Anthropometric and Functional Profile of Selected vs. Non-Selected 13-to-17-Year-Old Soccer Players

Lower-Body Power, Body Composition, Speed, and Agility Performance among Youth Soccer Players

Speed and agility have been described as crucial abilities for soccer players. The purpose of this study was to analyze, in detail, the variance in speed and agility tasks explained by lower-body power after controlling for age and body composition. The participants were 96 male soccer players aged 16.1 ± 1.6 years. Body composition (stature, body fat percentage-BF%, body mass, and fat-free mass-FFM), lower-body power (countermovement jump-CMJ, and squat jump-SJ), speed (5-, 10-, and 35 m sprints), and agility (t-test) were assessed. Among body composition parameters, BF% presented the highest number of significant relationships with speed and agility, with the strength of correlations ranging from small (5 m sprint, r = 0.25) to large (35 m sprint, r = 0.52). The strongest correlation coefficient emerged between FFM and the 35 m sprint (r = -0.65). Significant correlations were found between vertical jump performance and the 35 m sprint (CMJ: r = -0.68; SJ: r = -0.69), followed by the t-test (CMJ: r = -0.35; SJ: r = -0.47). The hierarchical multiple regression model could explain 22% to 67% of the variance observed in agility scores and speed. BF% remained the most statistically significant negative predictor of all regression models. The CMJ remained a statistically significant positive predictor of the 35 m sprint (β = -0.581, p ≤ 0.01) after controlling for age and body composition. Integrating programs targeting lower-body power might be important to enhance speed and agility performance in youth soccer. On the other hand, future research based on multidisciplinary approaches to investigate the effects of nutritional strategies in reducing or preventing gains in BF% is still needed, which remained a significant predictor of sprint and agility performance in the final models.

The decision-making in dribbling: a video analysis study of U10 soccer players' skills and coaches' quality evaluation

INTRODUCTION

Dribbling is an important soccer skill that, when effective, allows players to overcome opponents. It can provide a strong tactical advantage; for this reason, all of its components (sprint, speed, and ball control) are fundamental to the development of young players. Dribbling can also be considered a decision-making process, and due to its characteristics, it is not always easy to study ecologically. Using a video analysis study, this research aimed to determine whether dribbling skills, specifically dribbling choice (i.e., decision-making), were related to U10 soccer players' quality.

METHODS

Several outcomes measures, divided into three categories, were taken during video analyses: (i) measures related to the efficacy of dribbling skill; (ii) measures related to the ability of players without the ball to support the player in possession; and (iii) measures related to ball circulation. These data were retrospectively assessed to whether the coaches had formed the teams in training through an implicit knowledge of the players' dribbling skills.

RESULTS

The percentage of accurate dribbling (that is, the ability to perform correct passes after a successful dribble) was found to be the variable that coaches may have implicitly used in creating the three groups differentiated by technical skills (p < 0.05). In fact, this percentage was 12.9%, 24.0%, and 48.1% for the groups with lower, average, and higher technical skills, respectively.

CONCLUSION

Overall, the results demonstrate that dribbling accuracy has an important weight in the coach's evaluation of the technical skills level of young soccer players.

Hypertrophic adaptations to a 6-week in-season barbell vs. flywheel squat added to regular soccer training

BACKGROUND

The aim of this study was to compare the hypertrophic adaptations to barbell or flywheel squat exercise added to regular in-season soccer training.

METHODS

Quadriceps' (rectus femoris [RF], vastus medialis [VM] and vastus lateralis [VL]) cross-sectional area (CSA) in its portions (proximal [PROX], middle [MID], and distal [DIST]) was measured on both legs before and after a 6-week barbell (80 to 90% one-maximum repetition; N.=7) or flywheel (0.0611 to 0.0811 kg·m²; N.=7) in an U19 professional soccer team using a 3T magnetic resonance imaging. Both groups underwent 5 sets × 6 reps per session of squat separated by 3-min rest, while controlling the time under tension (within 0.5 and 0.8 s).

