International Journal of Environmental Research and Public Health (MDPI)
2004 | 525,942,120 words
The International Journal of Environmental Research and Public Health (IJERPH) is a peer-reviewed, open-access, transdisciplinary journal published by MDPI. It publishes monthly research covering various areas including global health, behavioral and mental health, environmental science, disease prevention, and health-related quality of life. Affili...
Examination of the Sprinting and Jumping Force-Velocity Profiles in Young...
Luis Miguel Fernández-Galván
Education Faculty, Autónoma University of Madrid, 28049 Madrid, Spain
Daniel Boullosa
Instituto Integrado de Saúde (INISA), Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil
Pedro Jiménez-Reyes
Centre for Sport Studies, Rey Juan Carlos University, 28943 Madrid, Spain
Víctor Cuadrado-Peñafiel
Education Faculty, Autónoma University of Madrid, 28049 Madrid, Spain
Arturo Casado
Centre for Sport Studies, Rey Juan Carlos University, 28943 Madrid, Spain
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Year: 2021 | Doi: 10.3390/ijerph18094646
Copyright (license): Creative Commons Attribution 4.0 International (CC BY 4.0) license.
[Full title: Examination of the Sprinting and Jumping Force-Velocity Profiles in Young Soccer Players at Different Maturational Stages]
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International Journal of Environmental Research and Public Health Article Examination of the Sprinting and Jumping Force-Velocity Profiles in Young Soccer Players at Different Maturational Stages Luis Miguel Fern á ndez-Galv á n 1 , Daniel Boullosa 2,3 , Pedro Jim é nez-Reyes 4 , V í ctor Cuadrado-Peñafiel 1 and Arturo Casado 4,5, * Citation: Fernández-Galván, L.M.; Boullosa, D.; Jiménez-Reyes, P.; Cuadrado-Peñafiel, V.; Casado, A Examination of the Sprinting and Jumping Force-Velocity Profiles in Young Soccer Players at Different Maturational Stages Int. J. Environ Res. Public Health 2021 , 18 , 4646 https://doi.org/10.3390/ ijerph 18094646 Academic Editor: Jo ã o Paulo Vilas-Boas Received: 15 March 2021 Accepted: 24 April 2021 Published: 27 April 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations Copyright: © 2021 by the authors Licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) 1 Education Faculty, Aut ó noma University of Madrid, 28049 Madrid, Spain; luisdepucela@gmail.com (L.M.F.-G.); victor.cuadrado@uam.es (V.C.-P.) 2 Instituto Integrado de Sa ú de (INISA), Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Brazil; daniel.boullosa@gmail.com 3 College of Healthcare Sciences, James Cook University, Townsville 4811, Australia 4 Centre for Sport Studies, Rey Juan Carlos University, 28943 Madrid, Spain; pedro.jimenezr@urjc.es 5 Faculty of Health Sciences, Isabel I de Castilla International University, 09003 Burgos, Spain * Correspondence: arturo.casado@urjc.es; Tel.: +34-914-888-343 Abstract: The aim was to determine the relationships among components of the force-velocity (F-V) profiles in jumping and sprinting, with both biological and chronological ages in 89 young soccer players belonging to categories from U 10 to U 18. Participants performed countermovement jumps (CMJ) and 20-m sprint tests. F-V components assessed were associated with both maturity offset and chronological age, using correlation and multiple linear regression analyses. Horizontal (i.e., maximal theoretical force [F 0 ] and velocity [V 0 ], maximal power [P max ] and F-V slope) and vertical (i.e., [F 0 ] and [P max ]) F-V components displayed very large correlations (i.e., 0.79 ≤ r ≤ 0.92) with both chronological age and maturity offset. The combination of sprinting P max and training experience and jumping F 0 and training experience explained up to 94% of the variances in maturity offset and chronological age. Furthermore, similar correlations were found between sprinting and jumping performances, and components of the F-V profiles, and both maturity offset and chronological age Identification of vertical jump and sprint mechanical determinants may assist in strengthening those components of the F-V profile which are weaker throughout the training process. Sprinting and jumping capabilities can be indistinctly monitored with respect to their chronological age or maturity offset in young soccer players Keywords: young soccer players; maturation; force-velocity profile; sprint; vertical jump 1. Introduction The macroscopic approach to assess sprinting and jumping abilities based on the force-velocity (F-V) relationship has gained increasing attention in the sport science community [ 1 , 2 ]. The horizontal and vertical F-V profiles are used to measure the individual performance characteristics displayed in horizontal sprint and vertical jump tests [ 2 , 3 ]. The F-V relationship can be modelled from the measurement of the force and velocity performed during vertical jumps against two or more loads [ 4 , 5 ] and from the velocity during a maximal horizontal sprint test [ 2 ]. Recent studies have demonstrated the optimal development of jumping and sprinting performances during the training process through the use of the F-V profile in adults [ 1 , 6 ]. Previous studies have confirmed the link between athletes’ performance in different sports with the different mechanical variables of the F-V profiles generated from jumping and sprinting tests [ 7 – 9 ]. Several studies have already reported the F-V profile of soccer players [ 9 – 12 ], providing reference values of the sprint F-V profile of soccer players according to age, gender, and level of practice [ 7 , 13 ]. The F-V profile in sprinting and jumping is composed of different variables, such as the maximal Int. J. Environ. Res. Public Health 2021 , 18 , 4646. https://doi.org/10.3390/ijerph 18094646 https://www.mdpi.com/journal/ijerph
