Quantitative analysis of Brazilian football players' organisation on the pitch

The Success Factors of Rest Defense in Soccer - A Mixed-Methods Approach of Expert Interviews, Tracking Data, and Machine Learning

While the tactical behavior of soccer players differs between specific phases of play (offense, defense, offensive transition, defensive transition), little is known about successful behavior of players during defensive transition (switching behavior from offense to defense). Therefore, this study aims to analyze the group tactic of rest defense (despite in ball possession, certain players safeguard quick counterattacks in case of ball loss) in defensive transition. A mixed-methods approach was used, involving both qualitative and quantitative analysis. Semi-structured expert interviews with seven professional soccer coaches were conducted to define rest defense. In the quantitative analysis, several KPIs were calculated, based on tracking and event data of 153 games of the 2020/21 German Bundesliga season, to predict the success of rest defense situations in a machine learning approach. The qualitative interviews indicated that rest defense can be defined as the positioning of the deepest defenders during ball possession to prevent an opposing counterattack after a ball loss. For instance, the rest defending players created a numerical superiority of 1.69 ± 1.00 and allowed a space control of the attacking team of 11.51 ± 9.82 [%] in the area of rest defense. The final machine learning model showed satisfactory prediction performance of the success of rest defense (Accuracy: 0.97, Precision: 0.73, f1-Score: 0.64, AUC: 0.60). Analysis of the individual KPIs revealed insights into successful behavior of players in rest defense, including controlling deep spaces and dangerous counterattackers. The study concludes regaining possession as fast as possible after a ball loss is the most important success factor in defensive transition.

The Qatar 2022 World Cup warm-up: Football goal-scoring evolution in the last 14 FIFA World Cups (1966-2018)

The aim of this study was to elucidate pattern of attacking actions leading up to goal scoring during the 14 FIFA World Cups from 1966 to 2018. The study analysed 1881 goals scored during a total of 732 matches. We employed observational methodology design. Before goal analysis began, it was developed the observing protocol in which data related to selected variables, by system of notation, was entered after reviewing each individual goal scoring action. The analysis of all video material was carried out independently by four experienced examiners (three of them are Ph.D in sports science and one is Ph.D. candidate in sports science with at least 7 years of coaching and experience as analyst in football). The inter-and intra-observer reliability presented good level of agreement. The kappa values ranged from 0.82 (goal scoring through open play) to 1.00 (action leading up to goal), showing a very high agreement for all performance variables. Interclass correlation was very high (ICC = 0.966, 95% upper and lower confidence intervals were between 0.933 and 1.00). A statistically significant trend (p < 0.05) from 1966 to 2018 was identified towards a higher relative frequency of goals scored from set play and collective actions from open play. The Chi-square did not reveal significant differences in the frequency of goal scoring patterns and goal-scoring zones. The results also revealed that the majority of goals were scored between the 76th and 90th minutes of a match (22.7%), from open play (70.5%), inside the penalty area (54.7%), one touch finishing (62.5%), and collective attacks in open play (55.8%). These findings may provide a possible strategic direction for improving goal-scoring performance in football, as well as practical implementation in World Cup tournament preparation.

The Qatar 2022 World Cup warm-up: Football goal-scoring evolution in the last 14 FIFA World Cups (1966-2018)

The aim of this study was to elucidate pattern of attacking actions leading up to goal scoring during the 14 FIFA World Cups from 1966 to 2018. The study analysed 1881 goals scored during a total of 732 matches. We employed observational methodology design. Before goal analysis began, it was developed the observing protocol in which data related to selected variables, by system of notation, was entered after reviewing each individual goal scoring action. The analysis of all video material was carried out independently by four experienced examiners (three of them are Ph.D in sports science and one is Ph.D. candidate in sports science with at least 7 years of coaching and experience as analyst in football). The inter-and intra-observer reliability presented good level of agreement. The kappa values ranged from 0.82 (goal scoring through open play) to 1.00 (action leading up to goal), showing a very high agreement for all performance variables. Interclass correlation was very high (ICC = 0.966, 95% upper and lower confidence intervals were between 0.933 and 1.00). A statistically significant trend (p < 0.05) from 1966 to 2018 was identified towards a higher relative frequency of goals scored from set play and collective actions from open play. The Chi-square did not reveal significant differences in the frequency of goal scoring patterns and goal-scoring zones. The results also revealed that the majority of goals were scored between the 76th and 90th minutes of a match (22.7%), from open play (70.5%), inside the penalty area (54.7%), one touch finishing (62.5%), and collective attacks in open play (55.8%). These findings may provide a possible strategic direction for improving goal-scoring performance in football, as well as practical implementation in World Cup tournament preparation.

