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Article

Age Is a New Indicator of Long-Ball Kicking Performance in Young Soccer Players: Analysing Kinanthropometry, Flexibility and Strength

by
Antonio Cejudo
1,*,
José Manuel Armada-Zarco
1 and
Riccardo Izzo
2
1
Department of Physical Activity and Sport, Faculty of Sport Sciences, CEIR Campus Mare Nostrum (CMN), University of Murcia, 30720 Murcia, Spain
2
Department of Biomolecular Sciences, School of Sport and Health Sciences, University of Urbino Carlo Bo, 61029 Urbino, Italy
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(19), 9052; https://doi.org/10.3390/app14199052
Submission received: 8 August 2024 / Revised: 2 October 2024 / Accepted: 5 October 2024 / Published: 7 October 2024
(This article belongs to the Special Issue Advances in Assessment of Physical Performance)
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Abstract

:
(1) Background: The kick of the ball in soccer is considered one of the most important technical gestures in soccer. Despite this, there is little evidence on ball-striking performance factors in base soccer. The main objectives of the present study were to identify the potential factors of long-ball kicking (LBK) performance and to determine the target training cut-off for LBK performance in young soccer players. (2) Methods: A cross-sectional observational study was conducted with 31 soccer players, with ages ranging from 12 to 18 years. Age, anthropometric data, sport experience, range of motion (ROM) and maximal isometric strength (MIS) of the lower limb were noted. Kick-of-the-ball performance was assessed by maximum ball displacement per kick. A k-mean cluster analysis determined two groups according to ball-kicking performance: low group (LPG-LBK) and high group (HPG-LBK). (3) Results: Differences were found between both groups in age, body mass, body mass index, leg length and knee flexion ROM (BF10 ≤ 6.33; δ ≥ 0.86 (moderate or higher)). Among the factors discussed above, age was the strongest predictor of ball-striking performance (odds ratio = 2.867; p = 0.003). The optimal cut-off for age predicting those players most likely to have a higher ball-striking performance was determined to be 13.5 years (p = 0.001; area under the curve = 85.3%). (4) Conclusions: Age over 13.5 increases the chances of a higher optimal ball-striking performance. The flexibility (knee flexion ROM) and strength (knee flexors) must be specifically trained in soccer players beginning at an early age.

1. Introduction

In professional soccer, a distinction is made between the teaching of the formative phases (non-specialisation, initiation, development and improvement) and the learning stages. These formative stages are associated with the categories of grassroots soccer according to the age-group of the players, Benjamin (U10), Alevín (U12), Infantil (U14), a (U16), Juvenile (U18) and Senior (18 or more years). The Alevín (U12) category is considered the most complicated formative stage due to the transition of soccer players from 8-a-side soccer (8 vs. 8) to 11-a-side soccer (11 vs. 11). The considerable increase in the dimensions of the soccer field can be a relevant physical and technical–tactical difficulty for these young players. The 8 vs. 8 soccer field is between 50 and 65 m long and between 30 and 45 m wide, while the 11 vs. 11 soccer field is between 90 and 120 m long and between 45 and 90 m wide [1].
This significant change requires a higher level of physical and technical–tactical preparation of youth soccer players. It can also be observed that some coaches demand technical actions from their young players, such as a forceful clearance, a long pass or a shot on goal from outside the penalty area in soccer. However, players show physical limitations due to the priority that coaches give to teaching technical and tactical content [2,3]. For optimal long-distance or long-ball kicking (LBK), coaches should be aware of the factors that influence kicking performance for each of the above technical actions. Previous scientific studies have reported that ball-kicking performance depends on age [2,3]; biological maturation [4]; body mass and height [2,5]; skill level [6]; shot precision [7,8]; kicking speed [2,3,9]; reaction forces with both the stance leg and the kicking leg [6,9]; and optimal ranges of motion of the trunk, pelvis, hips and knees [6,10,11]. Also, biological maturation must be taken into account in LBK and physical preparation, which is an individual process, with a peak growth rate or peak height velocity at around 14 years of age [4]. Strength, flexibility and neuromotor training of the lower limbs and trunk are modifiable factors in U12 soccer players that have a positive impact on speed and accuracy of kicking to improve LBK performance, especially when young players receive verbal instructions from their coach on the two characteristics of ball kicking, such as “shoot the ball towards the goal as quickly as possible” or “ shoot the ball as quickly as possible and try to hit the centre of the goal” [12].
Several experts [4] recommend training players in the general motor skills (strength, flexibility, speed, coordination and cardiorespiratory endurance) that predispose to physical performance, taking into account the sensitive stages, the characteristics of the training methods and previous training experience. However, researchers have not focussed on producing scientific studies that determine the quantitative requirements for the general motor skills needed for the most demanding technical requirements, such as the required LBK according to age or maturation [4,13]. Understanding LBK development from this perspective could have practical applications for the design and implementation of a physical and technical training programme and highlight the critical and sensitive periods for the development of specific LBK performance parameters. To our knowledge, there are no studies investigating this topic. Therefore, the main objectives of the present study were to identify the potential factors of LBK performance and to determine the target training cut-off for LBK performance in young soccer players.

