Team Sports Performance Analysed Through the Lens of Social Network Theory: Implications for Research and Practice

Motor, cognitive, and socio-cognitive mechanisms explaining social skills in autism and typical development

Challenges in social functioning are considered a core criterion for diagnosing autism. Although motor skills, executive functioning (EF), and theory of mind (ToM) abilities independently affect social challenges and are interconnected, these abilities' shared contribution to the explanation of social functioning in autism remains under-investigated. To address this disparity, we examined the motor, EF, and ToM abilities of 148 autistic and non-autistic youth (ages 6-16 years), evaluating these variables' impact on social ability and their interconnections. Our mediation model exploring the contribution of motor, EF, and ToM skills explained 85% of the variance in social functioning (Social Responsiveness Scale-SRS-2). Analysis yielded a direct path from study group to SRS-2-social (typically developing-TD > autistic) and two main parallel indirect joint paths: (a) Group ➔ motor ➔ EF ➔ SRS-2-social; and (b) Group ➔ motor ➔ ToM ➔ SRS-2-social. In two secondary indirect paths, autistic children showed lower motor skills, which in turn explained their higher EF and/or ToM impairment, which in turn explained their higher social skills impairment. Put differently, our results suggest that better EF and TOM proficiency may compensate for poorer motor skills. Findings also indicated that the collective impact of motor, EF, and ToM skills on social functioning, along with the mediating role played by EF and ToM on the social-motor linkage, may contribute to understanding individual differences in the social functioning of autistic children. These conclusions call for the inclusion of motor, EF, and ToM activities into daily practices to facilitate social functioning.

Comparing the Tactical Behavior of Young Soccer Players in Full- and Small-Sided Games

The objective was to assess and compare the tactical conduct of players aged U-8, U-10, and U-12 during full- and small-sided games, focusing on tactical modeling and interaction dynamics. Each age group comprised three teams (n = 180; 60 per category; 20 per team), engaging in a tournament where teams faced each other once in both formats - 18 matches; 3 per category in each format. Full-sided games (GK + 10 vs.10 + GK; 100 × 68 m) and small-sided games (U-8: GK + 4 vs. 4 + GK (36 × 20 m); U-10: GK + 7 vs. 7 + GK (52.5 × 34 m); U-12: GK + 10 vs. 10 + GK (68 × 45 m). Standard playing times (3 periods of 12 minutes (U-8s); 3 periods of 15 minutes (U-10s); and 3 periods of 20 minutes (U-12s), with a 5-minute break. Variables were examined using descriptive analysis (mean, standard deviation, and confidence interval), with paired t-tests and Wilcoxon tests employed for inter-format comparisons. Despite players benefiting from more time and space in full-sided games (increased ball receptions and overall ball involvement), results from small-sided games indicate three key advantages: 1) More goals (U-8s: z = -3.44, p = .050) and shots on target (U-8: z = -3.25, p = .001; U-10: z = -2.72, p = .007); 2) Game space management-ball circulation in larger amplitude (U-10: t = -4.20, p = .001; U-12: t = -4.35, p < .001); and with more transitions (U-10: t = -3.60, p = .002; U-12: t = -4.16, p = .001) and 3) Fast decision-making-larger ball velocity circulation (U-08: t = -3.54, p = .003; U-10: t = -5.13, p < .001; U-12: t = -5.80, p < .001).

Exploring the Effects of Instruction and Game Design on Youth Soccer Players' Skill Involvement and Cooperative Team Behaviour

Objectives: The relationship between task constraints and player behaviors is of interest to coaches tasked with designing practice to optimize learning. This study aims to compare the skill involvements and cooperative team behavior of teams of youth soccer players engaged in a goal exaggeration and/or a prescriptive coach instruction condition compared to a free-play control condition. Methods: Twenty male soccer players aged 12-15 participated in small-sided games under four conditions: free-play, goal exaggeration, prescriptive coach instruction, and combination over four weeks. Using video footage, teams' collective skill involvements (shot, pass, dribble) and passing network characteristics (closeness, density, and betweenness) were measured for each game. Results: A Friedmans rank test identified that playing conditions resulted in significant differences in attempted dribbles (p < .001), goals scored (p < .001), network density (p = .001), closeness (p < .001) and betweenness (p = .002). Teams attempted to dribble the most in the free-play and goal-exaggeration conditions, and the most goals were scored in the goal-exaggeration and combination conditions. Additionally, teams exhibited more well-connected passing networks (i.e. higher density, higher closeness, and lower betweenness values) in the combination condition and higher network density in the explicit instruction condition. Conclusions: The results of this study indicate that coach instruction may be more associated with cooperative team behavior, whereas free-play or manipulating task constraints in the absence of instruction may be associated with players attempting more individual actions.