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.

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.

How spatial constraints afford successful and unsuccessful penetrative passes in elite association football

BACKGROUND

The aim of the present study was to examine the spatial relations between teams (macro-level) and groups of players (meso-level) that afford successful penetrative passes (off-ball advantage) in elite football.

METHODS

Three balanced home matches from a Premier League team with 91 ball possessions in which a pass was performed into the opposition defensive area and overpassed the first defensive line, promoting a perturbation of the defensive team equilibrium, were selected for analysis. The spatial relations between teams were measured through spatial variables that captured the areas occupied by the teams, while the spatial relations between players were measured through variables that captured the distances and angles between attacking and defending players near the ball.

RESULTS

Results revealed, at the macro-level, higher values of width ratio between teams and the width of the attacking team for unsuccessful penetrative passes (UPP), when compared to successful penetrative passes (SPP). At the meso-level, a general decrease in distances and an increase in angles between attacking and defending players were observed between successful to unsuccessful penetrative passes.

CONCLUSIONS

These findings highlight the importance of using positional data analysis to identify teams' tactical profiles and to potentiate coaches' interventions.

The impact of COVID-19 lockdown on soccer positional and physical demands in the Spanish La Liga

The present study aimed to analyse the playing surface area, dispersion and distance covered of professional football teams comparing the pre-lockdown and the post- lockdown periods. Positional and match physical demands data were collected from all matches played in the First Spanish Division (n = 760) during season 2019/2020. Pre-lockdown (1^st - 27^th matchday) and post-lockdown period (28^th - 38^th matchday) were compared. Variables related to team-level spatial (i.e., convex hull, team width and team length) and physical performance (i.e., total distance and high-speed running distance) were analysed using an optical tracking system (i.e., ChyronHego). In addition, these variables were concerning in respect to the match location contextual variable. Linear mixed models were used to examine the difference between the pre-lockdown and post- lockdown periods following a hierarchical structure considering players, matches and teams. The results revealed that the pandemic lockdown affected the teams' performance when comparing the periods before and after lockdown, showing a general decrease in the average values of the spatial and physical variables measured. The current data could assist practitioners in making informed decisions in order to design and improve training plans for similar situations in which teams return to competition after an unusual period with no training.

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.

The "Hockey" Assist Makes the Difference-Validation of a Defensive Disruptiveness Model to Evaluate Passing Sequences in Elite Soccer

With the growing availability of position data in sports, spatiotemporal analysis in soccer is a topic of rising interest. The aim of this study is to validate a performance indicator, namely D-Def, measuring passing effectiveness. D-Def calculates the change of the teams' centroid, centroids of formation lines (e.g., defensive line), teams' surface area, and teams' spread in the following three seconds after a pass and therefore results in a measure of disruption of the opponents' defense following a pass. While this measure was introduced earlier, in this study we aim to prove the usefulness to evaluate attacking sequences. In this study, 258 games of Dutch Eredivisie season 2018/19 were included, resulting in 13,094 attacks. D-Def, pass length, pass velocity, and pass angle of the last four passes of each attack were calculated and compared between successful and unsuccessful attacks. D-Def showed higher values for passes of successful compared to unsuccessful attacks (0.001 < p ≤ 0.029, 0.06 ≤ d ≤ 0.23). This difference showed the highest effects sizes in the penultimate pass (d = 0.23) and the maximal D-Def value of an attack (d = 0.23). Passing length (0.001 < p ≤ 0.236, 0.08 ≤ d ≤ 0.17) and passing velocity (0.001 < p ≤ 0.690, -0.09 ≤ d ≤ 0.12) showed inconsistent results in discriminating between successful and unsuccessful attacks. The results indicate that D-Def is a useful indicator for the measurement of pass effectiveness in attacking sequences, highlighting that successful attacks are connected to disruptive passing. Within successful attacks, at least one high disruptive action (pass with D-Def > 28) needs to be present. In addition, the penultimate pass ("hockey assist") of an attack seems crucial in characterizing successful attacks.