2. Materials and Methods

2.1. Research Design

The study, which complies with the guidelines of the Declaration of Helsinki, was approved by the Ethics and Research Committee of the University of Murcia (CEI 4018/2022).
A cross-sectional observational study was conducted with 31 male youth soccer players to determine the training goals of the performance factors identified in the LBK. At the start of the season, the club’s management and coaching staff were informed of the key objectives of the study. Following approval, an introductory meeting was held with coaches, players and legal guardians to inform them about the methodology and potential risks of the scientific study. All players confirmed at the introductory meeting that they had read the detailed information about the research study and signed the informed consent form for their participation. In the case of minors, the legal guardians have signed the informed consent form. The players were also informed about the possibility of voluntarily withdrawing from the study at any time, without giving reasons. The evaluators answered any questions the players had before, during or after the research study.
This was followed by a familiarisation session with the test procedure and a warm-up before the assessment session. This session also served to record the age, anthropometric data and soccer history of the players (years of experience, number of competitions per season, weekly training frequency and duration of training sessions) by the evaluators of the study. Finally, the assessment took place during the competition period in the club’s facilities under standard conditions of 25°. The measurements were carried out by two evaluators with at least three years of testing experience.
Before the measurement, the players received general and specific warm-up training for each test, following the recommendations from the scientific literature [14,15,16,17]. The players were assessed in their usual training clothing. The order of the three procedures was the measurement of flexibility through range of motion (ROM), maximal isometric strength (MIS) and the LBK test. The different tests in each of these three content blocks were randomised. All tests were performed on both sides of the body. Each test was performed three times, and its average was used for further analysis [18].

2.2. Participants

A convenience sample of 31 young male soccer players (Infantil, U14; Cadete, U16; and Juvenile, U18) voluntarily participated in the scientific study. The players were 14.68 ± 2.10 years old, with 57.29 ± 12.09 kg body weight, 1.69 ± 0.09 cm body height, 19.76 ± 2.74 kg/m2 body mass index and 0.67 ± 0.05 m leg length. In terms of soccer background, the players had 7.71 ± 1.40 years of soccer experience, 3.65 ± 0.49 days of weekly training frequency, 370.32 ± 68.09 min of weekly training and 62.26 ± 15.86 min of participation in competitions. Players showed no signs and symptoms of orthopaedic problems in the lower limbs or spine that could affect physical–athletic competence, anthropometric characteristics, ROM and MIS during the previous two weeks and the evaluation session. Players who showed muscle pain, muscle soreness or overuse due to the weekend competition during the evaluation were excluded.

2.3. Evaluators

Data collection in this research study was conducted by two evaluators with at least three years of experience in musculoskeletal assessment. In general, the main evaluator was responsible for using the instrument and measuring the test, while the assistant evaluator controlled for possible compensatory movements [14,19].
Previously, an absolute intra-evaluator reliability study (two assessment sessions 24 h apart) was conducted with 10 players, and it showed excellent reproducibility of the evaluators (intraclass correlation coefficient greater than 0.91 with 95% probability and a minimum detectable change with 95% probability less than or equal to 5° in the ROM tests and 11.3 Newtons in the MIS tests).

2.4. Procedure

2.4.1. Tests to Assess Range of Motion (ROM)

The maximum passive range of motion (ROM) (Figure 1) of hip flexion with the knee extended (HF-KE) and flexed (HF-KF), hip extension (HE) and knee flexion (KF) was measured using the ROM-SPORT I battery [19]. The ROM-SPORT I method was designed so that the muscle at the end of the maximum passive ROM (muscle extensibility) is the protagonist of the joint tissue. In this sense, maximal passive movement was defined by the observation of a compensatory movement that falsely increased the ROM (false negative) and the feeling of discomfort or muscle stretching by the player. The described angle between the longitudinal axis of the mobilised body segment (along its bisector) and the horizontal gravity 0° was then measured [19].
The ROM measurement was performed using an ISOMED Unilevel inclinometer (ISOMED Unilevel, Inc., Portland, OR, USA) with an extendable telescopic rod, the reliability and validity of which were demonstrated in a systematic review [15,19]. A rigid back support or Lumbosant© (Imucot Traumatología SL, Murcia, Spain) was used to place and hold the pelvis in a neutral position (20°). The assistant evaluator was responsible for controlling the compensatory movements, while the main evaluator performed the main movement and the control of some compensatory movements [19].