The physical, technical and tactical demands of on-field training drills in professional Rugby league: a systematic scoping review

OBJECTIVES

The main objectives of this scoping review were to conduct a systematic search on the physical, technical and tactical demands of rugby league training, consolidate and summarise key findings and identify any existing gaps in knowledge.

METHODS

A systematic online search of Scopus, PubMed, MEDLINE and SPORTDiscus was conducted from earliest record to 6 August 2023 and supplemented by manually searching reference lists. The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist was followed. Studies were eligible for inclusion if they investigated the physical, technical and/or tactical demands of rugby league training within all levels of competition and included either male or female participants.

RESULTS

The initial search yielded 637 papers, 25 of which were included in the review. Of these studies, the majority (n = 19) exclusively examined the physical demands of training, one paper exclusively examined the technical demands of training, five studies included both physical and technical demands, and no studies examined the tactical demands of training. Small-sided games was the most prevalent drill included within investigations examining the physical and technical demands of various rugby league training drills.

CONCLUSIONS

The present review was the first to scope peer-reviewed literature on the multifaceted demands (i.e. physical, technical and tactical) demands of rugby league training. It is apparent that this area is under researched, specifically in literature examining the technical and tactical elements of rugby league training.

Analysis of player speed and angle toward the ball in soccer

The study analyzes how the magnitude and angle of the speed of soccer players change according to the distance to the ball and the phases of the game, namely the defensive and attacking phases. We observed how the role played in the team (goalkeeper, defender, midfielder, or forward) strongly determines the speed pattern of players. As a general trend, the speed's modulus is incremented as their position is closer to the ball, however, it is slightly decreased when arriving at it. Next, we studied how the angle of the speed with the direction to the ball is related to the distance to the ball and the game phases. We observed that, during the defensive phase, goalkeepers are the players that run more parallel to the ball, while forwards are the ones running more directly to the ball position. Importantly, this behavior changes dramatically during the attacking phase. Finally, we show how the proposed methodology can be used to analyze the speed-angle patterns of specific players to understand better how they move on the pitch according to the distance to the ball.

Relationships among Square Dance, Group Cohesion, Perceived Social Support, and Psychological Capital in 2721 Middle-Aged and Older Adults in China

(1) Background: Aging is a global phenomenon, and China's aging is extensive and rapid and already at the middle to upper level worldwide. Promoting social interaction and increasing positive psychological qualities in individuals are key components in helping people adapt to the physical and mental changes of the aging process. Among them, how middle-aged and older adults improve their physical and mental health through physical activity is of great concern. (2) Methods: This study measured the physical activity of 2721 middle-aged and elderly square dance participants across China, and structural equation modeling was applied to explore the relationship between square dance exercise and group cohesion as well as the role of perceived social support and psychological capital. (3) Results: The results showed that (a) square dance exercise positively predicts group cohesion among middle-aged and older adults. (b) Perceived social support and psychological capital mediate the relationship between square dance exercise and group cohesion, and the mediating role consists of three pathways: perceived social support alone, psychological capital alone, and perceived social support-psychological capital chain mediation. (c) The mediating effect of psychological capital alone is greater than the mediating effect of perceived social support alone and the mediating effect of the perceived social support-psychological capital chain. (4) Conclusions: This study provides support for the theory and practice of square dance exercise and intervention guidance for increasing positive psychological qualities and group dynamic levels in middle-aged and older adults.

Dynamical biomarkers in teams and other multiagent systems

Effective team behavior in high-performance environments such as in sport and the military requires individual team members to efficiently perceive the unfolding task events, predict the actions and action intents of the other team members, and plan and execute their own actions to simultaneously accomplish individual and collective goals. To enhance team performance through effective cooperation, it is crucial to measure the situation awareness and dynamics of each team member and how they collectively impact the team's functioning. Further, to be practically useful for real-life settings, such measures must be easily obtainable from existing sensors. This paper presents several methodologies that can be used on positional and movement acceleration data of team members to quantify and/or predict team performance, assess situation awareness, and to help identify task-relevant information to support individual decision-making. Given the limited reporting of these methods within military cohorts, these methodologies are described using examples from team sports and teams training in virtual environments, with discussion as to how they can be applied to real-world military teams.

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.