RESULTS

The barbell squat group experienced moderate CSA increments in the VM<inf>MID</inf> and the VL<inf>DIST</inf> of the right leg (d=0.98-0.99). Additionally, the flywheel group experience large CSA increments in the RF<inf>MID</inf>, VL<inf>PROX</inf> and VL<inf>MID</inf> of the right leg (d=1.00-1.84). On average, flywheel squat training largely produced greater force during exercise compared to the barbell squat training (29.2 vs. 12.2 N·kg^-1; d=5.95), whereas the barbell squat training produced moderately greater power output (10.5 vs. 9.7; d=0.52).

CONCLUSIONS

Barbell squat training seems to be more effective for VM hypertrophy whereas flywheel squat triggers greater RF and VL hypertrophy as complementary to regular field-based soccer practice and competition within a short range of time (6 weeks) during the in-season. These findings can be considered also from either strength or reconditioning perspective based on the increase in the quadriceps muscles' CSA as mechanism underlying strength/power adaptations.

Effects of a small-sided games training program in youth male soccer players: variations of the locomotor profile while interacting with baseline level and with the accumulated load

Purpose

This study aimed to (1) analyze the impact of a small-sided game training program in the locomotor profile of youth male soccer players (while interacting with the baseline level – higher and lower level); and (2) test the relationships between variation in locomotor profile and the accumulated demands in 3v3, 5v5 and match over the period of observation.

Methods

The cohort lasted 3-weeks. Twenty under-17 male amateur soccer players (16.8 ± 0.41 years; experience: 6.35 ± 0.67 years) were assessed twice for their final velocity at 30−15 intermittent fitness test (VIFT), peak speed at 30-m sprint test (PSS) and anaerobic speed reserve (ASR). The PSS was estimated using a Global Positioning System, while the VIFT was estimated using the maximum level attained by the players during the test. Based on the baseline levels, the scores were standardized using the Z-score. The total score of athleticism (TSA) was calculated per player to organize the players into two groups: lower TSA and higher TSA. Over the three weeks of observation, the small-sided games of 3v3 and 5v5 and match demands were monitored using polar team pro. The heart rate responses (mean and peak), distance covered (overall and split by speed thresholds), and peak speed in these games were obtained and summed over the weeks. The repeated measures ANCOVA tested the variations (time) of the locomotor profile of players while considering the baseline as covariable and the group as a factor. The Pearson-product correlation test analyzed the relationships between variations in locomotor profile (Δ, post-baseline) and the accumulated demands in 3v3, 5v5, and match.

Results

Between-groups analysis (lower TSA vs. higher TSA) revealed no significant differences on VIFT (p = 0.915), PSS (p = 0.269), ASR (p = 0.258) and TSA score (p = 0.138). Within-group (baseline vs. post-observation) analysis revealed significant difference on VIFT (p < 0.001), PSS (p = 0.008), while no significant differences were found on ASR (p = 0.949) and TSA score (p = 0.619). Significant correlations were found between ΔPSS and match total distance (r = 0.444; p = 0.050), match Z2 (r = 0.481; p = 0.032) and match Z3 (r = 0.454; p = 0.044). Significant correlations were found between ΔTSA and match total distance (r = 0.457; p = 0.043), match Z1 (r = 0.451; p = 0.046), match Z2 (r = 0.500; p = 0.025) and match Z3 (r = 0.468; p = 0.037).

Conclusion

Significant improvements were observed after the period of observation. However, the fitness baseline level and the accumulated training load in the small-sided games seem to have no significant impact on the observed improvements.