2.4.2. Tests to Assess Maximal Isometric Strength (MIS)

The MIS of the hip flexors (HFs) and extensors (HEs), as well as the knee flexors (KFs) and extensors (KEs) (Figure 2) was measured using a previously described method [20,21] that indirectly measures kicker force. To achieve isometric muscle contraction, an extendable arm was used to apply the player’s force against a wall or table. This strategy prevents the final result of the measurement from being increased by the additional force applied by the evaluator to withstand the thrust exerted by the player [14].
A Lafayette handheld dynamometer (Lafayette® Instrument Company, Lafayette, IN, USA), whose validity and reliability has been demonstrated in previous scientific studies with soccer players, was used to measure MIS in Newtons [22,23].

2.4.3. Test to Assess the Long-Ball Kicking (LBK)

To evaluate the LBK performance, it was carried out according to the methodological proposal of previous scientific studies, with the instruction to hit the ball as fast as possible and the goal of reaching the centre circle of the field [2,3,9]. The variable measured in terms of kicking performance was the maximum distance reached in meters by the ball after the instep kick [2]. The greatest distance reached in meters by the ball after the ball was kicked by the dominant limb was taken. To include a player in the high-performance group in the LBK (HPG-LBK), the cut-off distance established by a statistical cluster analysis was used.

2.5. Statistical Analysis

Statistical analyses were performed using the software JASP version 0.14.01 (JASP team of the University of Amsterdam, Amsterdam, The Netherlands). If the p-value is less than 0.05, it is judged as “significant”.
The data were first tested for normal distribution using the Shapiro–Wilk test. Abnormally distributed data showed a Gaussian distribution after log transformation. The descriptive statistics of the measured variables (age, kinanthropometry, sports history, ROM and MIS) were expressed as mean ± standard deviation. The presence of an asymmetry between the values of the dominant and non-dominant side was analysed using the Bayesian Paired Samples T-Test.
A k-means cluster analysis was performed to classify the players in the low-performance group in long-ball kicking (LPG-LBK) and the high-performance group in long-ball kicking (HPG-LBK).
Previously, an ANOVA analysis was performed to control for random effects, including the dichotomous variable ball-kicking performance (LPG-LBK vs. HPG-LBK) as a fixed factor and the performance variables as the dependent variable. The values of effect sizes η2 was interpreted using the following evidence categories: small for 0.01, medium for 0.06 and large for 0.14 [24].
The presence of differences in the independent variables measured between the two groups (LPG-LBK vs. HPG-LBK) was then analysed using the Bayesian Independent Samples T-Test. The BF10 was interpreted using the following evidence categories [25]: <1/100 = extreme evidence for H0, 1/100 to 1/30 = very strong evidence for H0, 1/30 to 1/10 = strong evidence for H0, 1/10 to 1/3 = moderate evidence for H0, and 1/3 to 1 anecdotal evidence for null (H0); and 1 to 3 = anecdotal evidence for H1, 3 to 10 = moderate evidence for H1, 10 to 30 = strong evidence for H1, 30 to 100 = very strong evidence for H1, and >100 extreme evidence for alternative hypothesis (H1). Models that showed at least moderate evidence, with a percentage error > 3, were considered sufficiently robust to describe the main effects. The mean and 95% interval credible of the posterior distribution of the standardized effect size (δ) was calculated (i.e., the population version of Cohen’s d) for comparisons between groups.
Binary logistic regression analysis was performed to determine the performance factors (measured independent variables) associated with HPG-LBK. Odd ratios (ORs) were used in the logistic regression model to compare the influence of the independent (or explanatory) variables on the dependent variable (HPG-LBK). The effect sizes for OR were defined as follows: OR for a small effect = 1 to 1.25, OR for a medium effect = 1.25 to 2, and OR for a large effect ≥ 2 [26].
An optimal cut-off value for these predictors of HPG-LBK performance was determined using receiver operating characteristic (ROC) analyses and the Youden index with the JAMOVI software version 1.6.23. The AUC value was classified as outstanding (0.90 ≥ AUC < 1.00), excellent (0.80 ≥ AUC < 0.90), acceptable (0.70 ≥ AUC < 0.80), poor (0.50 ≥ AUC < 0.80) and no discrimination (AUC < 0.50). In addition, the positive predictive value (PPV) and the negative predictive value (NPV) were calculated.
Finally, a Bayesian Independent Samples T-Test for independent samples was performed to determine whether there were differences between LPG-LBK and HPG-LBK as possible predictors of HPG-LBK performance.