Capture, analyse, visualise: An exemplar of performance analysis in practice in field hockey

The goal of performance analysis is to capture the multitude of factors that affect sports strategy, and present them in an informative, interpretable, and accessible format. The aim of this study was to outline a performance analysis process in field hockey that captures, analyses and visualises strategy in layers of detail culminating in the creation of an RStudio Shiny application. Computerised notational analysis systems were developed to capture in-game events and ball tracking data of 74 matches from the Women’s Pro League 2019. Game styles were developed using k-means cluster analysis to reduce detailed in-game events into practical profiles to identify the attack types, game actions and tempo of a team’s strategy. Ball movement profiles were developed to identify the predictability (entropy) and direction (progression rates) of ball movements, and consequent distribution of possession in different attacking zones. The Shiny application, an interactive web-platform, links the information from simple game profiles with detailed game variables to understand each teams’ holistic game plan, how they are different, and how to exploit these differences. The process outlined can be applied to any team invasion sport to understand, develop and communicate successful strategies under different match situations.

Identifying and analysing game styles and factors influencing a team's strategy in field hockey

Characterising a team's game style is a performance analysis approach that captures game events, and groups them into profiles using clustering techniques to identify the consistent (and winning) strategies a team implements. The aim of this study was to identify the game styles of international hockey teams. Video footage from the 2019 Pro League tournament (n = 74 female and n = 57 male matches) were analysed retrospectively using a notational analysis system in SportsCode™. Variables were arranged into six game style categories (established attack game actions, counter attack game actions, established attack success, counter attack success, set pieces, tempo) and two game style types identified per category using a k-means clustering algorithm. Decision trees were used to identify the influence of extrinsic and intrinsic match factors on the probability of a team playing a particular game style. Opposition and other reference team game style categories were shown to be more important in predicting a game style category than contextual factors. Examination of team profiles highlights how different strategies are successful for different teams such as high-intensity attack or absorbing pressure and counter attacking. This performance analysis process provides practical insights into the holistic performance of international hockey teams.

Guardiola, Klopp, and Pochettino: The Purveyors of What? The Use of Passing Network Analysis to Identify and Compare Coaching Styles in Professional Football

We applied social networks analysis to objectively discriminate and describe interpersonal interaction dynamics of players across different top-coaching styles. The aim was to compare metrics in the passing networks of Jürgen Klopp, Pep Guardiola, and Mauricio Pochettino across the UEFA Champions League seasons from 2017 to 2020. Data on completed passes from 92 games were gathered and average passing networks metrics were computed. We were not only able to find the foundations on which these elite coaches build the passing dynamics in their respective teams, but also to determine important differences that represent their particular coaching signatures. The local cluster coefficient was the only metric not significantly different between coaches. Still, we found higher average shortest-path length for Guardiola's network (mean ± std = 3.00 ± 0.45 a.u.) compared to Klopp's (2.80 ± 0.52 a.u., p = 0.04) and Pochettino's (2.70 ± 0.39 a.u., p = 0.01). Density was higher for Guardiola's (64.16 ± 20.27 a.u.) than for Pochettino's team (51.42 ± 17.28 a.u., p = 0.008). The largest eigenvalue for Guardiola's team (65.95 ± 16.79 a.u.) was higher than for Klopp's (47.06 ± 17.25 a.u., p < 0.001) and Pochettino's (42,62 ± 12.01 a.u., p < 0.001). Centrality dispersion was also higher for Guardiola (0.14 ± 0.02 a.u.) when compared to Klopp (0.12 ± 0.03 a.u., p = 0.008). The local cluster coefficient seems to build the foundation for passing work, however, cohesion characteristics among players in the three teams of the top coaches seems to characterize their own footprint regarding passing dynamics. Guardiola stands out by the high number of passes and the enhanced connection of the most important players in the network. Klopp and Pochettino showed important similarities, which are associated to preferences toward more flexibility of interpersonal linkages synergies.

A scoping review of approaches for measuring 'interdependent' collaborative performances

INTRODUCTION

Individual assessment disregards the team aspect of clinical work. Team assessment collapses the individual into the group. Neither is sufficient for medical education, where measures need to attend to the individual while also accounting for interactions with others. Valid and reliable measures of interdependence are critical within medical education given the collaborative manner in which patient care is provided. Medical education currently lacks a consistent approach to measuring the performance between individuals working together as part of larger healthcare team. This review's objective was to identify existing approaches to measuring this interdependence.

METHODS

Following Arksey & O'Malley's methodology, we conducted a scoping review in 2018 and updated it to 2020. A search strategy involving five databases located >12 000 citations. At least two reviewers independently screened titles and abstracts, screened full texts (n = 161) and performed data extraction on twenty-seven included articles. Interviews were also conducted with key informants to check if any literature was missing and assess that our interpretations made sense.

RESULTS

Eighteen of the twenty-seven articles were empirical; nine conceptual with an empirical illustration. Eighteen were quantitative; nine used mixed methods. The articles spanned five disciplines and various application contexts, from online learning to sports performance. Only two of the included articles were from the field of Medical Education. The articles conceptualised interdependence of a group, using theoretical constructs such as collaboration synergy; of a network, using constructs such as degree centrality; and of a dyad, using constructs such as synchrony. Both descriptive (eg social network analysis) and inferential (eg multi-level modelling) approaches were described.