Effects of High-Intensity Resistance Training on Physical Fitness, Hormonal and Antioxidant Factors: A Randomized Controlled Study Conducted on Young Adult Male Soccer Players

Purpose: The aim of this study was to test the effects of high-intensity resistance training (HIRT) intervention on the physical fitness, hormonal and antioxidant factors of adult male soccer players. Methods: A randomized controlled study design was implemented. Eighteen soccer players (age: 20.3 ± 0.66 years; stature: 174.0 ± 6.01 cm; body mass: 69.1 ± 6.4 kg; body mass index: 22.8 ± 1.6 kg/m2) voluntarily participated in this study. Players were assessed before and after an intervention lasting 8 weeks, with three training sessions a week. Assessments of physical fitness included the Yo-Yo intermittent recovery test level 1 (YYIRT1), 10-, 20-, and 30 m sprint time (ST), running-based anaerobic sprint test (RAST) and change-of-direction time (COD). Hormonal tests included cortisol, testosterone and growth hormone (GH), whereas the antioxidant assessment included superoxide dismutase (SOD), malondialdehyde (MDA) and glutathione (GSH). Results: Between-group analysis revealed no significant differences at baseline, whereas it revealed that HIRT presented significant better results than the control group on YYIRT (p = 0.032), 10 m ST (p = 0.041), 20 m ST (p = 0.040), 30 m ST (p = 0.044), RAST (p = 0.013), and COD (p = 0.031) after the intervention period. The within group analysis revealed that the HIRT group significantly improved the YYIRT1 (p < 0.001), VO2max (p < 0.001), 10 m ST (p < 0.001), 20 m ST (p = 0.006), 30 m ST (p < 0.001), RAST (p < 0.001) and COD (p < 0.001). Moreover, HIRT group significantly reduced the cortisol (p < 0.001) and MDA (p = 0.021), whereas it significantly increased the GH (p < 0.001), testosterone (p < 0.001), SOD (p = 0.009) and GSH (p = 0.005). Conclusions: The HIRT is effective for improving physical fitness, revealing significant better adaptations than controls. Moreover, hormonal and antioxidant adaptations are also confirmed after HIRT intervention.

Assessment of Body Composition and Physical Performance of Young Soccer Players: Differences According to the Competitive Level

Soccer is a multifactorial sport, in which players are expected to possess well developed physical, psychological, technical, and tactical skills. Thus, the anthropometric and fitness measures play a determinant role and could vary according to the competitive level. Therefore, the present study aimed to verify differences in body composition and physical performance between two soccer team. 162 young soccer players (from the Under 12 to Under 15 age categories; age: 13.01 ± 1.15 years) of different competitive levels (elite—n = 98 and non-elite—n = 64) were recruited. Anthropometric characteristics (height, weight, lengths, widths, circumferences, and skinfold thicknesses (SK)), bioelectrical impedance, physical performance test as countermovement jump (CMJ), 15 m straight-line sprints, Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo), and 20 + 20 m repeated-sprint ability (RSA)) were carried out. In addition, Body mass index (BMI), body composition parameters (percentage of fat mass (%F), Fat mass (FM, kg), and Fat-free mass (FFM, kg)) and the areas of the upper arm, calf and thigh were calculated, and the Bioelectric Impedance Vector Analysis (BIVA) procedures were applied. In addition, a linear discriminant analysis was assessed to determine which factors better discriminate between an elite and non-elite football team. Many differences were observed in body composition between and within each football team’s category, especially in triceps SK (p < 0.05), %F (p < 0.05), and all performance tests (p < 0.01). The canonical correlation was 0.717 (F(7,128) = 19.37, p < 0.0001), and the coefficients that better discriminated between two teams were 15 m sprint (−2.39), RSA (1−26), suprailiac SK (−0.5) and CMJ (−0.45). Elite soccer team players present a better body composition and greater physical efficiency. In addition, BIVA outcome could be a relevant selection criterion to scout among younger soccer players.

Physical characteristics of elite youth male football players aged 13-15 are based upon biological maturity

Background

Older and more mature football players have been reported to gain advantages in the selection process during adolescence. The aim of this study was to investigate the influence of skeletal age (SA) on the physical characteristics of elite male football players aged 13-15 years through a cross-sectional study.

