Exploring the determinants of success in different clusters of ball possession sequences in soccer.

The purpose of this study was two-step: (1) classify ball possession (BP) according to the duration and number of passes and (2) identify which tactical variables most discriminate the different BP. We obtained 527 BPs from four official matches of the Brazilian Soccer Championship 2016. Forty-one "notational", "space occupation", and "displacement synchronization" predictor variables were used. The BPs were classified into three groups: short (11.07 ± 4.49 s, 1.93 ± 0.99 passes), medium (26.83 ± 7.33 s, 5.41 ± 1.84 passes), long (55.50 ± 14.97 s, 12.11 ± 4.61 passes). Discriminant analysis identified the five most relevant variables to describe each group: coefficient of variation (CV) of the defensive team's synchronization-Y, CV defensive team´s synchronization-X, successful pass last third, CV distance between offensive team's centroid and target, mean of the offensive team's width. The approach highlights important variables and could benefit the description of offensive and defensive game sequences to provide precise knowledge on the process.

Dribbling speed along curved paths predicts attacking performance in match-realistic one vs. one soccer games.

This study assessed whether a new, closed-skill dribbling or sprinting task could predict attacking performance in soccer. Twenty-five male players were recruited from the Londrina Junior Team Football Academy in Brazil and asked to either dribble the ball or sprint through five custom circuits that varied in average curvature (0-1.37 radians.m-1). These measures were then validated using a realistic one vs. one competition in which each player acted as attacker or defender in turn (N = 1330 bouts). Sprinting (ICC = 0.96) and dribbling (ICC = 0.97) performances were highly repeatable for individual players. Average dribbling speed decreased non-linearly with increasing circuit curvature (F = 239.5; P < 0.001) from 5.19 ± 0.11 ms-1 on the straightest path to 2.13 ± 0.03 ms-1 on the curviest. Overall, dribbling but not sprinting performance predicted attacking success in the one vs. one competition, explaining more than 50% of the variation in attacking success alone (rp = 0.70; P < 0.001). In conclusion, our new closed-skill dribbling assessment is a valid and reliable protocol to predict a soccer player's success in attacking performance in one vs. one situation, and can be used to identify talented players.

Tethered Swimming for the Evaluation and Prescription of Resistance Training in Young Swimmers.

The aims of the present study were 1) to evaluate the effects of 11 weeks of a typical free-swimming training program on aerobic and stroke parameters determined in tethered swimming (Study 1; n=13) and 2) to investigate the responses of tethered swimming efforts, in addition to free-swimming sessions, through 7 weeks of training (Study 2; n=21). In both studies, subjects performed a graded exercise test in tethered swimming (GET) to determine anaerobic threshold (AnT), stroke rate at AnT (SRAnT), peak force at GET (PFGET) and peak blood lactate ([La-]GET). Participants also swam 100-, 200- and 400-m lengths to evaluate performance. In Study 2, swimmers were divided into control (i. e., only free-swimming; GC [n=11]) and tethered swimming group (i. e., 50% of the main session; GTS [n=10]). The results of Study 1 demonstrate that AnT, PFGET, [La-]GET and 200-m performance were improved with free-swimming training. The SRAnT decreased with training. In Study 2, free-swimming performance and most of the graded exercise test parameters were not altered in either group. However, [La-]GET improved only for GTS. These results demonstrate that aerobic parameters obtained in tethered swimming can be used to evaluate free-swimming training responses, and the addition of tethered efforts during training routine improves the lactate production capacity of swimmers.

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.

Erratum for the article by Caetano et al. JAB 31(6).

In the article by Caetano FG, et al, "Characterization of the Sprint and Repeated-Sprint Sequences Performed by Professional Futsal Players, According to Playing Position, During Official Matches," in the J Appl Biomech, 31(6), pp. 423-429, http://dx.doi.org/10.1123/jab.2014-0159, the second author's name was incorrectly listed as Murilo José de Oliveira. The second author's name should have been listed as Murilo José de Oliveira Bueno.

Dominant-non-dominant asymmetry of kicking a stationary and rolling ball in a futsal context.