CONCLUSION

Efforts to measure interdependence are scarce and scattered across disciplines. Multiple theoretical concepts and inconsistent terminology may be limiting programmatic work. This review motivates the need for further study of measurement techniques, particularly those combining multiple approaches, to capture interdependence in medical education.

Mathematical Models to Measure the Variability of Nodes and Networks in Team Sports

Pattern analysis is a widely researched topic in team sports performance analysis, using information theory as a conceptual framework. Bayesian methods are also used in this research field, but the association between these two is being developed. The aim of this paper is to present new mathematical concepts that are based on information and probability theory and can be applied to network analysis in Team Sports. These results are based on the transition matrices of the Markov chain, associated with the adjacency matrices of a network with n nodes and allowing for a more robust analysis of the variability of interactions in team sports. The proposed models refer to individual and collective rates and indexes of total variability between players and teams as well as the overall passing capacity of a network, all of which are demonstrated in the UEFA 2020/2021 Champions League Final.

The Communication and Passing Contributions of Playing Positions in a Professional Soccer Team

Determining the connectivity of team members in sport provides important information on team functioning. In soccer, teams that are highly connected via passing have been shown to be more successful compared to teams less connected via passing. In addition to passing connectivity, players are connected with each other via intra-team communication (ITC) through verbal instruction, and nonverbal cues. Despite ITC being a known component of effective teamwork to enhance strategy, efficiency, motivation and concentration, ITC of individual playing positions has not previously been measured during soccer games, nor has it been associated with passing connections in a performance context. In this study, the received ITC that was perceived to be beneficial to performance during 22 competitive professional soccer matches was measured, in conjunction with the passing connections between team members. In total, 526 ITC ratings were collected and analysed, and a total of 7,693 passes were analysed. From the ITC and passing measures, a player connectivity index (PCI) representing the coupling of ITC and passing, was developed to determine the overall connectivity of the individual playing positions. Social network analysis (SNA) centrality metrics were used to determine the connectivity of the playing positions. There were significant (p < .05) main effects between playing positions for beneficial ITC, passing, and the PCI for centrality metrics, indicating that different playing positions interact with other team members differently. Pairwise comparisons indicated significant differences between individual playing positions for ITC, passing and the PCI. The two central defenders and the two central defensive midfielders had the highest mean values for ITC, passing, and the PCI compared to the other playing positions. The current findings suggest that central defenders and central defensive midfielders are positioned tactically to be highly involved in the build-up of passing moves, and to deliver beneficial task related information to team members. These findings have implications for performance analysis, coaches, and for talent identification.

Learning Curve for a Dual Attending Surgeon Strategy in Posterior Spinal Fusion (PSF): An Analysis of 105 Severe Adolescent Idiopathic Scoliosis Patients (Cobb Angle ≥90°)

STUDY DESIGN

Retrospective study.

OBJECTIVE

To assess the learning curve of a dual attending surgeon strategy in severe adolescent idiopathic scoliosis patients.

SUMMARY OF BACKGROUND DATA

The advantages of a dual attending surgeon strategy in improving the perioperative outcome in scoliosis surgery had been reported. However, the learning curve of this strategy in severe scoliosis had not been widely studied.

METHODS

A total of 105 patients with adolescent idiopathic scoliosis with Cobb angle of 90° or greater, who underwent posterior spinal fusion using a dual attending surgeon strategy were recruited. Primary outcomes were operative time, total blood loss, allogeneic blood transfusion requirement, length of hospital stay from time of operation and perioperative complications. Cases were sorted chronologically into group 1: cases 1 to 35, group 2: cases 36 to 70, and group 3: case 71 to 105. Mean operative time (≤193.3 min), total blood loss (≤1612.2 mL), combination of both and allogeneic blood transfusion were the selected criteria for receiver operating characteristic analysis of the learning curve.

RESULTS

The mean Cobb angle was 104.5° ± 12.3°. The operative time, total blood loss, and allogeneic blood transfusion requirement reduced significantly for group 1 (220.6 ± 54.8 min; 2011.3 ± 881.8 mL; 12 cases) versus group 2 (183.6 ± 36.7 min; 1481.6 ± 1035.5 mL; 3 cases) and group 1 versus group 3 (175.6 ± 38.4 min; 1343.7 ± 477.8 mL; 3 cases) (P < 0.05). There were six perioperative complications. Fifty-seven cases were required to achieve the preset criteria (mean operative time and mean total blood loss) (area under the curve 0.740; P < 0.001; sensitivity 0.675; specificity 0.662).