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 2 of 11 theoretical force (F 0 ), maximal theoretical velocity (V 0 ), the slope of the F-V relationship (F-V slope), and maximal power (P max ). In addition, the F-V profile in sprinting includes the percentage of the resultant force that is generated in the horizontal direction [ 2 ], with the decrease in the ratio of horizontal-to-resultant force (DRF) and the maximal ratio of horizontal-to-resultant force (RF peak) being typically used to assess mechanical effectiveness and sprint performance [ 14 ]. It is well known that the most relevant determining events during soccer matches are determined by high intensity actions such as jumping, changes of direction, and sprints [ 15 ]. For this reason, a typical test battery in soccer players includes different sprinting and jumping tests [ 16 ]. Specifically, for young soccer players, the measurement of these capabilities is more accurate when they are related to maturation rather than to chronological age [ 17 ]. Biological maturation, in relation to human growth, refers to the time required and the process of change until the adult maturation state is reached [ 18 ]. The physical and physiological changes that occur during the progress of biological maturation evolve at a different pace, depending on the subject [ 18 ], with the maturity offset which is defined as the time before or after peak height velocity (PHV) being one of the most useful indicators of the maturation stage [ 18 , 19 ]. A preliminary investigation identified the relationship between different sprinting abilities, including acceleration and maximum sprint velocity and maturity offset, but not chronological age [ 20 ]. Subsequently, some studies have found high correlations between the improved performance in sprinting and jumping in young soccer players and maturity offset [ 20 – 25 ], therefore highlighting sprinting capabilities as valid indicators to be used as talent-identification criteria in young soccer players. However, to date, no previous studies have either used the F-V profiles in young soccer players, or assessed the relationship between these components and both chronological age and maturity offset. Evolution of different components of the horizontal and vertical F-V profile across the maturation process in this population would assist in the development of jumping and sprinting performances, therefore providing reference values to identify the strengths and weaknesses of young soccer players with different maturational levels. In addition, this information may help to improve the validity of sprinting and jumping performance evaluations. In this way, the assessment of the evolution of the different F-V profile components would indicate the specific development state in some of the most important conditional capacities in young soccer players. Furthermore, this evaluation would provide a talent identification criterion which may prove useful for soccer teams. In this manner, optimized early identification of young talents would promote the development of any soccer club, as it brings advantages such as specialization in the skills and abilities of the sport, future economic sales, and the incorporation of players in the first team [ 26 – 28 ]. Both sprinting and jumping performances have been strongly associated with their F-V mechanical determinants in adults [ 5 , 9 ]. Moreover, sprinting and jumping performances have been found to change according to maturation in young soccer players [ 20 , 23 , 24 ]. Therefore, it would be reasonable to assume that the changes of the components of the F-V profiles are more related to changes in maturation than changes in chronological age. Previously, Murtagh et al. [ 29 ] reported that sprinting ability was more related to maturation changes than jumping Therefore, the aims of this study were: (i) to examine the relationship between performance and F-V jump and sprint profile, with chronological age and maturity offset of young soccer players; and (ii) to compare relationships between maturity offset and chronological age for jumping and sprinting 2. Methods 2.1. Subjects In this study, 89 male young soccer players who train regularly in the same professional soccer academy volunteered for participation (age range: 8.04–17.93 years). Players regularly trained during at least one year prior to participation. Players trained specifically for soccer in a regular basis for 4.22 ± 2.34 years. Players and their parents agreed to
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 3 of 11 participate in the current research and parental consents were signed following the tenets of the Declaration of Helsinki 2.2. Design A cross-sectional design was conducted with jumping and sprinting performances Countermovement jumps (CMJ) without load and with two different loads (i.e., 25% and 50% of body mass), and 20-m sprints were conducted to identify the different components of the vertical and the horizontal F-V profiles, respectively (i.e., F 0 , V 0 , P max , F-V slope, F-V deficit, RF peak and DRF), according to Samozino’s method [ 2 ]. These variables were subsequently associated to both maturity offset and chronological age, with correlation and multiple linear regression analyses 2.3. Methodology Prior to data collection, anthropometric variables were recorded in the laboratory Body mass (Tanita BF-522 W, 0.1 kg precision, Japan), stature and seated height (noncommercial portable stadiometer, 0.1 cm precision) were recorded and subsequently used to calculate maturity offset through an estimation of the time before or after PHV, which also includes date of birth and the date of measurement [ 19 ]. This method approximates the amount of time (in years) until, or since, an individual’s predicted PHV indicating the maturity offset [ 19 ]. The equation used is the following: Maturity offset = − [9.236 + 0.0002708 * Leg Length and Sitting Height interaction] − [0.001663 * Age and Leg Length interaction] + [0.007216 * Age and Sitting Height interaction] + [0.02292 * Weight by Height ratio] (1) The distance range to PHV in order to classify soccer players by maturity status was larger than that used in previous studies using age at PHV [ 30 ], assuming the limitations of the offset equations [ 31 , 32 ] Participants were instructed to arrive for performance testing in a rested state, while avoiding strenuous exercise in the previous 48 hrs. All testing sessions were completed under thermoneutral conditions (sunny, wind speed of 1.1 ± 0.9 m/s, 23 ± 0.7 ◦ C, and 45 ± 6.3% of relative humidity). The testing sessions were performed at 5 p.m., which is the time at which players usually train. Participants performed a standardized 15-min warmup consisting of 5 min of jogging and 5 min of lower limb dynamic stretching followed by 5 unloaded CMJ and 3 loaded CMJs with 30 kg, and 3 progressive 30-m sprints (at 50%, 70% and 90% of the players’ self-perceived maximal velocity) Individual F-V profiles and P max can be easily determined through the completion of a certain number of series of loaded vertical jumps [ 2 , 3 , 5 , 33 ]. After the warm-up, each player performed 2 CMJs (without external load, and with 2 external loads of 25% and 50% of body mass) in randomized order. Players were instructed to stand up straight with their hands on their hips for the unloaded CMJs, and on the free-weight bar (0.5 kg) for the loaded CMJs, which were performed with a knee angle of approximately ~90 ◦ . The players were instructed to jump “as high as possible.” Two valid attempts were performed with each load with 2 min of recovery between attempts, and 4–5 min between loads. Jump height was recorded using the MyJump 2 app [ 34 ] installed on an iPhone 7 (Apple Inc., Cupertino, CA, USA). For this reason, players were also instructed to land with extended legs and feet in order to not overestimate CMJ height. The mean values of force and velocity components of the individual loads required to calculate the F-V profiles were obtained from previously validated equations [ 2 ]. After jumping evaluations, participants performed 2 maximal 20-m sprints, with 5 min of rest between attempts, on a synthetic outdoor track. Both attempts were recorded by using an iPhone 7 (Apple Inc., Cupertino, CA, USA) and MySprint app (T-Mobile Inc., Bellevue, WA, USA). Athletes started from a crouching position (staggered-stance) with the right hand on the track. The start of the sprint was determined as the moment in which the right thumb of the athlete took off the ground (this was detected by visual inspection with MySprint). Five markers were located at 5, 10, 15, and 20 m to ensure that the split times were correctly recorded. Two independent observers were asked to select the first frame in
