Lateral Preference and Inter-limb Asymmetry in Completing Technical Tasks During Official Professional Futsal Matches: The Role of Playing Position and Opponent Quality.

This study had the purpose of analyzing dominant and non-dominant limb performances (frequency of use and accuracy) during match-play technical actions with ball possession (receiving, passing, and shooting a ball) in professional futsal and also check for the possible influence of playing position and the quality of opponent. We have analyzed data pertaining to eight matches of the FIFA Futsal World Cup Thailand 2012™ in which 76 male professional senior futsal players participated (44 right-footed and 32 left-footed). In total, we coded 5,856 actions (2,550 ball receptions, 3,076 passes, and 230 shoots). Our main findings were that (a) players used the dominant limb more frequently than the non-dominant limb for all actions considered [p < 0.001; effect size (ES) medium-to-large]; (b) accuracy was generally greater when using the dominant limb, regardless of the quality of opponent (p < 0.01; ES large); and (c) in shooting actions, pivots showed similar accuracy between dominant and non-dominant limbs (p = 0.51; ES small). The study suggested that when completing technical actions with the ball in futsal, high-level players depended to a greater extent on the use of their dominant lower limb during official matches. Excepting a similarity detected between limbs on shooting performance of pivots, players from all positional roles generally showed a higher accuracy rate in receiving, passing, and shooting a ball when using their dominant limb as compared to their non-dominant one during match-play and the limb usage and accuracy seemed to be independent of the quality of opponents.

Dominant/non-dominant support limb kinematics and approach run parameters in futsal kicking of stationary and rolling ball.

BACKGROUND: Task constraints and players' asymmetry influences on lower extremity (i.e. kicking limb) kinematics during futsal instep kicking. However, support limb behavior when shooting in a futsal context was not previously investigated, and its potential role on such discrepant motor outputs is still unclear. Thus, the study aimed to compare kinematic features of the support limb and approach run between kicking a stationary and a rolling ball using dominant and non-dominant limbs. METHODS: Ten futsal players participated (21.88±2.86 years-old, 73.66±4.17 kg and 1.75±0.04 m) and performed kicks (five per limb per condition) with the dominant and non-dominant limbs in stationary and rolling ball conditions. Kinematic analysis comprised determination of support limb angular joint (hip, knee and ankle) displacement and velocity, approach run distance, angle, linear velocity, step length and width, support foot-to-ball distance, ball velocity (120 Hz) and accuracy (60 Hz). RESULTS: Hip adjustments (greater extension) in the support limb when kicking a rolling ball contributed in maintaining similar performance (e.g., ball velocity) to kicking a stationary ball, compensating for the lower approach run velocity and longer support foot to ball distance. Kicking with the non-dominant limb demonstrated a lower approach run velocity and the non-dominant support limb presented different angular motion compared to the dominant support limb in hip (< internal rotation), knee (< flexion), and ankle joints (< plantar flexion), being harmful to performance in both kicking stationary and rolling balls. CONCLUSIONS: Kicking a stationary and rolling ball presented similar performance, but compared to the dominant side, futsal instep kicks performed with the non-dominant support limb induces lower approach run velocity and inefficient angular joint motion, either harmful to performance output.

Kicking Performance in Young U9 to U20 Soccer Players: Assessment of Velocity and Accuracy Simultaneously.

PURPOSE: The purpose of this study was to compare the kicking performance of young soccer players in the U9 to U20 age groups. METHOD: Three hundred and sixty-six Brazilian players were evaluated on an official pitch using three-dimensional kinematics to measure (300 Hz) ball velocity (Vball), foot velocity (Vfoot), Vball/Vfoot ratio, last stride length, and distance between the support foot and the ball. Simultaneously, a two-dimensional procedure was also conducted to compute (60 Hz) the mean radial error, bivariate variable error, and accuracy. Possible age-related differences were assessed through one-way analysis of variance and magnitude-based inferences. RESULTS: Ball velocity increased by 103% (p < .001, η2 = .39) from the U11 age group (48.54 ± 8.31 km/hr) to the U20 age group (98.74 ± 16.35 km/hr). Foot velocity presented a 59% increase (p < .001, η2 = .32) from the U11 age group (49.08 ± 5.16 km/hr) to U20 (78.24 ± 9.49 km/hr). This finding was due to improvement in the quality of foot-ball impact (Vball/Vfoot ratio) from U11 (0.99 ± 0.13 a.u.) to U20 (1.26 ± 0.11 a.u.; p < .001, η2 = .25). Parameters such as mean radial error and accuracy appeared to be impaired during the growth spurt (U13-U15). Last stride length was correlated, low to moderately high, with Vball in all age groups (r = .36-.79). CONCLUSIONS: In summary, we concluded that simple biomechanical parameters of kicking performance presented distinct development. These results suggest that different training strategies specific for each age group could be applied. We provide predictive equations to aid coaches in the long-term monitoring process to develop the kick in soccer or search for talented young players.