Multiscale fractal dimension applied to tactical analysis in football: A novel approach to evaluate the shapes of team organization on the pitch

The aim of this study was to evaluate different shape descriptors applied to images of polygons that represent the organization of football teams on the pitch. The effectiveness of different shape descriptors (area/perimeter, fractal area, circularity, maximum fractal, rectangularity, multiscale fractal curve—MFC), and the concatenation of all shape descriptors (except MFC), denominated Alldescriptors (AllD)) was evaluated and applied to polygons corresponding to the shapes represented by the convex hull obtained from players’ 2D coordinates. A content-based image retrieval system (CBIR) was applied for 25 users (mean age of 31.9 ± 8.4 years) to evaluate the relevant images. Measures of effectiveness were used to evaluate the shape descriptors (P@n and R@n). The MFD (P@5, 0.46±0.37 and P@10, 0.40±0.31, p < 0.001; R@5, 0.14±0.13 and R@10, 0.24±0.19, p < 0.001) and AllD (P@5 = 0.43±0.36 and P@10 = 0.39±0.32, p < 0.001; R@5 = 0.13±0.11 and R@10 = 0.24±0.20, p < 0.001) descriptors presented higher values of effectiveness. As a practical demonstration, the best evaluated shape descriptor (MFC) was applied for tactical analysis of an official match. K-means clustering technique was applied, and different shapes of organization could be identified throughout the match. The MFC was the most effective shape descriptor in relation to all others, making it possible to apply this descriptor in the analysis of professional football matches.

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.

Training Design, Performance Analysis, and Talent Identification-A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby

Since the accelerating development of technology applied to team sports and its subsequent high amount of information available, the need for data mining leads to the use of data reduction techniques such as Principal Component Analysis (PCA). This systematic review aims to identify determinant variables in soccer, basketball and rugby using exploratory factor analysis for, training design, performance analysis and talent identification. Three electronic databases (PubMed, Web of Science, SPORTDiscus) were systematically searched and 34 studies were finally included in the qualitative synthesis. Through PCA, data sets were reduced by 75.07%, and 3.9 ± 2.53 factors were retained that explained 80 ± 0.14% of the total variance. All team sports should be analyzed or trained based on the high level of aerobic capacity combined with adequate levels of power and strength to perform repeated high-intensity actions in a very short time, which differ between team sports. Accelerations and decelerations are mainly significant in soccer, jumps and landings are crucial in basketball, and impacts are primarily identified in rugby. Besides, from these team sports, primary information about different technical/tactical variables was extracted such as (a) soccer: occupied space, ball controls, passes, and shots; (b) basketball: throws, rebounds, and turnovers; or (c) rugby: possession game pace and team formation. Regarding talent identification, both anthropometrics and some physical capacity measures are relevant in soccer and basketball. Although overall, since these variables have been identified in different investigations, further studies should perform PCA on data sets that involve variables from different dimensions (technical, tactical, conditional).

Identification, Computational Examination, Critical Assessment and Future Considerations of Spatial Tactical Variables to Assess the Use of Space in Team Sports by Positional Data: A Systematic Review

The aim of the review was to identify the spatial tactical variables used to assess the use of space in team sports using positional data. In addition, we examined computational methods, performed a critical assessment and suggested future considerations. We considered four electronic databases. A total of 3973 documents were initially retrieved and only 15 articles suggested original spatial variables or different computation methods. Spatial team sport tactical variables can be classified into 3 principal types: occupied space, total field coverage by several players; exploration space, the mean location (±standard deviations in X- and Y-directions) of the player/team during the entire game; and dominant/influence space, the region the players can reach before any other players. Most of the studies, i.e., 55%, did not include goalkeepers (GKs) and total playing space to assess occupied space, however, several proposed new variables that considered that all playing space could be “played” (i.e. effective free-space, normalized surface area). Only a collective exploration space variable has been suggested: the major range of the geometrical centre (GC). This suggestion could be applied to assess collective exploration space variables at a sub-system level. The measurement of the dominant/influence space has been based on the Voronoi region (i.e. distance d criteria), but several studies also based their computation on the time (t). In addition, several weighted dominant areas have been suggested. In conclusion, the use of spatial collective tactical variables considering the principal structural traits of each team sport (e.g. players of both teams, the location of the space with respect to the goal, and the total playing space) is recommended.