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 4 of 11 which participants’ right thumb left the ground (i.e., start of the sprint) and, subsequently, the frame in which the pelvis was aligned with each of the four different markers for each of the recorded sprints [ 35 ]. Split times along with participants’ body mass and stature were used by the MySprint app to calculate F 0 , V 0 , P max , FV slope, RF peak, and DRF following previously validated formulas [ 2 , 35 ]. As sprinting and jumping F 0 , P max , and FV slope are calculated in relation to body mass and in subsequent analyses with these variables body mass bias was going to be statistically controlled for, these values were multiplied by body mass 2.4. Statistical Analyses Statistical analyses were performed using SPSS 24.0 (IBM, Armonk, NY, USA). Data were tested for normality of distribution and homogeneity of variances using a Kolmorov– Smirnov normality test and a Levene test, respectively. Linear regression assumptions were checked using residual vs. fitted, normal QQ, and Cook’s distance plots. There was no evidence of heteroscedasticity or multicollinearity. Given the association between body size and performance in adolescent males and because body mass and stature are highly related, residuals (individual values minus the mean) of the latter variables were obtained. Their product (i.e., residuals of body mass x residuals of stature) was calculated representing body size and it was used in subsequent partial correlation and multiple regression analyses so that collinearity among the independent variables was reduced [ 32 ]. Correlations were calculated between participants’ maturity offset and chronological age and both their jumping and sprinting performances, along with the components of their horizontal and vertical F-V profiles. They were analyzed twice. The first analysis corresponded to Pearson’s correlation analysis and the second one was a partial correlation analysis controlling for the effect of training experience (years of specific soccer training) and body size. Correlation effects were interpreted as small (0.10–0.29), moderate (0.30–0.49), large (0.50–0.69), and very large ( ≥ 0.70) [ 36 ]. Stepwise linear regression analyses were conducted between either participants’ maturity offset or chronological age (dependent variable) and parameters of the horizontal and vertical F-V profiles (independent variables). The same regression analyses were conducted including also body size and training experience as independent variables. Coefficients of determination (R 2 ), unstandardized beta (regression) coefficients (B), SE of B (B SE ), and standardized beta (regression) coefficients ( β ) were also calculated. Significance for all analyses was set at p < 0.05 3. Results Table 1 displays the descriptive data for chronological age, body mass, stature, sitting height, 5 m sprint time, 20 m sprint time, and CMJ height of participants for each category Table 1. Descriptive statistics (mean ± standard deviation) of chronological age, body mass, stature, sitting height, 5 m sprint time, 20 m sprint time, and countermovement jump (CMJ) height of participants for each category Category n Age (years) Weight (kg) Stature (cm) Sitting Height (cm) 5 m Time (s) 20 m Time (s) CMJ Height (cm) U 18 18 17.27 ± 0.46 71.78 ± 11.37 177.39 ± 6.89 91.72 ± 3.04 1.55 ± 0.07 3.70 ± 0.14 35.0 ± 5.34 U 16 17 14.54 ± 0.45 61.12 ± 12.63 164.53 ± 5.0 87.98 ± 2.67 1.51 ± 0.15 3.98 ± 0.30 25.92 ± 4.97 U 14 17 12.71 ± 0.42 44.48 ± 7.06 151.47 ± 6.03 79.72 ± 3.17 1.61 ± 0.15 4.23 ± 0.36 22.35 ± 5.02 U 12 19 10.55 ± 0.44 43.58 ± 8.58 144.42 ± 6.19 75.22 ± 3.23 1.70 ± 0.14 4.52 ± 0.37 18.45 ± 5.83 U 10 18 8.40 ± 0.41 29.72 ± 5.17 129.0 ± 4.49 66.15 ± 2.30 1.78 ± 0.16 4.70 ± 0.40 18.06 ± 4.84 U number: under specific chronological age Associations among performance variables and maturity offset and chronological age are shown in Figure 1 . Very large correlations were identified between CMJ height and 20 m sprint times (Figure 1 ).
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 5 of 11 Int. J. Environ. Res. Public Health 2021 , 18 , x FOR PEER REVIEW 5 of 12 Table 1. Descriptive statistics (mean ± standard deviation) of chronological age, body mass, stature, sitting height, 5 m sprint time, 20 m sprint time, and countermovement jump (CMJ) height of participants for each category . Category n Age (years) Weight (kg) Stature (cm) Sitting Height (cm) 5 m Time (s) 20 m Time (s) CMJ Height (cm) U 18 18 17.27 ± 0.46 71.78 ± 11.37 177.39 ± 6.89 91.72 ± 3.04 1.55 ± 0.07 3.70 ± 0.14 35.0 ± 5.34 U 16 17 14.54 ± 0.45 61.12 ± 12.63 164.53 ± 5.0 87.98 ± 2.67 1.51 ± 0.15 3.98 ± 0.30 25.92 ± 4.97 U 14 17 12.71 ± 0.42 44.48 ± 7.06 151.47 ± 6.03 79.72 ± 3.17 1.61 ± 0.15 4.23 ± 0.36 22.35 ± 5.02 U 12 19 10.55 ± 0.44 43.58 ± 8.58 144.42 ± 6.19 75.22 ± 3.23 1.70 ± 0.14 4.52 ± 0.37 18.45 ± 5.83 U 10 18 8.40 ± 0.41 29.72 ± 5.17 129.0 ± 4.49 66.15 ± 2.30 1.78 ± 0.16 4.70 ± 0.40 18.06 ± 4.84 U number: under specific chronological age Figure 1. Associations between the performance in 5 m sprint, 20 m sprint, and countermovement jump, and maturity offset ( A , C and E , respectively), and chronological age ( B , D and F , respectively). Significant correlations: * p < 0.001 Partial correlations between 5 m, 20 m, and CMJ height and maturity offset controlling for training experience and body size were r = 0.23 p = 0.034), and 0.4 and 0.54 ( p < 0.001), respectively. Partial correlations between 5 m, 20 m, and CMJ height and chronological age controlling for training experience and body size were r = 0.25 ( p = 0.02), 0.45, and 0.56 p < 0.001), respectively Descriptive statistics of the different components of the vertical and horizontal F-V profiles, and Pearson correlation coefficients between them and both maturity offset and chronological are displayed in Table 2 .