3. Results

The ANOVA analysis (random effects) found significant differences in age (F1,29 = 28.531, p ≤ 0.001, η2 = 0.496, ES = small), body mass (F1,29 = 16.750, p ≤ 0.001, η2 = 0.366, ES = small), body mass index (F1,29 = 24.473, p ≤ 0.001, η2 = 0.452, ES = small), leg length (F1,29 = 8.277, p = 0.007, η2 = 0.222, ES = small), soccer experience (F1,29 = 4.740, p = 0.038, η2 = 0.140, ES = small) and KF ROM (F1,29 = 18.354, p ≤ 0.001, η2 = 0.388, ES = small).
The descriptive analysis found only differences between both body sides in the MIS-KE (BF10 = 539.02, δ = 0.80 (strong)) in the 31 soccer players (Table 1).
The cluster analysis obtained two groups (LPG-LBK vs. HPG-LBK) that determined the LBK cut-off point (HPG-LBK) at a distance of 30 or more meters. A total of 17 players (54.8%) exceeded this distance when kicking the ball.
In Table 2, differences were found between LPG-LBK and HPG-LBK in terms of age, body mass, body mass index, leg length and KF ROM (BF10 ≤ 6.33; δ ≥ 0.86 (moderate or higher)). The values in this variable are higher in the HPG-LBK players than in the LPG-LBK players.
A prediction model was created based on the variables that showed differences between LPG-LBK and HPG-LBK. The model summary (enter method) showed a significant relationship between the HPG-LBK and the predictor variable age for H1 (χ2(29) = 18.481; p < 0.001). The Akaike Information Criteria and Bayesian Information Criteria for model fit were 28.204 and 31.072, respectively. The statistical value R2 showed a good model fit, 60.1% for Nagelkerke’s R2, 43.3% for McFadden’s R2 and 49.7% for Tjur’s R2. The age (OR = 2.867 (large); 95% CI = 0.356 to 1.751; p = 0.003) was the predictor variables in the players. The model’s performance diagnostics yielded a sensitivity of 0.765 (13 out of 17) and a specificity of 1.000 (14 out of 14).
The area under the curve (AUC) of the receiver operating characteristic (ROC) curves was 0.853, indicating a good predictive model accuracy for the HPG-LBK, which was statistically significant (p = 0.001; Standard Error: 0.73; 95% CI: 0.710 to 0.996). Using the coordinates of the curves, the age that most accurately identified individuals at HPG-LBK was determined to be 13.5 years or older (sensitivity = 94.12%; specificity = 21.43%; Youden Index = 0.155) (Figure 3). The probability (positive predictive value) that a player aged 13.5 or older would kick a ball 30 metres or more (HPG-LBK) was 76.5%, and the probability (negative predictive value) that a player aged over 13.5 would not reach 30 metres with a ball kick (LPG-LBK) was 71.4%.
Finally, Table 3 shows the differences (BF10 ≤ 6.79; δ ≥ 0.87 (moderate or higher)) in the independent variables analysed in the players after the optimal cut-off point of 13.5 years.

