and when days-break was used as a covariate (0.45±0.27) but only possibly higher with relative ladder position covaried (RLP, 0.29±0.33). There was a possibly greater positive training-stress balance for load in wins (0.31; ±0.38) with db (0.39; ±0.39) and RLP covaried (0.27; ±0.48). There were no clear differences for strain for wins and losses or with either covariate. There was a likely greater positive training-stress balance for strain in wins (0.51; ±0.41) with days-break (0.48; ±0.41) but not RLP covaried.

CONCLUSIONS

Weekly-load and a positive training-stress balance for strain were the best predictors of match success. The higher weekly-load and training-stress balance for strain highlight the conflict between maintaining the training stimulus and minimising fatigue in Australian football players between matches.