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 6 of 11 Table 2. Descriptive statistics of parameters of the force-velocity profiles in sprinting and vertical jumping, and correlation coefficients and p -values between these parameters, either not controlling for or considering the influence of training experience and body size, and both maturity offset and chronological age (CA) Maturity Offset CA Bivariate r Partial r Bivariate r Partial r Sprinting Mean SD r p r p r p r p F 0 (N) 309.43 132.15 0.89 <0.001 0.7 <0.001 0.85 <0.001 0.62 <0.001 V 0 (m · s − 1 ) 6.57 1.06 0.77 <0.001 0.45 <0.001 0.79 <0.001 0.51 <0.001 P max (W) 530.41 286.63 0.92 <0.001 0.78 <0.001 0.9 <0.001 0.73 <0.001 FV slope (N · s · m − 1 ) 2572.87 1714.82 − 0.79 <0.001 − 0.56 <0.001 − 0.74 <0.001 − 0.51 <0.001 DRF (%) –0.09 0.02 0.29 0.005 0.18 0.098 0.29 0.007 0.2 0.065 RF peak (%) 0.43 0.05 0.59 <0.001 0.26 0.015 0.61 <0.001 0.3 0.005 Jumping Mean SD r p r p r p r p F 0 (N) 1407.2 618.21 0.91 <0.001 0.79 <0.001 0.89 <0.001 0.75 <0.001 V 0 (m · s − 1 ) 3.62 1.08 0.23 0.034 0.11 <0.001 0.21 0.226 0.07 0.508 P max (W) 1277.69 695.75 0.87 <0.001 0.67 <0.001 0.83 <0.001 0.6 <0.001 FV slope (N · s · m − 1 ) 2292.78 1300.53 − 0.01 0.916 − 0.03 0.771 − 0.0 0.519 − 0.01 0.923 FV deficit (%) 8.63 3.69 0.49 <0.001 0.17 0.122 − 0.09 0.39 0.11 0.328 SD, standard deviation; r, Pearson’s correlation coefficient; F 0 , theoretical maximal force; V 0 , theoretical maximal velocity; FV slope, force-velocity slope; P max , theoretical maximal power; FV deficit, percent difference respect to the optimal FV profile; DRF, decrease in the ratio of horizontal force; RF peak: maximal ratio of horizontal force; Bivariate r : bivariate Pearson’s correlation; Partial r : partial correlation controlling for training experience (years of specific soccer training) and body size (product of body mass and stature residuals [individual values minus the mean]);. Statistical significance set at p < 0.05 Both sprinting and jumping F-V parameters were similarly correlated with maturity offset and chronological age (Table 2 ). The largest correlations between parameters of the F-V profiles and both maturity offset and chronological age were identified in the F 0 and P max of both horizontal and vertical F-V profile components regardless of the influence of both body size and experience. The F-V slope and V 0 in sprinting exhibited very large and large correlations with maturity offset and chronological age with and without the influence of body size and experience, respectively. The other parameters showed lower correlation coefficients with maturity offset and chronological age (see Table 2 ). Four stepwise regression analyses were conducted between participants’ maturity offset and chronological age, and the sprinting FV profile components (i.e., F 0 , V 0 , P max , FV slope, DRF, and RF peak), and the jumping FV profile components (i.e., F 0 , V 0 , P max , FV slope, and FV deficit) either with or without the inclusion of training experience and body size as predictors (see Tables 3 and 4 ). Sprinting F-V profile parameters combining P max , DRF, and F 0 , P max , and DRF were able to explain up to 94% and 91% of the total variability of maturity offset and chronological age, respectively. However, when including body size and training experience as possible predictors, P max and training experience explained 95% of the variability of both maturity offset and chronological age (see Tables 3 and 4 ). Jumping F-V parameters combining F 0 and FV slope were able to explain up to 95% of the total variability of both maturity offset and chronological age. However, when including body size and training experience as independent variables in the regression analysis, F 0 , training experience and FV slope were also able to explain up to 95% of the total variability of both maturity offset and chronological age. Sprinting and jumping F-V parameters showed similar relationships with both maturity offset and chronological age in the stepwise linear regression analyses (Tables 3 and 4 ).