4. Discussion

To the authors’ knowledge, this is the first study to predict the potential determinants of LBK performance (maximum horizontal distance) and to determine the target training cut-off for LBK performance in young soccer players. Before answering both objectives based on the data obtained, kicking is a complex biomechanical sequence in which the foot contacts the ball [27], and both the speed and accuracy of the kick are determined by the resultant forces applied to the ball as it interacts with the foot [27,28]. Unsurprisingly, both the speed and accuracy of kicking improve with the physical and technical development of players [2,5]. Soccer kicking has been the subject of scientific research for more than 50 years, but no studies have been found to determine the values of predictors of performance in LBK training as a guide for training. An LBK refers to a pass, a shot or a clearance that is classified according to the distance the ball travels [29]. In particular, pass and shoot in soccer are classified into two (short and long) or three (short, medium and long) categories [29,30]. Amado-Peña et al. classify a short pass as being from 0 to 10 m, a medium pass as being from 10 to 20 m and a long pass as being more than 20 m for formative-stage players between the ages of 7 and 16 years [29]. Konefał et al., who analysed the performance frequency of selected technical activities in international soccer players during UEFA Euro 2016, defined long pass and short pass quantitatively at a cut-off of 22.86 m (25 yards) [31]. After studying the changes in technical and physical performance between the first and second half of official Italian Serie A matches, Rampinini et al. proposed the cut-off between short pass and long pass at a distance of 37 m in 186 soccer players with an average age of 27 years [32]. Abbott et al., who investigated the effect of bio-banding upon physical and technical performance of youth soccer players (11–15 years), establish the cut-off between short and long pass at 20 m and stated in their definition that the pass is directed to his teammate and that he successfully controls the ball [30]. In the present study, the long pass at a distance of 30 metres or more was determined on the basis of the participants’ results and the subsequent statistical analysis according to the homogeneity criterion (k-means cluster) for players aged between 12 and 18 years. The proposal by Abbott et al. could be more interesting, as they analyse the physical and technical performance of players according to their biological maturity and age rather than their chronological age. Executing an LBK involves kicking the ball with power and precision. This requires activating the muscles of the lower limbs, such as the iliacus, quadriceps, gluteus, adductors, hamstrings, gastrocnemius and tibialis anterior [33,34]. Maximising ball speed is a key element for LBK success [5,6,35], which depends on various factors such as age, skill level, approach angle and lateral dominance [2,3,6].
In the present study, age, kinanthropometry, hip and knee range of motion, and strength were factors associated with LBK performance. However, age was the most important predictor that distinguished the players with a ball kicking of more than 30 metres. These results are consistent with those found in previous research studies of one hundred and six young elite soccer players (12–15 years) [2], adult (male and female) [3] and male pubertal players [3]. On the contrary, no differences in soccer background were found depending on the cut-off point of ball kicking performance (≥30 m). However, the training load of soccer players in different age categories (U-12, U-15 and U-23) [36] and differences in anthropometric and physical fitness variables (handgrip strength, flexibility, vertical jump, countermovement jump, sprints and agility t-test, and repeated sprint ability 15 × 15 m) variables based on chronological age (7 and 15 years old) in young soccer players [37,38].
After classifying the players in relation to the optimal value of age (13.5 years or older), it was found that the HPG-LBK players had higher values in the evaluated variables such as age, body mass, body height, body mass index, leg length, soccer background, HE ROM, KF ROM, HE MIS and KF MIS. On the other hand, no differences in soccer background were found depending on the cut-off value of age (13.5 years or older), but a significant trend is observed in minutes played weekly in competition (average difference 13 min).
Soccer players at a higher performance level generally have higher values for kinanthropometric variables such as body mass, body height, lower limb length and body mass index than players at a lower performance level [3,39,40]. Players with delayed biological maturation in any age group are likely to have lower ball-kicking performance due to disadvantages in body mass, body height and muscle mass [35]. The differences in biological maturation in the form of growth spurts and changes in body composition, as well as the changing dimensions of the soccer field, have a greater impact on the physical, technical and tactical performance of pre-pubertal adolescent players than on pubertal or post-pubertal players [3,35]. As far as the authors are aware, previous studies have shown no relationship or association between the variables (body mass, body height and body mass index) and kicking performance (maximum horizontal distance). Players of older age and greater body height, body weight, leg mass and relative lean mass kick the ball with greater speed and accuracy using both limbs, the dominant and non-dominant sides [3,5,35,41,42]. Taller soccer players perform better in technical actions that require speed and strength due to the mechanical advantage of longer limbs [35,43]. However, no differences were found in aerobic endurance and soccer-specific skills such as short passing, kicking accuracy or ball control [43]. Wong et al. found that body mass correlates with kicking speed and the 30 m sprint. Body height correlated with vertical jump height, 10 m and 30 m sprint, distance in the Yo-Yo Intermittent Running Test and running time in a maximal oxygen consumption test [44]. In other sports, a larger body size (arm or forearm length) is associated with faster ball speed in handball players [45,46] and a faster ball strike in tennis [47]. Our results support these findings in relation to the maximum horizontal distance of the ball after kick in players with greater height or lower limb length, resulting in a higher kick performance in soccer (HPG-LBK). Based on these findings, youth soccer coordinators and coaches should consider the variation in kinanthropometric variables within age groups or competition categories when planning sports, especially in young players between 12 and 20 years of age, in order to achieve higher athletic performance with lower risk of injury [5]. In contrast, after biological development, no correlation was found between body weight and height and kicking performance, especially kicking speed, in older players, such as college [48] and Senior soccer players [49].