A systematic review of collective tactical behaviour in futsal using positional data

Although many studies on collective tactical behaviour have been published in the last decade, no study has revised and summarized the findings provided for futsal. The main aim of this systematic review was to identify and discuss the geometrical centre (GC), distance and area tactical variables used to assess team behaviour in futsal. In addition, it summarizes the findings on the tactical response during futsal competition and training. A systematic review of the relevant articles provided on futsal was carried out using seven electronic databases (SPORTDiscus, ProQuest, Cochrane Plus, Scopus, Google Scholar, PubMed and Web of Science) until September 25, 2019. From a total of 1,209 studies initially found, 12 were included in the qualitative synthesis. There were some trends in the analysis of positional data in futsal with the most relevant situations analysed being 1 vs 1 and 5 vs 4+Goalkeeper. The distances and angles between two points were the most assessed tactical variables. Five types of distance variables were used to assess collective tactical behaviour in futsal: GC-GC, GC-player, player-player, player-ball and player-space. Pressure (GC-GC) was greater in shots on goal than in tackles during professional futsal matches. Area variables were reduced to occupied space, exploration space and dominant area. Occupied space was measured only during competition while the dominant area was measured only during training sessions. The surface area and dominant regions were greater when players were attacking in comparison to when they were defending. In addition, two non-linear techniques (i.e. relative phase and entropy) were applied to analyse synchronisation and complexity and regularity or predictability. Defenders were highly synchronous, while attackers tried to break this coordination to achieve possibilities for action. Task constraints are suitable to induce different regularity patterns. This review is an opportunity to develop studies aimed at bridging the gap in collective tactical behaviour in futsal.

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.

Variability in tactical behavior of futsal teams from different categories

The aim of the present study was to analyze the time series of team spread during futsal official matches in the frequency domain for different categories. Using an automatic tracking method, trajectories of 258 players (excluding goalkeepers) were obtained, composed of 79 players from the under-15 (U15) category, 86 from the under-18 (U18), and 93 from the professional. We calculated the team spread defined as the Euclidean norm of the distance-between-player vector as a function of time. We applied the Fast Fourier Transformation method and calculated the median frequency for each time series of spread. The results of mean ± SD of the median frequency of the time series of spread from the first to the second half were significantly different only for the U15 category (first half, 1.04 ± 0.46, second half 1.40 ± 0.34). The frequency values differed significantly between the categories. The younger categories presented a higher frequency of spread oscillation than the professional category, which reflects the dynamics of the game between attack and defense sequences. The results provide insights into the features of the sport and present a basis for appropriate training interventions for players in each category, planning for future transition to the following category.

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.

Team Dynamics, Running, and Skill-Related Performances of Brazilian U11 to Professional Soccer Players During Official Matches