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 7 of 11 Table 3. Stepwise regression analyses relating both maturity offset and chronological age (CA) with components of force-velocity (FV) profiles in sprinting and jumping Sprinting Model 1 Model 2 Model 3 Maturity offset B SE B β B SE B β B SE B β P max 0.01 0 0.92 § 0.01 0 0.9 § 0.003 0.002 0.35 § DRF 22.65 6.36 0.14 † 38.94 8.5 0.24 § F 0 0.11 0.004 0.55 † R 2 adjusted 0.849 0.867 0.877 CA B SE B β B SE B β B SE B β P max 0.01 0 0.9 § 0.01 0 0.87 § DRF 27.57 9.24 0.14 † R 2 adjusted 0.8 0.817 Jumping Model 1 Model 2 Maturity offset B SE B β B SE B β F 0 0.004 0 0.91 § 0.004 0 0.96 § FV slope − 0.15 0.03 − 0.23 § R 2 adjusted 0.834 0.882 CA B SE B β B SE B β F 0 0.004 0 0.89 § 0.005 0 0.94 § FV slope − 0.18 0.04 − 0.21 § R 2 adjusted 0.792 0.831 FV slope, force-velocity slope; V 0 , theoretical maximal velocity; F 0 , theoretical maximal force; P max , theoretical maximal power; FV deficit, percent difference respect to the optimal FV profile; R 2 = Pearson’s multivariate coefficient of determination; B = unstandardized beta (regression) coefficient; SE B = standard error of B; β = standardized beta (regression) coefficient † p < 0.01, § p < 0.001 Table 4. Stepwise regression analyses relating both maturity offset and chronological age (CA) with components of force-velocity (FV) profiles in sprinting and jumping, body size, and training experience Sprinting Model 1 Model 2 Model 3 Maturity offset B SE B β B SE B β B SE B β P max 0.01 0 0.92 § 0.01 0 0.64 § 0.01 0.001 0.76 § Training experience 0.39 0.06 0.36 § 0.38 0.06 0.36 § RF peak − 7.76 2.22 − 0.16 † R 2 adjusted 0.849 0.897 0.909 CA B SE B β B SE B β B SE B β P max 0.01 0 0.9 § 0.01 0 0.55 § 0.01 0 0.62 § Training experience 0.58 0.08 0.43 § 0.53 0.08 0.4 § Body size 0.12 0.04 0.12 * R 2 adjusted 0.8 0.87 0.881 Jumping Model 1 Model 2 Maturity offset B SE B β B SE B β B SE B β F 0 0.004 0 0.91 § 0.003 0 0.7 § 0.003 0 0.74 § Training experience 0.43 0.06 0.4 § 0.36 0.05 0.33 § FV slope − 0.11 0.2 − 0.17 § R 2 adjusted 0.834 0.901 926 CA B SE B β B SE B β B SE B β F 0 0.004 0 0.89 § 0.003 0 0.54 § 0.003 0 0.62 § Training experience 0.61 0.08 0.46 § 0.54 0.07 0.4 § FV slope − 0.12 0.3 − 0.14 § R 2 adjusted 0.792 0.880 0.896 FV slope, force-velocity slope; V 0 , theoretical maximal velocity; F 0 , theoretical maximal force; P max , theoretical maximal power; FV deficit, percent difference respect to the optimal FV profile; Training experience: years of specific soccer training; Body size: product of body mass and stature residuals (individual values minus the mean); R 2 = Pearson’s multivariate coefficient of determination; B = unstandardized beta (regression) coefficient; SE B = standard error of B; β = standardized beta (regression) coefficient. * p < 0.05, † p < 0.01, § p < 0.001.
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 8 of 11 4. Discussion The aims of this study were to determine the relationships between performance and the different components of the F-V profile in jumping and sprinting, and the maturity offset and chronological age of young soccer players, and to compare relationships between maturity offset and chronological age for jumping and sprinting. The main findings of the current research are that the horizontal F-V components F 0 , V 0 , P max , FV slope, and vertical F-V components F 0 and P max displayed very large correlations with both chronological age and maturity offset regardless of the influence of body size and training experience. Additionally, different combinations of sprinting P max , DRF, F 0 , and training experience and body size explained more than 91% of the variations in maturity offset and chronological age. Furthermore, different combinations of jumping F 0 and FV slope and training experience explained 95% of the variances in maturity offset and chronological age. In addition, and contrary to our hypothesis, similar correlations were found between sprinting and jumping performances, and components of the F-V profiles with either maturity offset or chronological age Previously, Buchheit et al. [ 10 ] found that F 0 , V 0 , and P max were highly related to performance in acceleration and sprinting speed in players from U 13 to U 19 categories. The current results also confirm the relevance of these components, along with FV slope, on the development of sprinting performance in young soccer players as they showed very large correlations with maturity status and chronological age. According to the current results, F 0 , V 0 , and P max develop throughout the maturation process as long as sprinting performance, stature, weight, and muscle mass are increased due to the growing process [ 37 ]. Furthermore, the FV slope is decreased with maturation and age, thereby strengthening the relevance of F 0 in contrast to V 0 [ 2 ]. Therefore, the results of this study show a constant and homogeneous development in sprinting mechanical determinants such as P max , F 0 , V 0 , RF peak, and FV slope, but not in DRF. These results mean that older and more mature soccer players display better performance in these sprinting F-V components. Therefore, these F-V components can be considered very important and complementary markers of sprinting performance development, in order to improve the quality of training monitoring processes, rather than only evaluating sprinting times Moreover, the combination of P max , DRF, and F 0 was able to explain more than 91% of the variance in biological and chronological age, whereby P max was its highest predictor (Table 3 ). In addition, the inclusion of independent variables such as body size and training experience in the regression analysis improved its ability to predict both maturity offset and chronological age (Table 4 ), thereby also showing the influence of these variables on the sport development of young soccer players and more specifically on the development of sprinting F-V components [ 38 , 39 ]. Sprinting performance also displayed a very large correlation with maturity offset (Figure 1 ), confirming the findings by M é ndez-Villanueva