CONCLUSION

There was significant improvement in operative time and total blood loss when comparing group 1 versus group 2 and group 1 versus group 3. The cut-off point for the learning curve was 57 cases when the preset criteria were fulfilled (≤193.3 min operative time and ≤1612.2 mL of total blood loss).Level of Evidence: 4.

Body Physique, Body Composition, Physical Performance, Technical and Tactical Skills, Psychological Development, and Club Characteristics of Young Male Portuguese Soccer Players: The INEX Study

Youth soccer performance is multifaceted, includes physical growth, biological maturation, and physical fitness, and is linked to the sporting environment to which the players are exposed. We aim to describe age-related associations in body physique, body composition, physical performance technical and tactical skills, psychological and club characteristics of male soccer players aged 12 to 14 years. A total of 157 male soccer players clustered into three age-cohorts (12, 13 and 14 years) were recruited from six soccer clubs. Anthropometric, body composition and body physique, biological maturation, physical performance, skill/game proficiency data, psychological characteristics, and clubs’ characteristics were collected. Group means were compared using analysis of variance and covariance. Fourteen years old players were significantly taller, heavier, leaner, faster, stronger, and technically more skilled than their younger peers (p < 0.05). Differences in physical performance and technical skills (p < 0.05) were found between age groups when adjusting for confounders of soccer training and biological maturation. No significant differences (p > 0.05) between age groups were found in psychological domains. Our findings suggest that age, biological maturation, and training volume are key factors influencing young soccer players’ performance and development. Further, clubs’ conditions provide players with ample resources for their success in training and competition.

Consistency and identifiability of football teams: a network science perspective

We investigated the ability of football teams to develop a particular playing style by looking at their passing patterns. Using the information contained in the pass sequences during matches, we constructed the pitch passing networks of teams, whose nodes are the divisions of the pitch for a given spatial scale and links account for the number of passes from region to region. We translated football passings networks into their corresponding adjacency matrices. We calculated the correlations between matrices of the same team to quantify how consistent the passing patterns of a given team are. Next, we quantified the differences with other teams’ matrices and obtained an identifiability parameter that indicates how unique are the passing patterns of a given team. Consistency and identifiability rankings were calculated during a whole season, allowing to detect those teams of a league whose passing patterns are different from the rest. Furthermore, we found differences between teams playing at home or away. Finally, we used the identifiability parameter to investigate what teams imposed their passing patterns over the rivals during a given match.

Influence of Situational Variables, Team Formation, and Playing Position on Match Running Performance and Social Network Analysis in Brazilian Professional Soccer Players

Aquino, R, Carling, C, Palucci Vieira, LH, Martins, G, Jabor, G, Machado, J, Santiago, P, Garganta, J, and Puggina, E. Influence of situational variables, team formation, and playing position on match running performance and social network analysis of brazilian professional soccer players. J Strength Cond Res 34(3): 808-817, 2020-The purpose of this study was to investigate the independent and interactive effects of situational variables, opposition team formation, and playing position on running performance and network analysis in Brazilian professional soccer players (n = 22). Global positioning system technology was used to determine total distance covered, mean speed, maximum running speed, and distance covered in 6 speed ranges. Social network analysis was used to assess interpersonal coordination (team interactions characterized as successful passes [n = 3,033] between teammates). Observations of match running performance (n = 129) and network analysis (n = 108) were obtained. The main results were: (a) no interactive effects between team formation and playing position were observed for running and network variables (unclear to possibly); (b) matches played at home or against "weaker" opponents presented greater running demands and individual/global metrics of network analysis (likely to almost certain); (c) match outcome demonstrated influence only for running performance; matches in which the reference team won resulted in higher values than in matches lost; (d) when the reference team competed in 1-4-4-2 formation, this resulted in greater running demands than 1-4-2-3-1 formation (likely to almost certain); (e) reduced values of running performance variables were reported in central defenders compared with other positions. Central/external midfielders reported greater closeness/betweenness centrality, outdegree, and eigenvector compared with central/external defenders and forwards (likely to almost certain). The results from this study provide practical information to potentially impact on physical, tactical, and technical training.

Passing Networks and Tactical Action in Football: A Systematic Review

The aim of this study is to examine the most significant literature on network analyses and factors associated with tactical action in football. A systematic review was conducted on Web of Science, taking into account the PRISMA guidelines using the keyword “network”, associated with “football” or “soccer”. The search yielded 162 articles, 24 of which met the inclusion criteria. Significant results: (a) 50% of the studies ratify the importance of network structures, quantifying and comparing properties to determine the applicability of the results instead of analyzing them separately; (b) 12.5% analyze the process of offensive sequences and communication between teammates by means of goals scored; (c) the studies mainly identify a balance in the processes of passing networks; (d) the variables allowed for the interpretation of analyses of grouping metrics, centralization, density and heterogeneity in connections between players of the same team. Finally, a systematic analysis provides a functional understanding of knowledge that will help improve the performance of players and choose the most appropriate response within the circumstances of the game.

