Profiling of Physical Qualities of Highly Trained Portuguese Youth Soccer Players

Abstract

Background: A comprehensive understanding of variations in physical attributes both between and within young players is crucial for accurately identifying talent based on physical performance. This study aimed to compare maximum strength, jump, and sprint test results among young soccer players from different age categories and playing positions. Secondarily, this study aimed to analyze the association between maximum strength, jump, and sprint performances. Methods: A total of 103 players were categorized as U23, U19, U17, and U16. The players were placed into these age categories based on their football abilities. All participants completed standardized warm-ups, and testing procedures followed protocols established in previous studies. Results: Significant differences were found between age categories regarding the Isometric Mid-Thigh Pull (p < 0.001; η²_p = 0.33), Countermovement Jump (CMJ) (p < 0.001; η²_p = 0.50), Squat Jump (SJ) (p < 0.001; η²_p = 0.29), and sprint (p < 0.001; η²_p = 0.30) tests. No significant differences were detected in Broad Jump results between age categories. Moreover, no significant differences were observed in any physical capacities between playing positions. Furthermore, significant moderate-to-strong correlations (r = 0.30–0.86) were observed between all physical tests. Conclusions: Age categories can distinguish soccer players’ performance in different physical tests while no differences were observed between playing positions. Similar magnitude correlations were observed across all tests with only the CMJ and SJ being strongly correlated. Coaches and strength and conditioning professionals should apply a variety of tests to assess different physical qualities since they have different patterns between age categories.

1. Introduction

The profiling of soccer players highlights physical, physiological, and anthropometric characteristics [1,2,3]. Previous studies have reported significant differences regarding running performance and strength capacities between players of distinct age categories and playing positions [4,5]. Indeed, elite soccer players have shown better physical performance compared to their non-elite counterparts, whether at senior level or in youth categories [6]. This information is highly valuable for coaches and sports scientists since it enables the assessment and comparison of players’ physical capacities, regardless of their playing position or competition level [1]. Consequently, it supports the process of individualization during training prescriptions and load monitoring without disregarding the natural predisposition of some players to exhibit greater or lesser capacity in specific performance metrics [7]. In soccer, the profiling of players is intimately related to the profile of games and training practices, especially concerning the player’s field position and age category. Indeed, significant differences between playing positions and age categories in soccer players across different physical qualities were previously reported [8,9], demonstrating the necessity of coaches to individualize training prescriptions.

Soccer is characterized as a high-intensity interval-based sport, which requires a blend of skills such as speed, agility, endurance, and strength [10]. The most decisive actions in soccer depend on maximal strength and anaerobic power generated by the neuromuscular system, which is directly linked to the capacity for force production [11]. It has been suggested that the Isometric Mid-Thigh Pull (IMTP) test is effective for assessing maximum strength due to its validity, reliability, simplicity, and low risk [12]. Previous studies have reported that isometric tests such as the IMTP are well-suited for daily soccer routines since it results in minimal muscle damage compared to eccentric-based tests [13], which are commonly used for stratifying strength training programs, and serves as an index of fatigue [14]. Moreover, IMTP performance has been correlated with sprint performance, which is highly correlated with peak speed in professional English youth (U23) soccer players [12]. IMTP absolute peak force has shown greater differences in higher age categories, with moderate to large effect sizes (d = 0.62 to 1.66), and the largest effects observed in the highest age groups [15].

Jumping and sprinting abilities are widely used as indicators of neuromuscular fitness in youth players and as talent identification markers to differentiate between elite and non-elite soccer players [16]. Although jumping movements are not the most frequent in soccer matches, analytical testing involves lower technical complexity compared to sprinting and change of direction movements while providing distinct performance parameters. Vertical jumping, in particular, reflects lower-limb muscular explosive strength and is useful for monitoring training-induced adaptations [17,18]. Common exercises for evaluating rapid strength include the Countermovement Jump (CMJ) and Squat Jump (SJ) [19]. It has been reported that stronger players (measured via the IMTP) have demonstrated better CMJ performance [12].

Sprinting is another critical action that can determine the outcome of a soccer game. Indeed, straight sprints are the most dominant actions in scoring situations, with the majority performed without the ball, emphasizing the importance of assessing sprint performance [20,21]. Previous studies reported significant differences between age categories in sprinting performance [22]. Moreover, it has been shown that elite young soccer players are faster, stronger, and show better jumping performance than their non-elite counterparts [23]. Additionally, among elite young soccer players, noticeable differences between field positions are reported regarding various performance metrics including sprint, favoring higher performances of offensive position players (e.g., wide midfielders and forwards) [24,25].