et al. [ 20 ], who found that sprinting ability in U 14, U 16, and U 18 soccer players was highly related to the changes associated to biological maturation. Similar results were found in Australian footballers from U 11 to U 19 squads [ 40 ]. In contrast, McCunn et al. [ 41 ] found trivial and small correlation between maturation and sprinting speed (15 m) in U 11, U 12, and U 13 soccer players. These different results may be due to the different statistical analyses conducted between these studies. Whereas McCunn et al. [ 41 ] found a lack of correlation between the maturity offset and sprint performance only in the U 11–13 categories, in Gastin et al. [ 40 ] the correlations were conducted for the whole sample (U 11 − 19 categories). Similarly, CMJ performance in the current study displayed a very large correlation with biological maturation (Figure 1 ), which is in agreement with a previous study by Lloyd et al. (2015) [ 23 ]. In any case, these results should be taken cautiously since these important correlations were substantially reduced when body size and training experience were included as covariables in the analysis. In addition, Murtagh et al. [ 29 ] found that 10 m and 20 m sprint performances differed between young soccer players and non-trained controls of similar maturation status, while CMJ height differed between groups only in the postand mid-PHV sub-
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 9 of 11 groups. Accordingly, these authors suggested that vertical jumping ability should not be considered as a performance determinant in pre-PHV soccer players. In contrast, we found a large correlation between CMJ performance and maturity offset. In addition, jumping F 0 and P max displayed very large correlation effects with maturity offset. These results mean that more mature and older soccer players display greater performance in these F-V components. This may be explained by the considerable increases in muscle mass observed at different ages [ 42 ], thereby generating a higher rate of development of these jumping determinants during the fastest stages of growth [ 43 ]. In addition, jumping F 0 highly contributed to explain variability of both maturity offset and chronological age along with FV slope. Therefore, this result along with that similarly found in the correlation analysis indicate that F 0 is the mechanical determinant of jumping performance that evolves to the greatest extent across the development process in young soccer players One of the novelties of the current study is the evaluation of the relationships between F-V parameters in both jumping and sprinting and chronological age. The fact that similar relationships were found between these variables and maturity offset and chronological age is in contrast to previous research which highlighted the need to relate performance development to maturation status in order to determine talent identification markers [ 17 , 41 ]. Whereas growth and strength development are not entirely associated with chronological age evolution, especially at some specific stages [ 17 , 41 ], according to the present results, it seems that these differences are not enough to be taken into consideration throughout the whole development process. Accordingly, Mendez-Villanueva et al. [ 20 ] found significant differences between young soccer players of different categories (i.e., chronological ages) in sprint performance, but when controlling for maturation status, these differences disappeared. Thus, biological and chronological ages similarly influence the evolution of sprinting capabilities in young soccer players A limitation of the current study is that only players from the same academy were evaluated, therefore these results should be extrapolated to other contexts with caution 5. Practical Applications and Conclusions The frequent application of jumping and linear sprinting tests to obtain the forcevelocity profiles may provide useful information in young soccer players. In this sense identification of some sprint and jumping mechanical determinants such as F 0 , V 0 , P max and FV slope, and F 0 and P max , respectively, at a specific age or maturation status in young soccer players, may assist to strengthen those components of the F-V profile which are weaker throughout the training process. Accordingly, some training methods could be implemented in the training regime of young soccer players, such as resisted sprint training (with sled or vest) or assisted sprint training (with the use of bungee cords or an assistance pulley), which promote the development of the horizontal strength component across the entire spectrum [ 44 – 46 ] and provide an orientation towards either strength or speed depending on the specific needs of the athlete [ 47 ]. However, some jumping F-V mechanical determinants such as V 0 are not expected to increase with the maturation process or age. In addition, the results of the present study suggest that sprinting and jumping capabilities in young soccer player can be indistinctly monitored with respect to their chronological age or to maturity offset. As an example, a 15 year-old soccer player who did not improve V 0 after the pre-season, despite improving the sprinting time, should focus on developing this component through the implementation of specific training exercises such as those previously mentioned (e.g., unloaded maximal sprints) thus correcting the F-V imbalance, independently of the maturational status. Combining sprinting P max , DRF, F 0 , jumping F 0 , and FV slope, in addition to body size and training experience, can explain, to a very great extent, the changes in both maturity offset and chronological age. Sprint and CMJ performances and sprinting and jumping components of the F-V profiles correlate similarly with both maturity offset and chronological age in young soccer players. Further studies may focus on the analysis of the differences of sprinting and jumping F-V profile components between pre-, mid-, and post-pubertal young soccer players