The results show higher ROM-HE and ROM-KF in those players achieving LBK (≥30 m). These results are consistent with previous research assessing HF-KE ROM [50,51,52]. Correlations were found between hip-extension ROM and some of the kicking variables, such as HE ROM and KF ROM, during kicking in 60 men aged between 18 and 33 years [50]. García-Pinillos et al. [51] showed that 43 young male soccer players (aged 14–18 years) with good hamstring flexibility (HF-KE ROM) performed better in tests of acceleration and sprinting (5 m, 10 m and 20 m), countermovement jump, Balsom agility and kicking speed in relation to ball speed than players with lower hamstring flexibility [51]. Oliveira et al. concluded that HF-KE ROM may be a crucial factor in skill performance, as shown by the deficits in kicking in soccer players with shortened hamstrings compared to athletes with stretched hamstrings [52]. In the present study, the players in the HPG-LBK group also had higher HF-KE ROM values than the players in the LPG-LBK group. According to biomechanical concepts, greater muscle extensibility enables an increase in the arc of tension, and the movement trajectories relate to increased segmental speed [11]. During the of kick, maximal spine, pelvis, hip, and knee movements generate a full body tension arc (defined as ROM of hip extension, spine extension, spine rotation to the non-kick side, and pelvis anterior tilt at key point maximal HE ROM and KF ROM at key point maximal knee flexion). The pre-stretching of the muscles (the backswing phase causes a maximal hip extension and stretching of the iliopsoas, and the leg-cocking phase causes maximal knee flexion and stretching of the quadriceps) that connect the segments of the upper body and the kicking leg [53] increases the muscle contraction forces through the mechanism of the stretch-shortening cycle, which leads to an acceleration of the segments during the leg-cocking and acceleration phases [54]. The greater the distance over which these segments move (movement trajectory), the greater the potential to develop segmental velocity [50], and the sum of the segmental velocities finally determines the velocity of the ball [10,55]. Furthermore, optimal muscle flexibility does not restrict ROM in the follow-through phase of the kick [11,55]. In practise, optimal hip and knee flexibility must be achieved and maintained so that it is not impaired by age [56], maturation [56,57], performance level or sport category [56], competitive load [58] and lack of stretching exercise during training and competition [59,60] in youth soccer players. Several authors have demonstrated the effectiveness of stretching methods on the dynamic ROM and kicking speed of the lower-extremity joints during kicking in soccer players [61,62].
Regarding MIS, HPG-LBK players report higher values than LPG-LBK players in all muscles assessed, especially KF MIS, as classified by LBK performance and age cut-off value. This consistency is normal, as HPG-LBK players have a higher volume of soccer history (sports seasons, weekly training frequency, weekly training minutes and minutes of competition participation). The significant differences observed in the HE MIS and the KF MIS could be due to the importance of the hip extensors, such as the gluteus maximus and hamstring or gluteus medius in the LBK [33]. In the LBK, the instep kick is mainly used to kick the ball or for long passes. Correspondingly, the gluteus maximus and medius showed greater activation in the kicking limb in all phases (gluteus maximus, vastus medialis and gluteus medius in the preparation phase; iliacus and gluteus medius in the backswing phase; iliacus and vastus medialis in the cocking phase; iliacus and gluteus maximus in the acceleration phase; and gluteus maximus, iliacus and gluteus medius in the follow-through phases) [33]. In addition to activating the supporting-limb muscles during the instep kick, the hamstrings contribute to the higher activation with the gluteus maximus and medius (gluteus maximus and gluteus medius in the preparation phase; gluteus maximus, gluteus medius and hamstrings in the backswing phase; vastus medialis and gluteus medius in the cocking phase; vastus medialis and gluteus medius in the acceleration phase; and vastus medialis, gluteus medius and hamstrings in the follow-through phase) [33]. Supporting-limb muscle activation is important for performance when LBK [42]. Studies reporting on the correlation between strength and kicking performance show the importance of hip flexor and quadriceps strength. Also, there is some evidence that adequate strength of the stance leg, trunk muscles, hip adductors and muscles that control pelvic rotation are important [33,63]. However, strength training of the lower limbs and trunk should be trained in parallel with kicking technique [42,64], focussing on aspects such as the type of kicks, inter-segmental motion pattern transfer of speed from the foot to the ball (open kinetic chain system) [65] and optimum projection angle [66]. On the contrary, Masuda et al. show that technical skill is more important than strength [67].
The limitations of the study are as follows: (i) it was a cross-sectional study that cannot provide a direct assessment of age-related changes and the ball-kicking performance; (ii) the size of the sample with different ages, levels and regions does not allow us to extend the generality and applicability of the results; and (iii) it did not include a control of motivation and concentration, which can influence ball-kicking performance.
For future research, a longitudinal study should be designed with a larger stratified sample that shows differences in age (no more than two years), level and region. Furthermore, the inclusion of additional measures of kicking ability, including physical–technical (such as precision and speed) and psychological (such as motivation and concentration) factors, should be considered.