Palucci Vieira, LH, Aquino, R, Moura, FA, Barros, RMLd, Arpini, VM, Oliveira, LdP, Bedo, BLdS, and Pereira Santiago, PR. Team dynamics, running, and skill-related performances of Brazilian U11 to professional soccer players during official matches. J Strength Cond Res 33(8): 2202-2216, 2019-Analyses of movements during soccer competition have been used previously to help develop conditioning programs. However, this has not been extensively studied in youth populations. Therefore, the purposes of this study were to examine (1) dynamics of collective tactical movements, (2) running, and (3) skill-related performances during soccer matches disputed by children to senior players. A total of 120 Brazilian players in the age groups U11, U13, U15, U17, U20, and professional (PRO) were monitored during official competition matches (N = 12). Using semiautomatic video-based tracking (30 Hz), match running variables including total distance traveled, average speed, maximum sprint speed, and high-intensity activities were evaluated. Tactical metrics were computed as team surface area, spread, and median frequency. Through notational analysis, technical skills such as involvements with the ball, passes, ball touches, duels, and goal attempts were also recorded. One-way analysis of variance and magnitude-based inferences were used to detect differences between ages. Although the average speed, team surface area, and spread tended to present stabilized increases from the U15 (e.g., U15 > U13 > U11), maximal sprinting speed (PRO > U17 > U15, U13, U11) and percentage at very high-intensity activities (U20 > PRO, U17 > U15 > U13 > U11) demonstrated continuous gains. Median frequencies were higher in the younger groups (U13, U15, U17 > U20, PRO), although the percentage of successful passes was higher in the older groups (PRO > U17, U15 > U13, U11). We concluded that Brazilian U11 to PRO players present different performance profiles for running, collective movement dynamics, and technical skills, and that the rate of development regarding these components varies. Coaches should be aware of these differences to select and adapt training content for each age group.

Analysis of Match Dynamics of Different Soccer Competition Levels Based on the Player Dyads

The purpose of this study was to analyse the dynamics of play based on dyads during soccer matches, according to the competition level, period of the matches, and playing positions. We recorded eight Brazilian soccer matches (four of the national and four of the regional level), using up to six digital cameras (30 Hz). The position information of the 204 players in the eight matches was obtained using an automatic tracking system. The Euclidean distance between the nearest opponents was calculated over time to define the dyads. The interaction between the components of dyads was assessed by the distances between players and was compared among the different positions (defender, full-back, defensive midfielder, midfielder, and forward), match periods (15, 30, 45, 60, 75, and 90 min), and competition levels. Results showed smaller distances for the national level dyads, compared to the regional matches. Greater distances between the players were found in the last 15 minutes of the matches, compared to the other periods. The full-backs were more distant from opposing players compared to players from other playing positions. Thus, coaches should consider the characteristics of each playing position and the greater proximity between opponents’ players in top-level competition for the development of tactical proficiency of the players.

A comparison of match-physical demands between different tactical systems: 1-4-5-1 vs 1-3-5-2

The team tactical system and distribution of the football players on the pitch is considered fundamental in team performance. The present study used time-motion analysis and triaxial-accelerometers to obtain new insights about the impact of different tactical systems (1-4-5-1 and 1-3-5-2) on physical performance, across different playing positions, in a professional football team. Player performance data in fifteen official home matches was collected for analysis. The sample included twenty-two players from five playing positions (centre backs: n = 4; full-back/wide midfielder/ wing-back: n = 9; centre midfielder: n = 6 and centre forward: n = 3), making a total of 108 match observations. A novel finding was that general match physical demands do not differ considerably between these tactical formations, probably because match-to-match variability (variation of players’ running profile from match-to-match) might be higher than the differences in physical performance between tactical systems. However, change of formation had a different impact across playing positions, with centre backs playing in 1-4-5-1 performing significant more HIRcounts than in 1-3-5-2 (p = 0.031). Furthermore, a medium effect size (r = 0.33) was observed in HIRdist, with wide players covering higher distances when playing in 1-3-5-2 than in 1-4-5-1. These findings may help coaches to develop individualised training programs to meet the demands of each playing position according to the tactical system adopted.

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.

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.

How do futsal players of different categories play during official matches? A tactical approach to players' organization on the court from positional data

The purpose of this study was to analyze futsal players’ organization on the court in different categories while attacking and defending, in interception and shot to goal situations. We obtained the trajectories of 89 players from the under-15 category, 102 players from the under-18 category, and 110 professional players, during official matches. The spread, surface area, and Euclidian distances between the teams’ centroids were measured to represent the distribution of the futsal players on the court. The variables were analyzed during each offensive and defensive sequence, and during situations of shots to goal and interceptions, with and without the outfield goalkeeper player participation. While the players were attacking, all categories presented greater spread and surface area, compared to values when players were defending (P < 0.01). Among the categories, the results showed lower spread and area values for the younger players (P < 0.01). The results of spread, surface area, and distances between the teams’ centroids showed different forms of organization for each of the categories in specific situations of shots to goal and interceptions. The study provided insights that allow coaches to better plan suitable tactical training according to the requirements of each category.

