scholarly journals Influence of biological maturation on speed, jump, and endurance in high-level youth soccer players

2020 ◽  
Vol 42 ◽  
Author(s):  
Jorge L. C. Marinho ◽  
André O. Martins ◽  
Ezequiel Rey ◽  
Sixto González-Víllora
Keyword(s):  
Vertical Jump ◽  
Young Male ◽  
Peak Height ◽  
Soccer Players ◽  
Height Velocity ◽  
Peak Height Velocity ◽  
Speed Test ◽  
Test Distance ◽  
Effective Development ◽  
High Level

ABSTRACT The goal of this study is to identify the influence of the maturity state in the physical components of the high level youth male soccer players of an elite club in Brazil. Eighty-seven young male soccer players participated in this study, distributed in 34 U-14 players, 23 U-16 players and 30 U-19 players. Peak height velocity (PHV) was estimated: Pre-PHV (<-1.0 years, n=13), mid-PHV (-0.99 to 0.5 years, n=41), and post-PHV (>0.5 years, n=33). Running-based anaerobic sprint test, squat jump, yo-yo and 30m speed test were performed. The results of this study suggest that the maturational development influences vertical jump. VO2max, yo-yo test distance, fatigue index and power. This information is essential for the identification and effective development of talented football players.

scholarly journals Associations Between Variations in Accumulated Workload and Physiological Variables in Young Male Soccer Players Over the Course of a Season

2021 ◽  
Vol 12 ◽  
Author(s):  
Hadi Nobari ◽  
Ana Ruivo Alves ◽  
Filipe Manuel Clemente ◽  
Jorge Pérez-Gómez ◽  
Cain C. T. Clark ◽  
...  
Keyword(s):  
Strong Association ◽  
Body Height ◽  
Young Male ◽  
Peak Height ◽  
Soccer Players ◽  
Height Velocity ◽  
Peak Height Velocity ◽  
Intermediate Period ◽  
Physiological Variables ◽  
Fitness Levels

This study sought to analyze the relationship between in-season training workload with changes in aerobic power (VO2max), maximum and resting heart rate (HRmax and HRrest), linear sprint medium (LSM), and short test (LSS), in soccer players younger than 16 years (under-16 soccer players). We additionally aimed to explain changes in fitness levels during the in-season through regression models, considering accumulated load, baseline levels, and peak height velocity (PHV) as predictors. Twenty-three male sub-elite soccer players aged 15.5 ± 0.2 years (PHV: 13.6 ± 0.4 years; body height: 172.7 ± 4.2 cm; body mass: 61.3 ± 5.6 kg; body fat: 13.7% ± 3.9%; VO2max: 48.4 ± 2.6 mL⋅kg–1⋅min–1), were tested three times across the season (i.e., early-season (EaS), mid-season (MiS), and end-season (EnS) for VO2max, HRmax, LSM, and LSS. Aerobic and speed variables gradually improved over the season and had a strong association with PHV. Moreover, the HRmax demonstrated improvements from EaS to EnS; however, this was more evident in the intermediate period (from EaS to MiS) and had a strong association with VO2max. Regression analysis showed significant predictions for VO2max [F(2,20) = 8.18, p ≤ 0.001] with an R2 of 0.45. In conclusion, the meaningful variation of youth players’ fitness levels can be observed across the season, and such changes can be partially explained by the load imposed.

Is the Relationship Between Sprinting and Maximal Aerobic Speeds in Young Soccer Players Affected by Maturation?

2010 ◽  
Vol 22 (4) ◽  
pp. 497-510 ◽  
Author(s):  
Alberto Mendez-Villanueva ◽  
Martin Buchheit ◽  
Sami Kuitunen ◽  
Tsz Kit Poon ◽  
Ben Simpson ◽  
...  
Keyword(s):  
Body Mass ◽  
Allometric Scaling ◽  
Young Male ◽  
Peak Height ◽  
Soccer Players ◽  
Height Velocity ◽  
Peak Height Velocity ◽  
Positive Correlations ◽  
The Relationship

The purpose of this study was to investigate the relationship between maximal sprinting (MSS) and aerobic (MAS) speeds in a cohort of highly-trained young male soccer players with the influence of body mass controlled for using allometric scaling. MSS and MAS were obtained in 14 pre-age at peak height velocity (APHV) players (12.3 ± 0.7 years), 21 circum-APHV players (14.3 ± 0.9 year) and 26 post-APHV players (16.9 ± 0.7 years). The three groups showed similar positive correlations between MSS and MAS (r = 0.73 to 0.52; p < .01). In conclusion, our results suggest that the relationship between MSS and MAS is not affected by maturation.

scholarly journals Comparison of Drop Jump and Tuck Jump Knee Joint Kinematics in Elite Male Youth Soccer Players: Implications for Injury Risk Screening