5. Conclusions

A soccer coach should solicit long-ball kicking from young soccer players 13.5 years of age or older. The flexibility (KF ROM) and strength training (KF MIS), as well as neuromotor skills (shank–foot segment travels through a higher ROM, kicking speed and kicking accuracy) and various kicking techniques must be specifically trained in soccer players beginning at an early age.

Author Contributions

Conceptualization, A.C. and R.I.; methodology, A.C.; software, A.C.; validation, A.C., R.I. and J.M.A.-Z.; formal analysis, A.C. and J.M.A.-Z.; investigation, A.C. and R.I.; resources, A.C. and J.M.A.-Z.; data curation, A.C. and J.M.A.-Z.; writing—original draft preparation, A.C. and J.M.A.-Z.; writing—review and editing, A.C.; visualization, A.C.; supervision, A.C. and R.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of University of Murcia (CEI 4018/2022) for studies involving humans.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data associated with the study are not publicly available but are available from the corresponding author upon reasonable request.

Acknowledgments

I would like to thank the athletes who volunteered to participate in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Applsci 14 09052 g001
Figure 1. Assessment of hip and knee range of motion using the ROM-SPORT I battery.
Figure 1. Assessment of hip and knee range of motion using the ROM-SPORT I battery.
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Figure 2. Assessment of the maximal isometric strength of the hip and knee flexors and extensors.
Figure 2. Assessment of the maximal isometric strength of the hip and knee flexors and extensors.
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Figure 3. Sensitivity, specificity, area under the curve and cut-off point of age as a predictor of long-ball kicking.
Figure 3. Sensitivity, specificity, area under the curve and cut-off point of age as a predictor of long-ball kicking.
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Table 1. Differences between the two sides of the body in terms of leg length, range of motion and maximal isometric strength (torque).
Table 1. Differences between the two sides of the body in terms of leg length, range of motion and maximal isometric strength (torque).
Dominant LimbNon-Dominant LimbBF10δ (95% Credible Interval)Evidence for H1
Anthropometrics
Leg length (cm)0.67 ± 0.050.68 ± 0.060.677−0.28
(−0.62, 0.07)		Anecdotal
Range of motion (degrees)
HE ROM18.13 ± 5.0215.84 ± 5.261.240.34
(−0.00, 0.69)		Anecdotal
HF-KE ROM76.94 ± 14.1275.32 ± 13.160.310.22
(−0.11, 0.57)		Anecdotal
HF-KF ROM125.48 ± 9.95121.94 ± 13.820.640.58
(−0.07, 0.63)		Anecdotal
KF ROM90.65 ± 21.9488.23 ± 21.550.470.16
(−0.17, 0.51)		Anecdotal
Torque (N*m/kg)
HF MIS0.96 ± 0.360.93 ± 0.402.430.12
(−0.21, 0.45)		Anecdotal
HE MIS1.31 ± 0.371.21 ± 0.370.240.40
(0.05, 0.77)		Anecdotal
KF MIS0.71 ± 0.280.64 ± 0.263.410.43
(0.07, 0.80)		Anecdotal
KE MIS1.87 ± 0.391.50 ± 0.33539.020.80
(0.39, 1.23)		Extreme
ROM, range of motion; HF-KE ROM, hip flexion with the knee extended ROM; HF-KF ROM, hip flexion with the knee flexed ROM; HE ROM, hip extension ROM; KF ROM, knee flexion ROM; MIS, maximal isometric strength; HF MIS, hip flexors MIS; HE MIS, hip extensors MIS; KF, knee flexors MIS; KE MIS, knee extensors MIS.
Table 2. Differences in age, soccer background, anthropometrics, range of motion and maximal isometric strength (torque) according to the cut-off point of ball kicking performance (≥30 m).
Table 2. Differences in age, soccer background, anthropometrics, range of motion and maximal isometric strength (torque) according to the cut-off point of ball kicking performance (≥30 m).
LPG-LBK
Group (n = 14)		HPG-LBK
Group (n = 17)		Total
(n = 31)		BF10δ (95% Credible Interval)Evidence for H1
Age and anthropometrics
Age (y)13.07 ± 0.7316.00 ± 1.9414.68 ± 2.101563.76−1.73
(−2.65, 0.75)		Extreme
Body mass (kg)49.36 ± 9.0263.82 ± 10.3857.29 ± 12.0980.80−1.29
(−2.12, −0.51)		Very Strong
Body height (m)1.66 ± 0.091.72 ± 0.091.69 ± 0.091.313−0.53
(−1.25, 0.11)		Anecdotal