Time-motion analysis of goalball players in attacks: differences of the player positions and the throwing techniques. Sports Biomech 2018;18:470-481. [PMID: 29578380 DOI: 10.1080/14763141.2018.1433871]

In this study, we aimed to analyse goalball players time-motion variables (distance covered, time spent, maximum and average velocities) in official goalball match attacks, taking into account the attack phases (preparation and throwing), player position (centres and wings) and throwing techniques (frontal, spin and between the legs). A total of 365 attacks were assessed using a video based method (2D) through manual tracking using the Dvideo system. Inferential non-parametric statistics were applied for comparison of preparation vs. throwing phase, wings vs. centres and, among the throwing techniques, frontal, spin and between the legs. Significant differences were found between the attack preparation versus the throwing phase for all player time-motion variables: distance covered, time spent, maximum player velocity and average player velocity. Wing players performed most of the throws (85%) and covered longer distances than centres (1.65 vs 0.31 m). The between the legs and the spin throwing techniques presented greater values for most of the time-motion variables (distance covered, time spent and maximum player velocity) than did the frontal technique in both attack phases. These findings provide important information regarding players' movement patterns during goalball matches that can be used to plan more effective training.

Analysis of high-intensity efforts in brazilian professional soccer players

Purpose. The study aim was to characterize high-intensity efforts (HIEs) of soccer players. Methods. The HIE features were quantified according to playing positions, with the consideration of the moment of initial velocity increase, which precedes the velocity threshold. The total of 107 players of Brazilian first division championship were analysed with the automatic tracking method. HIE phase 1 began at the minimum local value and finished when the velocity reached 6.4 m/s. Phase 2 began immediately when the velocity exceeded 6.4 m/s and finished with the velocity lower than 6.4 m/s. Results. External defenders and forwards performed a greater (p < 0.01; d: 1.01-1.17) number of HIEs (40.0 ± 13.5 and 34.9 ± 6.6, respectively) than central defenders (26.6 ± 9.2). With respect to the distance covered and duration of phase 2, external defenders covered a greater (p < 0.01; d: 0.45-0.47) distance (13.5 ± 4.5 m) and spent more (p < 0.01; d: 0.24-0.26) time (1.8 ± 1.3 s) than central defenders (11.5 ± 4.3 m; 1.5 ± 1.2 s), forwards (11.4 ± 4.4 m; 1.5 ± 0.9 s), central midfielders (11.5 ± 4.4 m; 1.5 ± 1.2 s), and external midfielders (11.4 ± 4.6 m; 1.5 ± 1.1 s). Players performed a greater (p = 0.03; d: 2.29-5.17) number of HIEs with more than 120 s of recovery time compared with other time categories. Conclusions. The better characterization of HIE physical demands during soccer matches provides insights for coaches to plan a more specific physical training for professional players.

What's in a game? A systems approach to enhancing performance analysis in football

Purpose

Performance analysis (PA) in football is considered to be an integral component of understanding the requirements for optimal performance. Despite vast amounts of research in this area key gaps remain, including what comprises PA in football, and methods to minimise research-practitioner gaps. The aim of this study was to develop a model of the football match system in order to better describe and understand the components of football performance. Such a model could inform the design of new PA methods.

Method

Eight elite level football Subject Method Experts (SME’s) participated in two workshops to develop a systems model of the football match system. The model was developed using a first-of-its-kind application of Cognitive Work Analysis (CWA) in football. CWA has been used in many other non-sporting domains to analyse and understand complex systems.

Result

Using CWA, a model of the football match ‘system’ was developed. The model enabled identification of several PA measures not currently utilised, including communication between team members, adaptability of teams, playing at the appropriate tempo, as well as attacking and defending related measures.

Conclusion

The results indicate that football is characteristic of a complex sociotechnical system, and revealed potential new and unique PA measures regarded as important by SME’s, yet not currently measured. Importantly, these results have identified a gap between the current PA research and the information that is meaningful to football coaches and practitioners.