Node and Network Entropy—A Novel Mathematical Model for Pattern Analysis of Team Sports Behavior

Pattern analysis is a well-established topic in team sports performance analysis, and is usually centered on the analysis of passing sequences. Taking a Bayesian approach to the study of these interactions, this work presents novel entropy mathematical models for Markov chain-based pattern analysis in team sports networks, with Relative Transition Entropy and Network Transition Entropy applied to both passing and reception patterns. To demonstrate their applicability, these mathematical models were used in a case study in football—the 2016/2017 Champions League Final, where both teams were analyzed. The results show that the winning team, Real Madrid, presented greater values for both individual and team transition entropies, which indicate that greater levels of unpredictability may bring teams closer to victory. In conclusion, these metrics may provide information to game analysts, allowing them to provide coaches with accurate and timely information about the key players of the game.

How do Elite Soccer Teams Perform to Ball Recovery? Effects of Tactical Modelling and Contextual Variables on the Defensive Patterns of Play

Researchers in soccer match analysis have been using limited procedures to express the dynamics of the game and mainly focus on the attack. Therefore, the aims of this paper were to detect the successful teams’ ball recovery defensive patterns of play and study the influence of tactical modelling, halves, match status, opponent quality and stage competition on those patterns. The sample consisted of 1323 situations of defensive ball possession of the semi-finalist teams from the 2014 FIFA World Cup play-offs, which was collected by a valid and reliable observational instrument (Soccer-Defence). The Kruskal-Wallis H, Mann-Whitney U, Chi-square, Z-, multinomial logistic regression tests and sequential analysis (p < .05; z > 1.96) were used accordingly to test the differences and associations among and within teams of tactical modelling, tactical-technical behaviours and contextual variables to ball recovery. We found that among teams ball recovery differed in duration; H(3) = 14.958, p = .002. Germany were more likely to perform ball recovery by the goalkeeper than Argentina (p = .04; OR = 0.47) or the Netherlands (p < .05; OR = 0.50). Nevertheless, Brazil was the least likely to concede a shot off goal. Teams facing lower-ranked opponents were 0.63 times less likely to perform ball recovery by interception (p <.001). Additionally, sequential analysis illustrated that teams varied between central and lateral high-pressure zones before ball recovery in lower zones of the field. Finally, coaches could use such findings to design training exercises, create their own style of play, and set strategies.

Predicting Wins, Losses and Attributes' Sensitivities in the Soccer World Cup 2018 Using Neural Network Analysis

Predicting the results of soccer competitions and the contributions of match attributes, in particular, has gained popularity in recent years. Big data processing obtained from different sensors, cameras and analysis systems needs modern tools that can provide a deep understanding of the relationship between this huge amount of data produced by sensors and cameras, both linear and non-linear data. Using data mining tools does not appear sufficient to provide a deep understanding of the relationship between the match attributes and results and how to predict or optimize the results based upon performance variables. This study aimed to suggest a different approach to predict wins, losses and attributes' sensitivities which enables the prediction of match results based on the most sensitive attributes that affect it as a second step. A radial basis function neural network model has successfully weighted the effectiveness of all match attributes and classified the team results into the target groups as a win or loss. The neural network model's output demonstrated a correct percentage of win and loss of 83.3% and 72.7% respectively, with a low Root Mean Square training error of 2.9% and testing error of 0.37%. Out of 75 match attributes, 19 were identified as powerful predictors of success. The most powerful respectively were: the Total Team Medium Pass Attempted (MBA) 100%; the Distance Covered Team Average in zone 3 (15-20 km/h; Zone3_TA) 99%; the Team Average ball delivery into the attacking third of the field (TA_DAT) 80.9%; the Total Team Covered Distance without Ball Possession (Not in_Poss_TT) 76.8%; and the Average Distance Covered by Team (Game TA) 75.1%. Therefore, the novel radial based function neural network model can be employed by sports scientists to adapt training, tactics and opposition analysis to improve performance.

The Role of Hypernetworks as a Multilevel Methodology for Modelling and Understanding Dynamics of Team Sports Performance

Despite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommending methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels.