Therefore, a comprehension of physical qualities between young players is essential for effectively recognizing talent based on their physical performance attributes and optimizing training strategies according to each player’s profile. This study aims to (i) compare the physical capacities of young soccer players from a professional club across different age categories; and (ii) compare the physical capacities between playing positions. Secondly the present study aims to analyze whether strength, jump, and sprint tests are correlated. The hypotheses are as follows: (i) higher age categories will perform better across all tests; (ii) forwards will achieve superior sprint test results compared to their peers in other positions; and (iii) IMTP and vertical jump tests will be correlated.

2. Methods

One hundred and three highly trained male soccer players from a Portuguese club, were recruited to participate in this study, from U23 (n = 24 players; age: 19.7 ± 1.6 yrs; height: 1.80 ± 0.07 m; body mass: 75.6 ± 6.9 kg), U19 (n = 28 players; age: 18.1 ± 0.6 yrs; height: 1.79 ± 0.06 m; body mass: 72.2 ± 6.8 kg), U17 (n = 25 players; age:16.6 ± 0.6 yrs; height: 1.76 ± 0.06 m; body mass: 67.9 ± 6.2 kg), and U16 (n = 26 players; age: 15.5 ± 0.5 yrs; height: 1.72 ± 0.06 m; body mass: 65.2 ± 8.6 kg). Regarding exclusion criteria, only goalkeepers and injured players, who were not able to be assessed in these tests, were excluded, in order to ensure a more representative number of subjects. Data collection was part of the teams’ routines in which players are assessed throughout the season. Therefore, normal ethics committee clearance was not required [26]. However, the club’s director provided written consent for the data for the study.

2.1. Dynamometry

The Piforce had two load cells (CATLT DYLY103) of 200 kg, each with a maximum capacity of 1961 N (one on each side to measure the force applied by each leg). The force was measured at a sampling rate of 80 Hz using an Arduino Uno with an HX711 converter. For the IMTP (Figure 1A), participants were placed in a standing position and the bar height was adjusted up or down to allow the athlete to obtain the optimal knee (125–145°) and hip (140–150°) angles [27]. Participants were instructed to exert force “as fast and strong as possible” to obtain peak force (PF) [28]. The PF was estimated with Python code using Visual Studio (Microsoft Corporation, Redmond, WA, USA). The onset of force production was defined by visual detection as previously suggested [28] for each maximal voluntary contraction (MVC) and quantified in Newtons. After that, all MVCs were processed using an automated routine in Visual Studio Code, which gave a Peak Force value for both cells. For data analysis, maximum repetition was selected for each test, and the average was calculated between the two cells for those tests.

2.2. Jumps and Speed Equipment

The CMJ, SJ, and DJ tests were assessed by Chronojump software (Chronojump 2.3.0-83), which has been used to assess jump metrics [29]. The Broad Jump (BJ) was assessed using a tape measure with participants being positioned with the front part of the foot on the 0 m mark. The sprint test was assessed by using the same Chronojump software (Chronojump 2.3.0-83) with two photocells that were placed at the 0 m mark and at the end mark (40 m), with the participant being positioned 1 m behind the photocell. These procedures were previously used to assess the speed of football players [1,30].

2.3. Protocols

Soccer players were familiarized with each exercise in previous training sessions. The tests were conducted under the same conditions with a 48 h recovery post-game. To increase the tests’ reliability, players performed the same warm-up protocol, which consisted of a 5 min exercise on a stationary bike. To minimize the fatigue effect between tests, the assessments were split into three sessions: one for the maximum strength test (IMTP), another for rapid strength tests (CMJ, SJ, DJ, and BJ), and a third for the sprint test. The order of the tests in each session was randomized. Regarding the IMTP, after the standard warm-up, players performed two maximal voluntary isometric contractions (MVICs) of 3 s with a 2 min recovery between trials. If a countermovement occurred prior to the beginning of the pull (IMTP), the trial was not considered, and the player was asked to repeat it. Moreover, in relation to the CMJ, SJ, DJ, and BJ, after the standard warm-up, players performed two maximal jumps with a 1 min recovery between reps. The DJ was performed from a 20 cm high box. For all jumps, if hip flexion, dorsiflexion, or an arm swing occurred along the jump, the trial was not considered, and the player was asked to repeat it. For the sprint test, after a general warm-up, players performed a single 40 m sprint after resting for 2 min. For all tests (with the exception of the IMTP), the best repetition was used in the analysis.