Periodization Training Focused on Technical-Tactical Ability in Young Soccer Players Positively Affects Biochemical Markers and Game Performance

Aquino, RLQT, Cruz Gonçalves, LG, Palucci Vieira, LH, Oliveira, LP, Alves, GF, Pereira Santiago, PR, and Puggina, EF. Periodization training focused on technical-tactical ability in young soccer players positively affects biochemical markers and game performance. J Strength Cond Res 30(10): 2723-2732, 2016-The aim of this study was to investigate the effects of 22 weeks of periodized training, with an emphasis on technical-tactical ability, on indirect markers of muscle damage, and the on-field performance of young soccer players. Fifteen players (age 15.4 ± 0.2 years, height 172.8 ± 3.6 cm; body mass 61.9 ± 2.9 kg; % fat 11.7 ± 1.6; V[Combining Dot Above]O2max 48.67 ± 3.24 ml·kg·min) underwent 4 stages of evaluation: prepreparatory stage-T0; postpreparatory stage-T1; postcompetitive stage I-T2 and; postcompetitive stage II-T3. The plasmatic activity of creatine kinase (CK) and lactate dehydrogenase (LDH) were evaluated, as well as the on-field performance (movement patterns, tactical variables). Regarding the plasmatic activity of CK and LDH, there was a significant reduction (p ≤ 0.05) throughout the periodization training (T0: 350 U·L; T3: 150 U·L). Significant increases were observed (p ≤ 0.05) in the intensity of the game, high-intensity activities (HIA) (T0: 22%; T3: 27%), maximum speed (T0: 30 km·h; T3: 34 km·h) and tactical performance, team surface area (T0: 515 m; T3: 683 m), and spread (T0: 130 m; T3: 148 m). In addition, we found significant inverse correlations between the percentage variation of T0 to T3 in CK and LDH activities with percentage variation in high-intensity running (r = -0.85; p ≤ 0.05 and r = -0.84; p < 0.01, respectively) and HIA (r = -0.71 and r = -0.70; p ≤ 0.05, respectively) during the matches. We concluded that there was reduced activity in biochemical markers related to muscle damage, as well as increases in-game high-intensity performance and the tactical performance of the study participants. Furthermore, players who showed greater reduction in plasma activity of CK and LDH also obtained greater increases in-game high-intensity performance along the periodization. These results may contribute to the expansion and future consolidation of the knowledge of coaches and sport scientists to develop effective methodologies for training in soccer.

Team Synergies in Sport: Theory and Measures

Individual players act as a coherent unit during team sports performance, forming a team synergy. A synergy is a collective property of a task-specific organization of individuals, such that the degrees of freedom of each individual in the system are coupled, enabling the degrees of freedom of different individuals to co-regulate each other. Here, we present an explanation for the emergence of such collective behaviors, indicating how these can be assessed and understood through the measurement of key system properties that exist, considering the contribution of each individual and beyond These include: to (i) dimensional compression, a process resulting in independent degree of freedom being coupled so that the synergy has fewer degrees of freedom than the set of components from which it arises; (ii) reciprocal compensation, if one element do not produce its function, other elements should display changes in their contributions so that task goals are still attained; (iii) interpersonal linkages, the specific contribution of each element to a group task; and (iv), degeneracy, structurally different components performing a similar, but not necessarily identical, function with respect to context. A primary goal of our analysis is to highlight the principles and tools required to understand coherent and dynamic team behaviors, as well as the performance conditions that make such team synergies possible, through perceptual attunement to shared affordances in individual performers. A key conclusion is that teams can be trained to perceive how to use and share specific affordances, explaining how individual’s behaviors self-organize into a group synergy. Ecological dynamics explanations of team behaviors can transit beyond mere ratification of sport performance, providing a comprehensive conceptual framework to guide the implementation of diagnostic measures by sport scientists, sport psychologists and performance analysts. Complex adaptive systems, synergies, group behaviors, team sport performance, ecological dynamics, performance analysis.

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.