2020 ◽  
Vol 29 (6) ◽  
pp. 760-765 ◽  
Author(s):  
Rhodri S. Lloyd ◽  
Jon L. Oliver ◽  
Gregory D. Myer ◽  
Mark B. De Ste Croix ◽  
Josh Wass ◽  
...  
Keyword(s):  
Injury Risk ◽  
Vertical Jump ◽  
Knee Kinematics ◽  
Frontal Plane ◽  
Young Male ◽  
Soccer Players ◽  
Height Velocity ◽  
Peak Height Velocity ◽  
Male Youth ◽  
Youth Soccer

Context: Despite the popularity of jump-landing tasks being used to identify injury risk factors, minimal data currently exist examining differences in knee kinematics during commonly used bilateral jumping tasks. This is especially the case for rebounding-based protocols involving young athletes. Objective: To compare the frontal plane projection angles (FPPAs) during the drop vertical jump (DVJ) and tuck jump assessment (TJA) in a cohort of elite male youth soccer players of varying maturity status. Methods: A total of 57 male youth soccer players from an English championship soccer club participated in this study. Participants performed 3 trials of the DVJ and TJA, during which movement was recorded with 2-dimensional video cameras. FPPA for both right (FPPA-r) and left (FPPA-l) legs, with values <180° indicative of medial knee displacement. Results: On a whole-group level, FPPA-r (172.7° [7.4°] vs 177.2° [11.7°]; P < .05; effect size [ES] = 0.46) and FPPA-l (173.4° [7.3°] vs 179.2° [11.0°]; P < .05; ES = 0.62) were significantly greater for both limbs in the TJA compared with the DVJ; however, these differences were less consistent when grouped by maturity status. FPPA-r during the TJA was significantly and moderately greater in the circa-peak height velocity (PHV) group compared with the post-PHV cohorts (169.4° [6.4°] vs 175.3° [7.8°]; P < .05; ES = 0.49). Whole-group data showed moderate relationships for FPPA-r and FPPA-l between the TJA and DVJ; however, stronger relationships were shown in circa- and post-PHV players compared with the pre-PHV cohort. Conclusions: Considering that the TJA exposed players to a larger FPPA and was sensitive to between-group differences in FPPA-r, the TJA could be viewed as a more suitable screen for identifying FPPA in young male soccer players.

scholarly journals Biological maturity and the anthropometric, physical and technical assessment of talent identified U16 Australian footballers

2017 ◽  
Vol 12 (3) ◽  
pp. 344-350 ◽  
Author(s):  
Ashley J Cripps ◽  
Christopher Joyce ◽  
Carl T Woods ◽  
Luke S Hopper
Keyword(s):  
Characteristic Curve ◽  
Vertical Jump ◽  
Binary Logistic Regression ◽  
Peak Height ◽  
Technical Skill ◽  
Height Velocity ◽  
State Representation ◽  
Peak Height Velocity ◽  
Biological Maturation ◽  
Australian Football

This study compared biological maturation, anthropometric, physical and technical skill measures between talent and non-talent identified junior Australian footballers. Players were recruited from the under 16 Western Australian Football League and classified as talent (state representation; n = 25, 15.7 ± 0.3 y) or non-talent identified (non-state representation; n = 25, 15.6 ± 0.4 y). Players completed a battery of anthropometric, physical and technical skill assessments. Maturity was estimated using years from peak height velocity calculations. Binary logistic regression was used to identify the variables demonstrating the strongest association with the main effect of ‘status’. A receiver operating characteristic curve was used to assess the level of discrimination provided by the strongest model. Talent identified under 16 players were biologically older, had greater stationary and dynamic leaps and superior handball skill when compared to their non-talent identified counterparts. The strongest model of status included standing height, non-dominant dynamic vertical jump and handball outcomes (AUC = 83.4%, CI = 72.1%–95.1%). Biological maturation influences anthropometric and physical capacities that are advantageous for performance in Australian football; talent identification methods should factor biological maturation as a confound in the search for junior players who are most likely to succeed in senior competition.

scholarly journals Injury Risk and Injury Burden Are Related to Age Group and Peak Height Velocity Among Talented Male Youth Soccer Players

2018 ◽  
Vol 6 (12) ◽  
pp. 232596711881104 ◽  
Author(s):  
Hans Jan Bult ◽  
Maarten Barendrecht ◽  
Igor Joeri Ramon Tak
Keyword(s):  
Injury Risk ◽  
Age Groups ◽  
Peak Height ◽  
Soccer Players ◽  
Height Velocity ◽  
Incidence Density ◽  
Chronological Age ◽  
Peak Height Velocity ◽  
The Mean ◽  
Injury Burden