Body mass index (kg/m2)17.75 ± 1.7421.41 ± 2.2719.76 ± 2.74601.06−1.61
(−2.48, −0.68)		Extreme
Leg length (cm)0.65 ± 0.050.70 ± 0.050.67 ± 0.056.33−0.86
(−1.62, −0.18)		Moderate
Soccer background
Experience (y)7.14 ± 1.038.18 ± 1.517.71 ± 1.401.93−0.62
(−1.34, 0.05)		Anecdotal
Weekly training (min)354.12 ± 72.03390.00 ± 59.61370.32 ± 68.090.780.41
(−0.21, 1.08)		Anecdotal
Weekly competition (min)57.14 ± 12.6766.47 ± 17.3062.26 ± 15.860.97−0.47
(−1.18, 0.17)		Anecdotal
Range of motion (degrees)
HE ROM15.82 ± 4.0518.39 ± 3.8716.98 ± 4.121.120.50
(−0.16, 1.22)		Anecdotal
HF-KE ROM73.38 ± 13.5879.46 ± 11.6576.13 ± 12.910.660.36
(−0.26, 1.04)		Anecdotal
HF-KF ROM121.18 ± 7.56126.79 ± 12.76123.71 ± 10.450.810.41
(−0.22, 1.09)		Anecdotal
KF ROM77.65 ± 21.37103.75 ± 8.5989.44 ± 21.21125.331.39
(0.63, 2.23)		Extreme
Torque (N*m/kg)
HF MIS0.89 ± 0.500.98 ± 0.200.94 ± 0.370.40−0.17
(−0.81, 0.44)		Anecdotal
HE MIS1.14 ± 0.281.36 ± 0.381.26 ± 0.351.19−0.51
(−1.21, 0.12)		Anecdotal
KF MIS0.59 ± 0.210.75 ± 0.270.68 ± 0.251.17−0.51
(−1.22, 0.13)		Anecdotal
KE MIS1.61 ± 0.251.74 ± 0.321.68 ± 0.290.62−0.34
(−0.98, 0.28)		Anecdotal
LPG-LBK, low-performance group in long-ball kicking; HPG-LBK, high-performance group in long-ball kicking; ROM, range of motion; HF-KE ROM, hip flexion with the knee extended ROM; HF-KF ROM, hip flexion with the knee flexed ROM; HE ROM, hip extension ROM; KF ROM, knee flexion ROM; MIS, maximal isometric strength; HF MIS, hip flexor MIS; HE MIS, hip extensor MIS; KF, knee flexor MIS; KE MIS, knee extensor MIS.
Table 3. Differences in age, soccer background, body composition, range of motion and maximal isometric strength (torque) according to the cut-off point of the predictor age (13.5 years).
Table 3. Differences in age, soccer background, body composition, range of motion and maximal isometric strength (torque) according to the cut-off point of the predictor age (13.5 years).
Group < 13.5 Years Old (n = 14)Group ≥ 13.5 Years Old (n = 17)BF10δ (95% Credible Interval)Evidence for H1
Age and Anthropometrics
Age (y)12.71 ± 0.4716.29 ± 1.401.217 × 107−3.15
(−4.25, −2.19)		Extreme
Body mass (kg)48.71 ± 10.3964.35 ± 8.32300.38−1.51
(−2.38, −0.56)		Extreme
Body height (m)1.64 ± 0.101.74 ± 0.0612.58−0.99
(−1.78, −0.29)		Strong
Body mass index (kg/m2)17.86 ± 2.0921.31 ± 2.19183.47−1.41
(−2.30, 0.57)		Extreme
Leg length (cm)0.64 ± 0.050.70 ± 0.0423.93−1.07
(−1.90, −0.34)		Strong
Soccer background
Experience (y)7.36 ± 0.938.00 ± 1.660.64−0.35
(−1.04, 0.26)		Anecdotal
Weekly training (min)380.0 ± 65.63362.35 ± 71.020.410.19
(−0.43, 0.83)		Anecdotal
Weekly competition (min)55.36 ± 17.3767.94 ± 15.822.57−0.47
(−1.18, 0.17)		Anecdotal
Range of motion (degrees)
HE ROM19.11 ± 3.8715.24 ± 3.526.790.87
(0.16, 1.63)		Moderate
HF-KE ROM80.00 ± 11.6472.94 ± 13.350.840.43
(−0.22, 1.13)		Anecdotal
HF-KF ROM125.89 ± 12.69121.91 ± 8.130.520.28
(−0.35, 0.96)		Anecdotal
KF ROM103.93 ± 8.4877.50 ± 21.21153.841.41
(0.61, 2.23)		Extreme
Torque (N*m/kg)
HF MIS0.88 ± 0.521.00 ± 0.170.47−0.25
(−0.88, 0.36)		Anecdotal
HE MIS1.13 ± 0.371.37 ± 0.301.44−0.55
(−1.27, 0.09)		Anecdotal
KF MIS0.54 ± 0.230.79 ± 0.229.31−0.93
(−1.71, −0.22)		Moderate
KE MIS1.61 ± 0.301.75 ± 0.280.64−0.35
(−1.03, 0.29)		Anecdotal
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Cejudo, A.; Armada-Zarco, J.M.; Izzo, R. Age Is a New Indicator of Long-Ball Kicking Performance in Young Soccer Players: Analysing Kinanthropometry, Flexibility and Strength. Appl. Sci. 2024, 14, 9052. https://doi.org/10.3390/app14199052

AMA Style

Cejudo A, Armada-Zarco JM, Izzo R. Age Is a New Indicator of Long-Ball Kicking Performance in Young Soccer Players: Analysing Kinanthropometry, Flexibility and Strength. Applied Sciences. 2024; 14(19):9052. https://doi.org/10.3390/app14199052

Chicago/Turabian Style

Cejudo, Antonio, José Manuel Armada-Zarco, and Riccardo Izzo. 2024. "Age Is a New Indicator of Long-Ball Kicking Performance in Young Soccer Players: Analysing Kinanthropometry, Flexibility and Strength" Applied Sciences 14, no. 19: 9052. https://doi.org/10.3390/app14199052

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