The aim of this study was to analyse the characteristics of the asymmetries in the dominant and non-dominant limbs when kicking stationary and rolling balls. Ten experienced Brazilian amateur futsal players participated in this study. Each participant performed kicks under two conditions (stationary ball vs. rolling ball) with the dominant and non-dominant limbs (five kicks per condition per limb). We analysed the kicking accuracy, ball and foot velocities, angular joint displacement and velocity. The asymmetry between the dominant and non-dominant limbs was analysed by symmetry index and two-way repeated measures ANOVA. The results did not reveal any interaction between the condition and limb for ball velocity, foot velocity and accuracy. However, kicking with the dominant limb in both kicks showed higher ball velocity (stationary ball: dominant - 24.27 ± 2.21 m · s(-1) and non-dominant - 21.62 ± 2.26 m · s(-1); rolling ball: dominant - 23.88 ± 2.71 m · s(-1) and non-dominant - 21.42 ± 2.25 m · s(-1)), foot velocity (stationary ball: dominant - 17.61 ± 1.87 m · s(-1) and non-dominant - 15.58 ± 2.69 m · s(-1); rolling ball: dominant - 17.25 ± 2.26 m · s(-1) and non-dominant - 14.77 ± 2.35 m · s(-1)) and accuracy (stationary ball: dominant - 1.17 ± 0.84 m and non-dominant - 1.56 ± 1.30 m; rolling ball: dominant - 1.31 ± 0.91 m and non-dominant - 1.97 ± 1.44 m). In addition, the angular joint adjustments were dependent on the limb in both kicks (the kicks with non-dominant limb showed lower hip external rotation than the kicks with the dominant limb), indicating that the hip joint is important in kick performance. In conclusion, the kicks with the non-dominant limb showed different angular adjustments in comparison to kicks with the dominant limb. In addition, kicking a rolling ball with the non-dominant limb showed higher asymmetry for accuracy, indicating that complex kicks are more asymmetric.

Characterization of the Sprint and Repeated-Sprint Sequences Performed by Professional Futsal Players, According to Playing Position, During Official Matches.

The purposes of this study were to investigate sprints and to characterize repeated-sprint sequences (RS) performed by athletes during professional futsal matches. We analyzed 97 players during 5 official matches using the DVideo automatic tracking system. The sprints were analyzed during the first and second halves according to playing position, and RS were categorized according to the number of sprints and the time between them. The results showed an increase (F[1, 2520] = 3.96; P = .046) in the sprint duration from the first (mean = 3.1 ± 1.3) to the second half (mean = 3.2 ± 1.2). However, no differences were found for other variables (distance covered, peak velocity, initial velocity, recovery time between sprints, and sprints performed per minute) or among playing positions. In addition, when considering RS, the results showed that RS comprising two sprints interspersed with a maximum of 15 seconds of recovery were significantly more frequent than other RS. The findings of this study characterizing the sprinting features of futsal players can help coaches to plan physical training and assessments according to the requirements of the sport.

Analysis of football game-related statistics using multivariate techniques.

Abstract The purpose of this study was to explore football game-related statistics during a competition, using principal component and cluster analyses to determine if it is possible to distinguish the winning teams from the drawing and losing ones. We collected the game-related statistics of the group phase matches of the 2006 World Cup and organised them into a matrix. The principal components of the covariance matrix were calculated. The scores of the first and second components were used to represent the new data, and cluster analysis was applied to separate the elements in two groups (G1 and G2). To analyse the degree of separation between the groups, we calculated the Silhouette Coefficient for each group. Finally, we checked if the winning teams were classified into the same group. The Silhouette Coefficients found for G1 and G2 were 0.54 and 0.55, respectively. Results showed that 70.3% of the winning teams were classified into the same group (G1). Similarly, 67.8% of the drawing and losing teams were classified in G2. This study presented a different way to analyse game-related statistics that allowed the multivariate differences to be shown between successful and unsuccessful teams.

Analysis of the distance covered by Brazilian professional futsal players during official matches.

The purpose of this study was to measure and characterise the distances covered by Brazilian professional futsal players. The trajectories of 93 players during five matches were obtained using an automatic tracking method. The distances covered were analysed for different game conditions: over the entire game and during the times when the ball was out of play and in play separately. When the entire game was considered, the results showed that there was a reduction in the total distance covered per minute from the first [median ± IQR (interquartile range): 97.9 ± 16.2 m/min] to the second half (median = 90.3 m/min; IQR = 12.0), and when only the in-play time was considered (first half: 136.6 ± 17.2 m/min; second half: 129.2 ± 16.7 m/min). The percentage of distance covered in the standing and walking velocity range was higher in the second half than in the first when considering the entire game (30.8% and 28.0%, respectively) and during the in-play time (19.3% and 16.2%, respectively). In conclusion, this study verified that futsal players reduced the physical performance during the second half.

Who are the best passing players in professional soccer? A machine learning approach for classifying passes with different levels of difficulty and discriminating the best passing players.