Network analysis of kick-in possession chains in elite Australian football

The study aim was to investigate ball movement patterns using network analysis techniques, to compare between successful and unsuccessful outcomes and teams in the Australian Football League (AFL). This analysis focused on possession chains starting from a kick-in (n = 1,720), drawn from all games played in the 2015 AFL Premiership season (18 teams, 206 games). Player interactions were quantified using four network metrics: cluster coefficient, degree centrality, network density, and entropy. Three-way ANOVA with Tukey post hoc and ω2 effect sizes were calculated to assess whether differences existed between kick-in outcomes, ladder brackets, and match outcomes for each network metric. No significant differences were observed between ladder brackets or match outcomes for any network metric. More successful kick-in chains were characterised by lower density (ω2 = 0.26, large effect; F(9, 1678) = 66.6, p < 0.00) and higher entropy (ω2 = 0.17, large effect; F(9, 1678) = 39.6, p < 0.00). This suggests that chains resulting in successful kick-in outcomes exhibited lower interconnectedness, with a high number of players involved, and lower predictability in ball movement patterns. These findings have practical value for coaches and performance analysts and support further applications of network analysis in Australian football.

Spatial and Temporal Entropies in the Spanish Football League: A Network Science Perspective

We quantified the spatial and temporal entropy related to football teams and their players by means of a pass-based interaction. First, we calculated the spatial entropy associated to the positions of all passes made by a football team during a match, obtaining a spatial entropy ranking of Spanish teams during the 2017/2018 season. Second, we investigated how the player’s average location in the field is related to the amount of entropy of his passes. Next, we constructed the temporal passing networks of each team and computed the deviation of their network parameters along the match. For each network parameter, we obtained the permutation entropy and the statistical complexity of its temporal fluctuations. Finally, we investigated how the permutation entropy (and statistical complexity) of the network parameters was related to the total number of passes made by a football team. Our results show that (i) spatial entropy changes according to the position of players in the field, and (ii) the organization of passing networks change during a match and its evolution can be captured measuring the permutation entropy and statistical complexity of the network parameters, allowing to identify what parameters evolve more randomly.

A multilevel hypernetworks approach to capture properties of team synergies at higher complexity levels

Previous work has sought to explain team coordination using insights from theories of synergy formation in collective systems. Under this theoretical rationale, players are conceptualised as independent degrees of freedom, whose interactions can become coupled to produce team synergies, guided by shared affordances. Previous conceptualisation from this perspective has identified key properties of synergies, the measurement of which can reveal important aspects of team dynamics. However, some team properties have been measured through implementation of a variety of methods, while others have only been loosely addressed. Here, we show how multilevel hypernetworks comprise an innovative methodological framework that can successfully capture key properties of synergies, clarifying conceptual issues concerning team collective behaviours based on team synergy formation. Therefore, this study investigated whether different synergy properties could be operationally related utilising hypernetworks. Thus, we constructed a multilevel model composed of three levels of analysis. Level N captured changes in tactical configurations of teams during competitive performance. While Team A changed from an initial 1-4-3-3 to a 1-4-4-2 tactical configuration, Team B altered the dynamics of the midfielders. At Level N + 1, the 2 vs. 1 (1 vs. 2) and 1 vs. 1 were the most frequently emerging simplices, both behind and ahead of the ball line for both competing teams. Level N + 2 allowed us to identify the prominent players (a6, a8, a12, a13) and their interactions, within and between simplices, before a goal was scored. These findings showed that different synergy properties can be assessed through hypernetworks, which can provide a coherent theoretical understanding of competitive team performance.

A multilevel hypernetworks approach to capture meso-level synchronisation processes in football

Understanding team behaviours in sports performance requires understanding the interdependencies established between their levels of complexity (micro-meso-macro). Previously, most studies examined interactions emerging at micro- and macro-levels, thus neglecting those emerging at a meso-level (reveals connections between player and team levels, depicted by the emergence of coordination in specific sub-groups of players-simplices during performance). We addressed this issue using the multilevel hypernetworks approach, adopting a cluster-phase method, to record player-simplice synchronies in two performance conditions where the number, size and location of goals were manipulated (first-condition: 6 × 6 + 4 mini-goals; second-condition: Gk + 6 × 6 + Gk). We investigated meso-level coordination tendencies, as a function of ball-possession (attacking/defending), field-direction (longitudinal/lateral) and teams (Team A/Team B). Generally, large synergistic relations and more stable patterns were observed in the longitudinal direction of the field than the lateral direction for both teams, and for both game phases in the first condition. The second condition displayed higher synchronies and more stable patterns in the lateral direction than the longitudinal plane for both teams, and for both game phases. Results suggest: (i) usefulness of hypernetworks in assessing synchronisation of teams at a meso-level; (ii) coaches may consider manipulating these task constraints to develop levels of local synchronies within teams.