Background: The relationship between injury risk (IR) in age groups and periods around peak height velocity (PHV) remains unclear. PHV is defined as the moment of the largest increase in body height. Purpose: To investigate injury risk and injury burden as functions of growth velocity (periods around PHV) and chronological age groupings (under 12 years [U12] to U19) in talented youth male soccer players. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 170 players from the youth academy of a Dutch soccer club (highest professional league: Eredivisie) were observed for 1 to 3 seasons. Injuries, exposure, PHV age, and chronological age were registered. The injury incidence density (IID) and injury burden per 1000 hours of soccer participation, with 95% CIs, were calculated for 5 PHV periods and 7 age groups. These were compared with the overall cohort results using incidence ratios (IRs) and burden ratios (BRs) with 95% CIs. Results: The mean age at PHV was 14.4 ± 0.65 years (range, 12.8-16.5 years). The mean IID for the total cohort was 8.34 injuries per 1000 hours (95% CI, 7.71-9.02). Compared with the overall mean, a significantly higher IID was found for PHV period 4+5 (IR, 1.31 [95% CI, 1.00-1.71]; P = .049) and for the U15 group (IR, 1.49 [95% CI, 1.24-1.79]; P < .001). The overall injury burden was 58.37 injury days per 1000 hours (95% CI, 56.66-60.13). In PHV period 4+5, the injury burden was significantly higher (BR, 1.53 [95% CI, 1.39-1.68]; P < .001) when compared with the overall mean. Also, compared with the overall mean, the injury burden was higher in the U16 (BR, 1.48 [95% CI, 1.39-1.58]; P < .001), U15 (BR, 1.28 [95% CI, 1.19-1.38]; P < .001), and U17 groups (BR, 1.21 [95% CI, 1.13-1.31]; P < .001). Conclusion: Talented young soccer players were more prone to injuries during the 6 months after PHV (31% above overall mean) as well as in the U15 group (49% above overall mean). Based on the higher injury burden in the U16 (48%), U15 (28%), and U17 (21%) groups, we suggest that research on injury risk factors and preventive measures should primarily target these age groups. Additional interventions based on PHV may be of limited value from a screening perspective. Further research is needed on the interaction between age groups and PHV periods.

scholarly journals Predictive Analytic Techniques to Identify Hidden Relationships between Training Load, Fatigue and Muscle Strains in Young Soccer Players

Sports ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Mauro Mandorino ◽  
António J. Figueiredo ◽  
Gianluca Cima ◽  
Antonio Tessitore
Keyword(s):  
Area Under The Curve ◽  
Predictive Ability ◽  
Peak Height ◽  
Neuromuscular Fatigue ◽  
Training Load ◽  
Soccer Players ◽  
Height Velocity ◽  
Support Vector ◽  
Peak Height Velocity ◽  
Injury Surveillance System

This study aimed to analyze different predictive analytic techniques to forecast the risk of muscle strain injuries (MSI) in youth soccer based on training load data. Twenty-two young soccer players (age: 13.5 ± 0.3 years) were recruited, and an injury surveillance system was applied to record all MSI during the season. Anthropometric data, predicted age at peak height velocity, and skeletal age were collected. The session-RPE method was daily employed to quantify internal training/match load, and monotony, strain, and cumulative load over the weeks were calculated. A countermovement jump (CMJ) test was submitted before and after each training/match to quantify players’ neuromuscular fatigue. All these data were used to predict the risk of MSI through different data mining models: Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM). Among them, SVM showed the best predictive ability (area under the curve = 0.84 ± 0.05). Then, Decision tree (DT) algorithm was employed to understand the interactions identified by the SVM model. The rules extracted by DT revealed how the risk of injury could change according to players’ maturity status, neuromuscular fatigue, anthropometric factors, higher workloads, and low recovery status. This approach allowed to identify MSI and the underlying risk factors.

Associations Between Balance and Muscle Strength, Power Performance in Male Youth Athletes of Different Maturity Status

2016 ◽  
Vol 28 (4) ◽  
pp. 521-534 ◽  
Author(s):  
Raouf Hammami ◽  
Anis Chaouachi ◽  
Issam Makhlouf ◽  
Urs Granacher ◽  
David G. Behm
Keyword(s):  
Muscle Strength ◽  
Dynamic Balance ◽  
Correlation Coefficients ◽  
Young Male ◽  
Peak Height ◽  
Height Velocity ◽  
Power Performance ◽  
Peak Height Velocity ◽  
Youth Athletes ◽  
Back Extensor