The present study aimed to assess the use of technical-tactical variables and machine learning (ML) classifiers in the automatic classification of the passing difficulty (DP) level in soccer matches and to illustrate the use of the model with the best performance to distinguish the best passing players. We compared eight ML classifiers according to their accuracy performance in classifying passing events using 35 technical-tactical variables based on spatiotemporal data. The Support Vector Machine (SVM) algorithm achieved a balanced accuracy of 0.70 ± 0.04%, considering a multi-class classification. Next, we illustrate the use of the best-performing classifier in the assessment of players. In our study, 2,522 pass actions were classified by the SVM algorithm as low (53.9%), medium (23.6%), and high difficulty passes (22.5%). Furthermore, we used successful rates in low-DP, medium-DP, and high-DP as inputs for principal component analysis (PCA). The first principal component (PC1) showed a higher correlation with high-DP (0.80), followed by medium-DP (0.73), and low-DP accuracy (0.24). The PC1 scores were used to rank the best passing players. This information can be a very rich performance indication by ranking the best passing players and teams and can be applied in offensive sequences analysis and talent identification.

Exploring the recurrent states of football teams' tactical organization on the pitch during Brazilian official matches.

Football teams' tactical organization on the pitch is usually represented by the surface area. Considering the different shapes adopted by the teams during the match, the role of the tactical variability for success is lacking. The aim of this study was to explore and to evaluate the association between recurrent states of tactical organization and technical performance during football matches. A total of 28 teams of Brazilian First Division Championships were analysed. Teams' surface area shapes were represented by the maximum value of the Multiscale Fractal Dimension in each timestamp, producing a time series. Recurrences of states of tactical organization were determined via recurrence plots and recurrence quantitative analysis during attacking and defending phases, and considering the whole match. The outcomes were correlated with nine traditional technical performance indicators. The main results showed that structural recurrence or variability on tactical organization is associated with performance success during the defending and attacking actions. Recurrence plot and measures based on the recurrence density proved to be valuable tools to represent teams' dynamics.

Acute responses of biomechanical parameters to different sizes of hand paddles in front-crawl stroke.

This study investigated the acute effects of different sizes of paddles on the force-time curve during tethered swimming and swimming velocity in front-crawl stroke. Fourteen male swimmers (20.0 ± 3.7 years; 100-m best time: 53.70 ± 0.87 s) performed two 10-s maximal efforts in tethered swimming to obtain peak force, average force, impulse, rate of force development, stroke duration and time to peak force. Swimming velocity, stroke rate and stroke length were obtained from two 25-m maximal swims. Both tests were repeated in five conditions: free swimming, wearing small (280 cm (2) ), medium (352 cm (2) ), large (462 cm (2) ) and extra-large (552 cm (2) ) hand paddles. Compared to free swimming, paddles provided significant increases of peak force (medium: 11.5%, large: 16.7%, extra-large: 21.7%), impulse (medium: 15.2%, large: 22.4%, extra-large: 30.9%), average force (medium: 5.1%, large: 7.5%), rate of force development (extra-large: 11.3%), stroke duration (medium: 9.3%, large: 11.8%, extra-large: 18.5%), time to peak force (medium: 11.1%, large: 15.9%, extra-large: 22.1%), swimming velocity (medium: 2.2%, large: 3.2%, extra-large: 3.7%) and stroke length (medium: 9.0%, large: 9.0%, extra-large: 14.8%), while stroke rate decreased (medium: -6.2%, large: -5.5%, extra-large: -9.5%). It is concluded that medium, large and extra-large paddles influence the force-time curve and change swimming velocity, suggesting these sizes may be useful for force development in water.

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.

Interpersonal coordination of opposing player dyads during attacks performed in official football matches.

The purpose of this study was to characterise the interpersonal coordination between opponent players during offensive sequences in official matches and to verify if offensive sequences ended in shots to goal present different coordination patterns when compared than those that ended in defensive tackles. A total of 580 offensive sequences occurred during matches resulting in shots to goal (n = 172) or defensive tackles (n = 408) were analysed. The bidimensional coordinates and technical actions of male professional football players (n = 1160) were obtained using a video-based tracking system. Dyads were defined using a network analysis and composed of the nearest opponent. Interpersonal coordination of the dyads was analysed using the vector coding and the frequency for each coordination pattern was computed. In-phase was predominant for all displacement directions and offensive sequences outcomes, and antiphase was the least frequent. For lateral displacements, offensive sequences ending in shot to goal presented lower frequency for in-phase and higher frequency for offensive player phase than ended in defensive tackle. This information about the relationship of opponent players dyads during decisive moments of the matches provides fundamentals for future research and assists coaches to understand the different behaviours in successful and unsuccessful attacks.