Quantifying Collective Performance in Rugby Union

Objectives: The aim of this study was to quantify collective experience based on cumulative shared selections of players and to assess its impact on team performance in international rugby union. We assume that the greater the experience, the better the group will perform. Methods: Scoresheets of all games involving at least one of all 10 nations participating at the Rugby Championship and the Six Nations Championship were collected from the end of the 1999 Rugby World Cup (RWC) up to the 2015 RWC. A single indicator quantifying the cumulative shared selections (CSS, the number of selections that each player has shared with the other ones) was computed for each match as a key collective experience indicator. The World Rugby Ranking points of each nation and the percentage of victories were used to estimate team performance. The study period was divided into sequences of 4 years corresponding to the period between two consecutive RWCs. For each sequence and nation, slopes and intercept of CSS trends were computed along with victory percentage and mean ranking points. Multiple linear regression analysis was used to establish the associations between team performance and experience. Results: In regards to the CSS trends, both intra- and inter-nation variability appears to exist. Positive and negative slopes can be observed for the same team from one 4-year cycle to the next. Still, CSS slope is found to be significantly associated with both ranking points (p value = 0.042, R ² = 0.13) and victory percentage (p value = 0.001, R ² = 0.42). Conclusion: The evolution of the CSS that quantifies the collective experience of a team is linked to its performance. Such an indicator could be helpful in the decision-making process of national coaching staff.

Exploiting Bi-Directional Self-Organizing Tendencies in Team Sports: The Role of the Game Model and Tactical Principles of Play

Research has revealed how inherent self-organizing tendencies in athletes and sports teams can be exploited to facilitate emergence of dynamical patterns in synergy formation in sports teams. Here, we discuss how game models, and associated tactical principles of play, may be implemented to constrain co-existing global-to-local and local-to-global self-organization tendencies in team sports players during training and performance. Understanding how to harness the continuous interplay between these co-existing, bi-directional, and coordination tendencies is key to shaping system behaviors in sports training. Training programs are traditionally dominated by designs, which shape the self-organizing tendencies of players and teams at a global-to-local scale by coaches imposing a tactical/strategical plan with associated tactical principles of play. Nevertheless, recent research suggests that performers also need to be provided with opportunities to explore self-organizing tendencies that emerge at the local-to-global scale in training. This directional tendency in synergy formation can be facilitated by players being given opportunities to actively explore different adaptive and innovative performance solutions, coherent with principles of play circumscribed in an overarching game model. Developing methods (coaching sessions rooted on principles of dynamical systems theory that foment the development of such local-to-global relations) to exploit the continuous interplay between these co-existing tendencies within sports teams may promote more effective and efficient athlete skill training programs, in addition to enhancing performance.

Play-by-Play Network Analysis in Football

This study identifies dominant and intermediary players in football by applying a play-by-play social network analysis (SNA) on 70 professional matches from the 1. and 2. German Bundesliga during the 2017/2018 season. SNA provides a quantification of the complex interaction patterns between players in team sports. So far, the individual contributions and roles of players in football have only been studied at match-level considering the overall passing of a team. In order to consider the real structure of football, a play-by-play network analysis is needed that reflects actual interplay. Moreover, a distinction between plays of certain characteristics is important to qualify different interaction phases. As it is often impossible to calculate well known network metrics such as betweenness on play-level, new adequate metrics are required. Therefore, flow betweenness is introduced as a new playmaker indicator on play-level and computed alongside flow centrality. The data on passing and the position of players was provided by the Deutsche Fußball Liga (DFL) and gathered through a semi-automatic multiple-camera tracking system. Central defenders are identified as dominant and intermediary players, however, mostly in unsuccessful plays. Offensive midfielders are most involved and defensive midfielders are the main intermediary players in successful plays. Forward are frequently involved in successful plays but show negligible playmaker status. Play-by-play network analysis facilitates a better understanding of the role of players in football interaction.

Training programme designs in professional team sport: An ecological dynamics exemplar

Ecological dynamics is a contemporary theory of skill acquisition, advocating the mutuality of the performer-environment system, with clear implications for the design of innovative training environments in elite sport. It contends that performance behaviours emerge, and are adapted, by athletes satisfying a confluence of constraints impacting on their structural and functional capacities, the physics of a performance environment and the intended task goals. This framework implicates contemporary models of coaching, training design and sport science support, to stimulate continuous interactions between an individual and performance environment, predicated on representative learning designs (RLD). While theoretical principles of RLD in ecological dynamics are tangible, their practical application in elite and high level (team) sports need verification. Here, we exemplify how data sampled from a high-performance team sport setting could underpin innovative methodologies to support practitioners in designing representative training activities. We highlight how the use of principles grounded within ecological dynamics, along with data from performance analytics, could suggest contemporary models of coaching and preparation for performance in elite sport.

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.