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Int. J. Environ. Res. Public Health 2021 , 18 , 4646 10 of 11 Author Contributions: Conceptualization, L.M.F.-G., P.J.-R., D.B. and A.C.; methodology, P.J.-R. and A.C.; investigation, L.M.F.-G. and A.C.; writing—original draft preparation, L.M.F.-G. and A.C.; writing—review and editing, L.M.F.-G., P.J.-R., D.B. and A.C.; supervision, P.J.-R., D.B., V.C.-P. and A.C. All authors have read and agreed to the published version of the manuscript Funding: This research received no external funding Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the ethical committee of Isabel I de Castilla International University (protocol number UI 1-PI 016) Informed Consent Statement: Informed consent was obtained from all subjects involved in the study Acknowledgments: The authors gratefully thank the subjects who participated in the current study Conflicts of Interest: The authors declare no conflict of interest References 1 Jim é nez-Reyes, P.; Samozino, P.; Brughelli, M.; Morin, J.B. Effectiveness of an individualized training based on force-velocity profiling during jumping Front. Physiol 2017 , 7 , 677. [ CrossRef ] 2 Samozino, P.; Rabita, G.; Dorel, S.; Slawinski, J.; Peyrot, N.; Saez de Villarreal, E.; Morin, J.B. A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running Scand. J. Med. Sci. Sport 2016 , 26 , 648–658 [ CrossRef ] [ PubMed ] 3 Jim é nez-Reyes, P.; Samozino, P.; Pareja-Blanco, F.; Conceiç ã o, F.; Cuadrado-Peñafiel, V.; Gonz á lez-Badillo, J.J.; Morin, J.B. Validity of a simple method for measuring force-velocity-power profile in countermovement jump Int. J. Sports Physiol. Perform 2017 , 12 , 36–43. [ CrossRef ] 4 Garc í a-Ramos, A.; Feriche, B.; P é rez-Castilla, A.; Padial, P.; Jaric, S. Assessment of leg muscles mechanical capacities: Which jump, loading, and variable type provide the most reliable outcomes? Eur. J. Sport Sci 2017 , 17 , 690–698. [ CrossRef ] [ PubMed ] 5 Jim é nez-Reyes, P.; Samozino, P.; Cuadrado-Peñafiel, V.; Conceiç ã o, F.; Gonz á lez-Badillo, J.J.; Morin, J.B. Effect of countermovement on power–force–velocity profile Eur. J. Appl. Physiol 2014 , 114 , 2281–2288. [ CrossRef ] 6 Morin, J.B.; Samozino, P. Interpreting power-force-velocity profiles for individualized and specific training Int. J. Sports Physiol Perform 2016 , 11 , 267–272. [ CrossRef ] [ PubMed ] 7 Jim é nez-Reyes, P.; Samozino, P.; Garc í a-Ramos, A.; Cuadrado-Peñafiel, V.; Brughelli, M.; Morin, J.B. Relationship between vertical and horizontal force-velocity-power profiles in various sports and levels of practice PeerJ 2018 , 6 , e 5937. [ CrossRef ] [ PubMed ] 8 Jim é nez-Reyes, P.; Garc í a-Ramos, A.; Cuadrado-Peñafiel, V.; P á rraga-Montilla, J.A.; Morcillo-Losa, J.A.; Samozino, P.; Morin, J.B Differences in sprint mechanical force–velocity profile between trained soccer and futsal players Int. J. Sports Physiol. Perform 2019 , 14 , 478–485. [ CrossRef ] 9 Marcote-Pequeño, R.; Garc í a-Ramos, A.; Cuadrado-Peñafiel, V.; Gonz á lez-Hern á ndez, J.M.; G ó mez, M Á .; Jim é nez-Reyes, P Association between the force–velocity profile and performance variables obtained in jumping and sprinting in elite female soccer players Int. J. Sports Physiol. Perform 2019 , 14 , 209–215. [ CrossRef ] 10 Buchheit, M.; Samozino, P.; Glynn, J.A.; Michael, B.S.; Al Haddad, H.; Mendez-Villanueva, A.; Morin, J.B. Mechanical determinants of acceleration and maximal sprinting speed in highly trained young soccer players J. Sports Sci 2014 , 32 , 1906–1913. [ CrossRef ] 11 Nagahara, R.; Morin, J.B.; Koido, M. Impairment of sprint mechanical properties in an actual soccer match: A pilot study Int. J Sports Physiol. Perform 2016 , 11 , 893–898. [ CrossRef ] 12 Cross, M.R.; Lahti, J.; Brown, S.R.; Chedati, M.; Jimenez-Reyes, P.; Samozino, P.; Eriksrud, O.; Morin, J.B. Training at maximal power in resisted sprinting: Optimal load determination methodology and pilot results in team sport athletes PLoS ONE 2018 , 13 , e 0195477. [ CrossRef ] 13 Baumgart, C.; Freiwald, J.; Hoppe, M. Sprint Mechanical Properties of Female and Different Aged Male Top-Level German Soccer Players Sports 2018 , 6 , 161. [ CrossRef ] 14 Morin, J.B.; Edouard, P.; Samozino, P. Technical ability of force application as a determinant factor of sprint performance Med Sci. Sports Exerc 2011 , 43 , 1680–1688. [ CrossRef ] 15 Castagna, C.; D’Ottavio, S.; Abt, G. Activity Profile of Young Soccer Players During Actual Match Play J. Strength Cond. Res 2003 , 17 , 775–780. [ CrossRef ] 16 Hulse, M.A.; Morris, J.G.; Hawkins, R.D.; Hodson, A.; Nevill, A.M.; Nevill, M.E. A field-test battery for elite, young soccer players Int. J. Sports Med 2013 , 34 , 302–311. [ CrossRef ] 17 Malina, R.M.; Peña Reyes, M.E.; Figueiredo, A.J.; Coelho E Silva, M.J.; Horta, L.; Miller, R.; Chamorro, M.; Serratosa, L.; Morate, F. Skeletal age in youth soccer players: Implication for age verification Clin. J. Sport Med 2010 . [ CrossRef ] 18 Malina, R.M.; Bouchard, C. Growth, Maturation, and Physical Activity Med. Sci. Sport. Exerc 1992 . [ CrossRef ] 19 Mirwald, R.L.; Baxter-Jones, A.D.G.; Bailey, D.A.; Beunen, G.P. An assessment of maturity from anthropometric measurements Med. Sci. Sports Exerc 2002 , 34 , 689–694. [ CrossRef ] [ PubMed ]
[[[ p. 11 ]]]