Quantitative analysis of Brazilian football players' organisation on the pitch.

The purpose of this study was to characterise Brazilian teams' coverage area and spread on the pitch while attacking and defending and to analyse the teams' organisation in tackle and shot on goal situations. We obtained the trajectories of 223 players in eight games with a tracking method. Team area was defined as the area of the convex hull formed by players' positions. Team spread was defined as the Frobenius norm of the distance-between-player matrix. We calculated teams' area and spread over time and in situations of shots on goal (n = 233) and tackles (n = 1897). While the players attacked, spread and area (median +/- confidence interval) ranged from 322.9 +/- 0.8 to 387.8 +/- 1.0 m and from 905.4 +/- 4.4 to 1407.6 +/- 5.5 m2, respectively. On defence, the values were smaller (p < 0.05) and ranged from 283.4 +/- 0.9 to 325.8 +/- 0.9 m and from 773.8 +/- 4.6 to 1158.4 +/- 5.5 m2 for the spread and the area. In defending circumstances, the teams presented a greater area and spread when they suffered shots on goal than when the teams performed tackles. In attacking situations, the teams presented a greater area and spread when they suffered tackles than when they performed shots on goal. The results allowed showing the attacking-defending interaction between Brazilian teams.

Classification and determinants of passing difficulty in soccer: a multivariate approach.

INTRODUCTION: Usually, the players' or teams' efficiency to perform passes is measured in terms of accuracy. The degree of difficulty of this action has been overlooked in the literature. OBJECTIVES: The present study aimed to classify the degree of passing difficulty in soccer matches and to identify and to discuss the variables that most explain the passing difficulty using spatiotemporal data. RESULTS: The data used corresponds to 2,856 passes and 32 independent variables. The Fisher Discriminant Analysis presented 72.0% of the original grouped cases classified correctly. The passes analyzed were classified as low (56.5%), medium (22.6%), and high difficulty (20.9%), and we identified 16 variables that best explain the degree of passing difficulty related to the passing receiver, ball trajectory, pitch position and passing player. CONCLUSIONS: The merit and ability of the player to perform passes with high difficulty should be valued and can be used to rank the best players and teams.In addition, the highlighted variables should be looked carefully by coaches when analyzing profiles, strengths and weaknesses of players and teams, and talent identification context. PRACTICAL IMPLICATIONS: The values found for each variable can be used as a reference for planning training, such as small side games, and in future research.

Penalty feet positioning rule modification and laterality effect on soccer goalkeepers' diving kinematics.

In 2019, a new rule was applied in soccer. It allows the goalkeeper to have only one foot or part of it on the goal line when the kicker hits the ball, unlike the previous rule that determined the goalkeeper should have both feet on the line. The purpose of the present study was to analyze how the change in the rule and the lower limbs laterality influences on the diving save kinematic performance in penalties. Six goalkeepers, two professionals and four amateurs, performed a total of 20 dives in the laboratory and had their force and impulse exerted by the lower limb and displacement/velocity data from the center of body mass collected through force plates and kinematic analysis. The side preference was collected through an inventory. The results showed that goalkeepers dive further (p < 0.001) and faster (p < 0.001) when diving according to the new rule. Dives for the non-dominant side presented higher values than the trials for the dominant side in mediolateral (p = 0.02) and resultant (p = 0.03) displacements. Concluding, the goalkeepers performed better with the new rule in the analyzed variables and the lower limb preference has influenced only the mediolateral and resultant displacement.

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.

Football player dominant region determined by a novel model based on instantaneous kinematics variables.

Dominant regions are defined as regions of the pitch where a player can reach before any other and are commonly determined without considering the free-spaces in the pitch. We presented an approach to football players' dominant regions analysis, based on movement models created from players' positions, displacement, velocity, and acceleration vectors. 109 Brazilian male professional football players were analysed during official matches, computing over 15 million positional data obtained by video-based tracking system. Movement models were created based on players' instantaneous vectorial kinematics variables, then probabilities models and dominant regions were determined. Accuracy in determining dominant regions by the proposed model was tested for different time-lag windows. We calculated the areas of dominant, free-spaces, and Voronoi regions. Mean correct predictions of dominant region were 96.56%, 88.64%, and 72.31% for one, two, and three seconds, respectively. Dominant regions areas were lower than the ones computed by Voronoi, with median values of 73 and 171 m2, respectively. A median value of 5537 m2 was presented for free-space regions, representing a large part of the pitch. The proposed movement model proved to be more realistic, representing the match dynamics and can be a useful method to evaluate the players' tactical behaviours during matches.

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.