Methods and Materials

We enrolled 167 elite players aged 13-15 from three academic football schools in China, and measured height, body mass, thigh circumference, skinfold (triceps and calf), 10 m/30-m sprint, T-tests (left and right), 5 × 25-m repeated-sprint ability (5 × 25 RSA), standing long jump, and YoYo intermittent recovery test level 1 (YYIR1). Subjects were divided into early-, average-, and late-maturity levels according to their SA and chronological age (CA) based on the following criteria: SA-CA > +1 year, SA-CA = ±1 year, and SA-CA < -1 year, respectively. The differences in parameters among the groups were analyzed using one-way analysis of variance and Bonferroni's post-hoc test, with statistical significance set at p < 0.05.

Results

Relative to the late-maturing players, the early- and average-maturing players aged 13-15 years were taller, heavier, had a larger thigh circumference, and scored higher on the standing long jump, 30 m sprint, and 5 × 25-RSA (p < 0.05). The physical (except for body-fat percentage) and athletic characteristics of players aged 13-15 were not only significantly influenced by biological maturity, but also increased significantly with CA. The influence of biological maturity on height, 30-m sprints, and 5 × 25-m RSA diminished with age and exerted no significant effect on body-fat percentage and on YYIR1. Late-maturing players exhibited the greatest increase in physical (except for body-fat percentage) and athletic performance (except for the 10-m sprint) compared to players of early and/or average maturity.

Conclusions

Although early-maturing players aged 13-15 possessed better anthropometric and physical performance than late- and average-maturing players, the growth and development of physical function of late- and average-maturing players was significantly greater, particularly with respect to height, sprint speed, and muscular power.

Selected vs. Non-Selected Under-20 National Futsal Players: Differences between Physical Performance and Training Intensity Experienced in Training Camps

The aim of this study was two-fold: (i) analyze the variations in the physical fitness of selected and non-selected under-20 male national futsal players; and (ii) analyze the variations in training intensity monitored during training camps. Thirty-three Taiwan under-20 national futsal players were monitored for training intensity during 18 training camps. They were divided into two groups: selected (n = 14) and non-selected (n = 17) players. The physical assessments included the following measures: body mass, distance covered at Yo-Yo intermittent recovery test Level 1, final velocity at 30-15 Intermittent Fitness Test (30-15 IFT), standing long jump, maximum heart rate (HR), and 1-min sit-up. The training intensity was monitored using the rate of perceived exertion (RPE), HR at different intensity zones, and locomotor demands measured at different speed thresholds. The results revealed that the selected players were significantly faster in the 15-m sprint with ball (p = 0.001) and 30-m sprint (p = 0.001). Additionally, the selected players presented significantly greater HRaverage and time spent above 90% maximum HR during the three-to-six-day training camps (p < 0.05) compared to the non-selected players. Interestingly, the NS demonstrated a greater number of sprints during the training camps (p = 0.001), while the selected players presented greater distance/minute and average speed (p = 0.001). A regression analysis showed that the distance/minute and average speed was a significant predictor of maximum HR in the selected players. As conclusions, the physical fitness outcomes are different between the selected and non-selected national futsal players. The selected players spent more time in high intensity HR demands in training sessions.

Discriminant Analysis of Anthropometric and Training Variables among Runners of Different Competitive Levels

The purpose of this study was to investigate the multivariate profile of different types of Brazilian runners and to identify the discriminant pattern of the distinct types of runners, as a runners' ability to self-classify well. The sample comprised 1235 Brazilian runners of both sexes (492 women; 743 men), with a mean age of 37.94 ± 9.46 years. Individual characteristics were obtained through an online questionnaire: Sex, age, body height (m) and body mass (kg), socioeconomic status, and training information (i.e., self-classification, practice time, practice motivation, running pace, frequency and training volume/week). Multivariate analysis of variance was conducted by sex and the discriminant analysis was used to identify which among running pace, practice time, body mass index and volume/training could differentiate groups such as "professional athletes", "amateur athletes" and "recreational athletes". For both sexes, running pace was the variable that better discriminated the groups, followed by BMI and volume/week. The practice time is not a good indicator to differentiate runner's types. In both sexes, semi-professional runners were those that better self-classify themselves, with amateur runners presenting the highest classification error. This information can be used to guide the long-term training, athlete's selection programs, and to identify the strengths and weaknesses of athletes.