Balance, strength and power relationships may contain important information at various maturational stages to determine training priorities. Purpose:The objective was to examine maturity-specific relationships of static/dynamic balance with strength and power measures in young male athletes.Methods:Soccer players (N = 130) aged 10–16 were assessed with the Stork and Y balance (YBT) tests. Strength/power measures included back extensor muscle strength, standing long jump (SLJ), countermovement jump (CMJ), and 3-hop jump tests. Associations between balance with strength/power variables were calculated according to peak-height-velocity (PHV).Results:There were significant medium-large sized correlations between all balance measures with back extensor strength (r = .486–.791) and large associations with power (r = .511–.827). These correlation coefficients were significantly different between pre-PHV and circa PHV as well as pre-PHV and post-PHV with larger associations in the more mature groups. Irrespective of maturity-status, SLJ was the best strength/power predictor with the highest proportion of variance (12–47%) for balance (i.e., Stork eyes opened) and the YBT was the best balance predictor with the highest proportion of variance (43–78%) for all strength/power variables.Conclusion:The associations between balance and muscle strength/power measures in youth athletes that increase with maturity may imply transfer effects from balance to strength/power training and vice versa in youth athletes.

scholarly journals Assessing Differences in Cardiorespiratory Fitness With Respect to Maturity Status in Highly Trained Youth Soccer Players

2018 ◽  
Vol 30 (2) ◽  
pp. 216-228 ◽  
Author(s):  
Greg Doncaster ◽  
John Iga ◽  
Viswanath Unnithan
Keyword(s):  
Oxygen Uptake ◽  
Cardiorespiratory Fitness ◽  
Peak Height ◽  
Peak Oxygen Uptake ◽  
Running Economy ◽  
Fat Free Mass ◽  
Soccer Players ◽  
Height Velocity ◽  
Peak Height Velocity ◽  
Youth Soccer

Purpose: The purpose of the study was to examine differences in measures of cardiorespiratory fitness and determinants of running economy with respect to maturity status in a group of highly trained youth soccer players. Methods: A total of 21 highly trained youth soccer players participated in this study. On separate visits, players’ peak oxygen uptake (VO2peak), running economy at 3 different speeds [8 km·h−1, 80% gaseous exchange threshold (GET), and 95% GET], and pulmonary oxygen uptake (VO2) kinetics were determined. Players also performed a Yo-Yo intermittent recovery test level 1 (Yo-Yo IR1). Players were categorized as either “pre-PHV” (peak height velocity) or “mid-PHV” group using the measure of maturity offset. Independent t tests and Cohen’s d effect sizes were then used to assess differences between groups. Results: The mid-PHV group was significantly taller, heavier, and advanced in maturity status. Absolute measures of VO2peak were greater in the mid-PHV group; however, when expressed relative to body mass, fat-free mass, and theoretically derived exponents, VO2peak values were similar between groups. Pre-PHV group presented a significantly reduced VO2 response, during relative submaximal running speeds, when theoretically derived exponents were used, or expressed as %VO2peak. VO2 kinetics (tau) were faster during a low (standing) to moderate (95% GET) transition in the pre-PHV group. Yo-Yo IR1 performance was similar between groups. Conclusion: Although measures of VO2peak and Yo-Yo IR1 performance are shown to be similar between groups, those categorized as pre-PHV group display a superior running economy at relative submaximal running speeds and faster taus during a low to moderate exercise transition than their more mature counterparts.

scholarly journals Comparison of maturation and physical performance in basketball athletes of different playing positions

2019 ◽  
Vol 21 ◽  
Author(s):  
Lilian Keila Barazetti ◽  
Pedro Rafael Varoni ◽  
Fernando de Souza Campos ◽  
Michelli Demarchi ◽  
Lucielle Baumann ◽  
...  
Keyword(s):  
Physical Performance ◽  
Body Mass ◽  
Aerobic Power ◽  
Vertical Jump ◽  
Peak Height ◽  
Lower Limbs ◽  
Height Velocity ◽  
Leg Length ◽  
Peak Height Velocity ◽  
Sitting Height

Abstract The aim of this study was to compare the characteristics of somatic maturation, anthropometric and physical performance (vertical jump and aerobic power) in young basketball players of different playing positions (under 13 years) and analyze these relationships using Peak Height Velocity (PHV) as a measure of somatic maturation. For this, 26 male athletes were evaluated. Anthropometric variables were: body mass, standing and sitting height, and length of lower limbs. Maturation was determined by age at PHV. Physical performance was determined by lower limb power (counter movement jump - CMJ) and aerobic power (Intermittent Recovery Test) tests. MANOVA reported significant differences (p<0.05) among playing positions regarding variables Maturity Offset, estimated PHV age, standing height, sitting height, estimated leg length, body mass and Yo-Yo IR1. In addition, it was identified that point guards reached estimated PHV at later age than their peers who act as small forwards and centers. Regarding CMJ, no significant differences were identified among playing positions, but in relation to aerobic power, point guards and small forwards presented higher performance. These findings confirm that maturation has great effect on growth and physical performance measures and the estimated PHV age is an applicable tool in young athletes, mainly aiding professionals in structuring the teaching-learning- training process in this age group.

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