Construct validity of tests that measure kick performance for young soccer players based on cluster analysis: exploring the relationship between coaches rating and actual measures.

BACKGROUND: The main aim of this study was to verify the relationship between the classification of coaches and actual performance in field tests that measure the kicking performance in young soccer players, using the K-means clustering technique. METHODS: Twenty-three U-14 players performed 8 tests to measure their kicking performance. Four experienced coaches provided a rating for each player as follows: 1: poor; 2: below average; 3: average; 4: very good; 5: excellent as related to three parameters (i.e. accuracy, power and ability to put spin on the ball). RESULTS: The scores interval established from k-means cluster metric was useful to originating five groups of performance level, since ANOVA revealed significant differences between clusters generated (P<0.01). Accuracy seems to be moderately predicted by the penalty kick, free kick, kicking the ball rolling and Wall Volley Test (0.44≤r≤0.56), while the ability to put spin on the ball can be measured by the free kick and the corner kick tests (0.52≤r≤0.61). Body measurements, age and PHV did not systematically influence the performance. The Wall Volley Test seems to be a good predictor of other tests. CONCLUSIONS: Five tests showed reasonable construct validity and can be used to predict the accuracy (penalty kick, free kick, kicking a rolling ball and Wall Volley Test) and ability to put spin on the ball (free kick and corner kick tests) when kicking in soccer. In contrast, the goal kick, kicking the ball when airborne and the vertical kick tests exhibited low power of discrimination and using them should be viewed with caution.

Performance comparisons of the kicking of stationary and rolling balls in a futsal context.

Angular kinematics of the hip, knee, and ankle joints, as well as ball velocity and accuracy for stationary and rolling balls were compared in a futsal (Five-a-Side Indoor soccer) context. Ten futsal athletes performed five kicks each on stationary and rolling futsal balls. Six digital cameras (120 Hz) recorded the kicks. For both kick types, angles for hip, knee, and ankle joints were calculated using Euler angle conventions. Angular velocity, ball velocity, foot linear velocity, relative velocity, and accuracy also were analyzed. The kicking of both stationary and rolling balls showed similarities for ball velocity (24.2 +/- 2.2 m/s and 23.8 +/- 2.7 m/s, respectively), foot velocity (17.6 +/- 1.8 m/s and 17.2 +/- 2.2 m/s, respectively), and accuracy (26% and 24% target hits, respectively). We observed few differences in angular kinematics and angular joint velocities between kick types. Elite players can make online adjustments in the preparatory phase so that kicking a rolling ball is almost exactly like kicking a stationary ball.

Determination of Force Coresponding to Maximal Lactate Steady State in Tethered Swimming.