Int. J. Environ. Res. Public Health 2021 , 18 , 4646 11 of 11 20 Mendez-Villanueva, A.; Buchheit, M.; Kuitunen, S.; Douglas, A.; Peltola, E.; Bourdon, P. Age-related differences in acceleration, maximum running speed, and repeated-sprint performance in young soccer players J. Sports Sci 2011 , 29 , 477–484. [ CrossRef ] [ PubMed ] 21 Asadi, A.; Ramirez-Campillo, R.; Arazi, H.; S á ez de Villarreal, E. The effects of maturation on jumping ability and sprint adaptations to plyometric training in youth soccer players J. Sports Sci 2018 , 36 , 2405–2411. [ CrossRef ] 22 Colyer, S.L.; Nagahara, R.; Takai, Y.; Salo, A.I.T. The effect of biological maturity status on ground reaction force production during sprinting Scand. J. Med. Sci. Sport 2020 , 30 , 1387–1397. [ CrossRef ] 23 Lloyd, R.S.; Oliver, J.L.; Radnor, J.M.; Rhodes, B.C.; Faigenbaum, A.D.; Myer, G.D. Relationships between functional movement screen scores, maturation and physical performance in young soccer players J. Sports Sci 2015 , 33 , 11–19. [ CrossRef ] 24 Moran, J.J.; Sandercock, G.R.H.; Ram í rez-Campillo, R.; Meylan, C.M.P.; Collison, J.A.; Parry, D.A. Age-related variation in male youth athletes’ countermovement jump after plyometric training: A meta-analysis of controlled trials J. Strength Cond. Res 2017 , 31 , 552–565. [ CrossRef ] 25 Moran, J.; Parry, D.A.; Lewis, I.; Collison, J.; Rumpf, M.C.; Sandercock, G.R.H. Maturation-related adaptations in running speed in response to sprint training in youth soccer players J. Sci. Med. Sport 2018 , 21 , 538–542. [ CrossRef ] 26 Pion, J.; Segers, V.; Fransen, J.; Debuyck, G.; Deprez, D.; Haerens, L.; Vaeyens, R.; Philippaerts, R.; Lenoir, M. Generic anthropometric and performance characteristics among elite adolescent boys in nine different sports Eur. J. Sport Sci 2015 , 15 , 357–366 [ CrossRef ] [ PubMed ] 27 Hertzog, M.; Paul, D.; Nassis, G.; Silva, J. Does Early Recruitment Predict Greater Physical Performance in Academy Soccer Players? Sports 2018 , 6 , 108. [ CrossRef ] [ PubMed ] 28 Peña-Gonz á lez, I.; Fern á ndez-Fern á ndez, J.; Moya-Ram ó n, M.; Cervell ó , E. Relative Age Effect, Biological Maturation, and Coaches’ Efficacy Expectations in Young Male Soccer Players Res. Q. Exerc. Sport 2018 , 89 , 373–379. [ CrossRef ] 29 Murtagh, C.F.; Brownlee, T.E.; O’Boyle, A.; Morgans, R.; Drust, B.; Erskine, R.M. Importance of speed and power in elite youth soccer depends on maturation status J. Strength Cond. Res 2018 , 32 , 297–303. [ CrossRef ] 30 Thomis, M.; Claessens, A.L.; Lefevre, J.; Philippaerts, R.; Beunen, G.P.; Malina, R.M. Adolescent growth spurts in female gymnasts J. Pediatr 2005 , 146 , 239–244. [ CrossRef ] [ PubMed ] 31 Moore, S.A.; McKay, H.A.; Macdonald, H.; Nettlefold, L.; Baxter-Jones, A.D.G.; Cameron, N.; Brasher, P.M.A. Enhancing a somatic maturity prediction model Med. Sci. Sports Exerc 2015 , 47 , 1755–1764. [ CrossRef ] [ PubMed ] 32 Malina, R.M.; Claessens, A.L.; Van Aken, K.; Thomis, M.; Lefevre, J.; Philippaerts, R.; Beunen, G.P. Maturity offset in gymnasts: Application of a prediction equation Med. Sci. Sports Exerc 2006 , 38 , 1342–1347. [ CrossRef ] 33 Samozino, P.; Edouard, P.; Sangnier, S.; Brughelli, M.; Gimenez, P.; Morin, J.B. Force-velocity profile: Imbalance determination and effect on lower limb ballistic performance Int. J. Sports Med 2014 , 35 , 505–510. [ CrossRef ] [ PubMed ] 34 Balsalobre-Fern á ndez, C.; Glaister, M.; Lockey, R.A. The validity and reliability of an iPhone app for measuring vertical jump performance J. Sports Sci 2015 , 33 , 1574–1579. [ CrossRef ] 35 Romero-Franco, N.; Jim é nez-Reyes, P.; Castaño-Zambudio, A.; Capelo-Ram í rez, F.; Rodr í guez-Juan, J.J.; Gonz á lez-Hern á ndez, J.; Toscano-Bendala, F.J.; Cuadrado-Peñafiel, V.; Balsalobre-Fern á ndez, C. Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods Eur. J. Sport Sci 2017 , 17 , 386–392. [ CrossRef ] [ PubMed ] 36 Hopkins, W.G.; Marshall, S.W.; Batterham, A.M.; Hanin, J. Progressive statistics for studies in sports medicine and exercise science Med. Sci. Sports Exerc 2009 , 41 , 3. [ CrossRef ] [ PubMed ] 37 Meylan, C.M.P.; Cronin, J.B.; Oliver, J.L.; Hughes, M.G.; McMaster, D.T. The reliability of jump kinematics and kinetics in children of different maturity status J. Strength Cond. Res 2012 , 26 , 1015–1026. [ CrossRef ] 38 Malina, R.M.; Cumming, S.P.; Kontos, A.P.; Eisenmann, J.C.; Ribeiro, B.; Aroso, J. Maturity-associated variation in sport-specific skills of youth soccer players aged 13-15 years J. Sports Sci 2005 , 23 , 515–522. [ CrossRef ] 39 Lima, A.B.; Nascimento, J.V.; Leonardi, T.J.; Soares, A.L.; Paes, R.R.; Gonçalves, C.E.; Carvalho, H.M. Deliberate practice, functional performance and psychological characteristics in young basketball players: A bayesian multilevel analysis Int. J Environ. Res. Public Health 2020 , 17 , 4078. [ CrossRef ] 40 Gastin, P.B.; Bennett, G.; Cook, J. Biological maturity influences running performance in junior Australian football J. Sci. Med Sport 2013 , 16 , 140–145. [ CrossRef ] 41 McCunn, R.; Weston, M.; Hill, J.K.A.; Johnston, R.D.; Gibson, N.V. Influence of Physical Maturity Status on Sprinting Speed among Youth Soccer Players J. Strength Cond. Res 2017 , 31 , 1795–1801. [ CrossRef ] 42 Malina, R.M. Quantification of fat, muscle and bone in man Clin. Orthop. Relat. Res 1969 , 65 , 9–38. [ CrossRef ] 43 Meylan, C.M.; Cronin, J.; Hopkins, W.G.; Oliver, J. Adjustment of measures of strength and power in youth male athletes differing in body mass and maturation Pediatr. Exerc. Sci 2014 , 26 , 41–48. [ CrossRef ] [ PubMed ] 44 Tufano, J.J.; Amonette, W.E. Assisted Versus Resisted Training Strength Cond. J 2018 , 40 , 106–110. [ CrossRef ] 45 Upton, D.E. The effect of assisted and resisted sprint training on acceleration and velocity in Division IA female soccer athletes J. Strength Cond. Res 2011 , 25 , 2645–2652. [ CrossRef ] [ PubMed ] 46 Tamilrasi, K.; Maniazhagu, D. Effects of combination of assisted and resisted sprint training on agiity among male soccer players Int. J. Phys. Educ. Sport. Manag. Yogic Sci 2014 , 4 , 23–28. [ CrossRef ] 47 Lahti, J.; Jim é nez-Reyes, P.; Cross, M.R.; Samozino, P.; Chassaing, P.; Simond-Cote, B.; Ahtiainen, J.P.; Morin, J.-B. Individual Sprint Force-Velocity Profile Adaptations to In-Season Assisted and Resisted Velocity-Based Training in Professional Rugby Sports 2020 , 8 , 74. [ CrossRef ]
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Jumping, Maturation process, Maturation, Sprint, Body size, Statistical analyses, Chronological age, Maturation status, Stepwise linear regression, Talent Identification, Creative Commons Attribution, Regression analyses, Vertical jump, Countermovement jump, Young soccer players, Sprint performance, Maximal power, Training Experience, Training method, Soccer player, Vertical jumping, Jumping performance, Horizontal, Vertical, Maturity status, Partial correlation analysis, Jumping test, Biological maturation, Peak height velocity, V 0, Maturity offset.