Coordination analysis of players' distribution in football using cross-correlation and vector coding techniques

The purpose of this study was to investigate the coordination between teams spread during football matches using cross-correlation and vector coding techniques. Using a video-based tracking system, we obtained the trajectories of 257 players during 10 matches. Team spread was calculated as functions of time. For a general coordination description, we calculated the cross-correlation between the signals. Vector coding was used to identify the coordination patterns between teams during offensive sequences that ended in shots on goal or defensive tackles. Cross-correlation showed that opponent teams have a tendency to present in-phase coordination, with a short time lag. During offensive sequences, vector coding results showed that, although in-phase coordination dominated, other patterns were observed. We verified that during the early stages, offensive sequences ending in shots on goal present greater anti-phase and attacking team phase periods, compared to sequences ending in tackles. Results suggest that the attacking team may seek to present a contrary behaviour of its opponent (or may lead the adversary behaviour) in the beginning of the attacking play, regarding to the distribution strategy, to increase the chances of a shot on goal. The techniques allowed detecting the coordination patterns between teams, providing additional information about football dynamics and players' interaction.

Analysis of Soccer Players' Positional Variability During the 2012 UEFA European Championship: A Case Study

The purpose of this study was to analyse players’ positional variability during the 2012 UEFA European Championship by applying principal component analysis (PCA) to data gathered from heat maps posted on the UEFA website. We analysed the teams that reached the finals and semi-finals of the competition. The players’ 2D coordinates from each match were obtained by applying an image-processing algorithm to the heat maps. With all the players’ 2D coordinates for each match, we applied PCA to identify the directions of greatest variability. Then, two orthogonal segments were centred on each player’s mean position for all matches. The segments’ directions were driven by the eigenvectors of the PCA, and the length of each segment was defined as one standard deviation around the mean. Finally, an ellipse was circumscribed around both segments. To represent player variability, segment lengths and elliptical areas were analysed. The results demonstrate that Portugal exhibited the lowest variability, followed by Germany, Spain and Italy. Additionally, a graphical representation of every player’s ellipse provided insight into the teams’ organisational features throughout the competition. The presented study provides important information regarding soccer teams’ tactical strategy in high-level championships that allows coaches to better control team organisation on the pitch.

Cognitive representations and cognitive processing of team-specific tactics in soccer

Two core elements for the coordination of different actions in sport are tactical information and knowledge about tactical situations. The current study describes two experiments to learn about the memory structure and the cognitive processing of tactical information. Experiment 1 investigated the storage and structuring of team-specific tactics in humans' long-term memory with regard to different expertise levels. Experiment 2 investigated tactical decision-making skills and the corresponding gaze behavior, in presenting participants the identical match situations in a reaction time task. The results showed that more experienced soccer players, in contrast to less experienced soccer players, possess a functionally organized cognitive representation of team-specific tactics in soccer. Moreover, the more experienced soccer players reacted faster in tactical decisions, because they needed less fixations of similar duration as compared to less experienced soccer players. Combined, these experiments offer evidence that a functionally organized memory structure leads to a reaction time and a perceptual advantage in tactical decision-making in soccer. The discussion emphasizes theoretical and applied implications of the current results of the study.

A spectral analysis of team dynamics and tactics in Brazilian football

The purposes of this study were to characterise the total space covered and the distances between players within teams over ten Brazilian First Division Championship matches. Filmed recordings, combined with a tracking system, were used to obtain the trajectories of the players (n = 277), before and after half-time. The team surface area (the area of the convex hull formed by the positions of the players) and spread (the Frobenius norm of the distance-between-player matrix) were calculated as functions of time. A Fast Fourier Transform (FFT) was applied to each time series. The median frequency was then calculated. The results of the surface area time series median frequencies for the first half (0.63 ± 0.10 cycles · min⁻¹) were significantly greater (P < 0.01) than the second-half values (0.47 ± 0.14 cycles · min⁻¹). Similarly, the spread variable median frequencies for the first half (0.60 ± 0.14 cycles · min⁻¹) were significantly greater (P < 0.01) than the second-half values (0.46 ± 0.16 cycles · min⁻¹). The median frequencies allowed the characterisation of the time series oscillations that represent the speed at which players distribute and then compact their team formation during a match. This analysis can provide insights that allow coaches to better control the team organisation on the pitch.