The main aim of the present investigation was to verify if the aerobic capacity (AC) measured in tethered swimming corresponds to the maximal lactate steady state (MLSS) and its correlation with 30 min and 400m free style swimming. Twenty-five swimmers were submitted to an incremental tethered swimming test (ITS) with an initial load of 20N and increments of 10N each 3min. After each stage of 3min, the athletes had 30s of interval to blood sample collections that were used to measure blood lactate concentrations ([La-]). The ACBI was determined by the abrupt increase in [La-] versus force (F). The points obtained between [La-] versus force (N) were adjusted by an exponential curve model to determine AC corresponding to 3.5mmol.l-1 (AC3.5) and 4.0mmol.l-1 (AC4.0). After these procedures, the swimmers performed maximal efforts of 30min and 400m in free style swimming. We used the distance performed in 30min and the time performed in 400m to calculate the median velocities (i.e. V30 and V400) of these protocols. After one week, in order to measure the MLSS, nine athletes performed three 30-min tethered swimming efforts with intensities of 90, 100, and 110% of ACBI. The ANOVA one-way was used to compare the ACBI, AC3.5 and AC4.0. Correlations between ACs, and between ACs and V30 and V400 (p<0.05) were determined using the Pearson's correlation coefficient. The intensity corresponding to 100% of ACBI was similar to the MLSS. It was observed significant correlations of the aerobic capacities (i.e. ACBI, AC3.5 and AC4.0) with V30 (r>0.91) and V400 (r>0.63). According to our results, it is possible to conclude that the ACBI corresponds to the MLSS, and both the AC - individually determined - and the AC - determined using fixed blood lactate concentrations of 3.5 and 4.0mmol.l-1 - can be used to predict the mean velocity of 30min and 400m in free style swimming. In addition to that, the tethered swimming system can be used for aerobic development in places where official sized swimming pools are not available, such as rehabilitation clinics and health clubs.

Effects of taper on swimming force and swimmer performance after an experimental ten-week training program.

The purpose of this research was to examine how an 11-day taper after an 8.5-week experimental training cycle affected lactate levels during maximal exercise, mean force, and performance in training swimmers, independent of shaving, psychological changes, and postcompetition effects. Fourteen competition swimmers with shaved legs and torsos were recruited from the São Paulo Aquatic Federation. The training cycle consisted of a basic training period (endurance and quality phases) of 8.5 weeks, with 5,800 m.d(-1) mean training volume and 6 d.wk(-1) frequency; and a taper period (TP) of 1.5 weeks' duration that incorporated a 48% reduction in weekly volume without altering intensity. Attained swimming force (SF) and maximal performance over 200-m maximal swim (Pmax) before and after taper were measured. After taper, SF and Pmax improved 3.6 and 1.6%, respectively (p < 0.05). There were positive correlations (p < 0.05) between SF and Pmax before (r = 0.86) and after (r = 0.83) the taper phase. Peak lactate concentrations after SF were unaltered before (6.79 +/- 1.2 mM) and after (7.15 +/- 1.8 mM) TP. Results showed that TP improved mean swimming velocity, but not in the same proportion as force after taper, suggesting that there are other factors influencing performance in faster swimming.

Analysis of the distances covered by first division brazilian soccer players obtained with an automatic tracking method.

Methods based on visual estimation still is the most widely used analysis of the distances that is covered by soccer players during matches, and most description available in the literature were obtained using such an approach. Recently, systems based on computer vision techniques have appeared and the very first results are available for comparisons. The aim of the present study was to analyse the distances covered by Brazilian soccer players and compare the results to the European players', both data measured by automatic tracking system. Four regular Brazilian First Division Championship matches between different teams were filmed. Applying a previously developed automatic tracking system (DVideo, Campinas, Brazil), the results of 55 outline players participated in the whole game (n = 55) are presented. The results of mean distances covered, standard deviations (s) and coefficient of variation (cv) after 90 minutes were 10,012 m, s = 1,024 m and cv = 10.2%, respectively. The results of three-way ANOVA according to playing positions, showed that the distances covered by external defender (10642 ± 663 m), central midfielders (10476 ± 702 m) and external midfielders (10598 ± 890 m) were greater than forwards (9612 ± 772 m) and forwards covered greater distances than central defenders (9029 ± 860 m). The greater distances were covered in standing, walking, or jogging, 5537 ± 263 m, followed by moderate-speed running, 1731 ± 399 m; low speed running, 1615 ± 351 m; high-speed running, 691 ± 190 m and sprinting, 437 ± 171 m. Mean distance covered in the first half was 5,173 m (s = 394 m, cv = 7.6%) highly significant greater (p < 0.001) than the mean value 4,808 m (s = 375 m, cv = 7.8%) in the second half. A minute-by-minute analysis revealed that after eight minutes of the second half, player performance has already decreased and this reduction is maintained throughout the second half. Key pointsA novel automatic tracking method was presented. No previous work was found in the literature reporting data of simultaneous trajectories of all soccer players obtained by an automatic tracking method.The study reveals 7% reduction in mean distance covered in the second half and moreover after eight minutes of the second half, player performance has already decreased and this reduction is maintained throughout the second half.