2.4. Statistical Analysis

All data were analyzed using IBM SPSS Statistics 27.0 (IBM Corporation, Armonk, NY, USA). An assumption test was first conducted to check for data normality, outliers, and homogeneity of variance-covariance matrices, with no violations identified. To analyze differences between age categories and playing positions, a one-way ANOVA was performed. Post-hoc analysis was conducted using Bonferroni correction to determine differences within each factor. Moreover, the correlation between tests were analyzed using Pearson’s and Spearman’s coefficient for normally and not normally distributed data, respectively. The correlation coefficients were classified as weak (<0.3), moderate (0.3–0.7), and strong (>0.7) [31]. The partial eta squared values were reported as a measure of the effect size of the ANOVA findings, and were classified as small (η²_p = 0.01–0.05), medium (η²_p = 0.06–0.013), and large (η²_p > 0.14) effects. Additionally, the significance was set at p < 0.05, and to analyze the effect size, it was also calculated by Cohen’s d.

3. Results

3.1. Playing Position

Comparing test results by playing position, no statistically significant differences were found: IMTP (p = 0.41; d = 0.04), CMJ (p = 0.26; d = 0.06), SJ (p = 0.11; d = 0.08), DJ (p = 0.35; d = 0.05), BJ (p = 0.33; d = 0.05), and sprint (p = 0.47; d = 0.04).

3.2. Age Categories

The results revealed that there were statistically significant differences in the IMTP (p < 0.001; η²_p = 0.33), CMJ (p < 0.001; η²_p = 0.495), SJ (p < 0.001; η²_p = 0.29), and sprint (p < 0.001; η²_p = 0.23) test results among all age categories.

Regarding IMTP performance (Figure 2A), significant differences were found in the following comparisons: U23 and U17 (U23 = 1706 ± 269 N; U17 = 1386 ± 199 N; p = 0.001; d = 1.68); U23 and U16 (U23 = 1706 ± 269 N; U16 = 1330 ± 228 N; p < 0.001; d = 1.51); and U19 and U16 (U19 = 1565 ± 176 N; U16 = 1330 ± 228 N; p = 0.007; d = 1.15).

For the SJ (Figure 2B), significant differences were detected between U23 and U16 (U23 = 36.26 ± 4.98 cm; U16 = 30.26 ± 3.87 cm; p < 0.001; d = 2.17); U19 and U16 (U19 = 36.11 ± 3.57 cm; U16 = 30.26 ± 3.87 cm; p < 0.001; d = 1.57); and U17 and U16 (U17 = 35.21 ± 4.14; U16 = 30.26 ± 3.87 cm; p = 0.003; d = 1.24).

In relation to the CMJ (Figure 2C), there were also significant differences in the following comparisons: U23-U16 (U23 = 38.60 ± 4.88 cm; U16 = 29.84 ± 3.83 cm; p < 0.001; d = 2.00); U19-U16 (U19 = 39.53 ± 3.68 cm; U16 = 29.84 ± 3.83 cm; p < 0.001; d = 3.56); and U17-U16 (U17 = 36.03 ± 3.81 cm; U16 = 29.84 ± 3.83 cm; p < 0.001; d = 1.62)

For the BJ (Figure 2D), the only differences that were found were when comparing the following: U23-U16 (U23 = 2.02 ± 0.11 cm; U16 = 1.86 ± 0.13 cm; p = 0.002; d = 2.01); and U19-U16 (U19 = 2.00 ± 0.15 cm; U16 = 1.86 ± 0.13 cm; p = 0.008; d = 12.76).

Regarding the sprint (Figure 2E), there were significant differences in the following comparisons: U23-U16 (U23 = 7.61 ± 0.24 m/s; U16 = 7.28 ± 0.35 m/s; p = 0.002; d = 1.10); U19-U16 (U19 = 7.62 ± 0.16 m/s; U16 = 7.28 ± 0.35 m/s; p < 0.001; d = 1.30); and U17-U16 (U17 = 7.73 ± 0.31; U16 = 7.28 ± 0.35 m/s; p < 0.001; d = 1.37).

3.3. Correlation Between Tests

Correlation analysis revealed that all physical performance tests were significantly correlated. Detailed information regarding the strength of the correlation and level of significance between tests can be found in

Table 1. Pearson correlation analysis between the different physical performance tests. * denotes a significant correlation between tests (p < 0.05).

	IMTP	Squat Jump	Countermovement Jump	Broad Jump	Sprint
IMTP		r = 0.30 (p = 0.003) *	r = 0.43 (p < 0.001) *	r = 0.38 (p < 0.001) *	r = 0.33 (p = 0.002) *
Squat Jump			r = 0.86 (p < 0.001) *	r = 0.59 (p < 0.001) *	r = 0.37 (p < 0.001) *
Countermovement Jump				r = 0.60 (p < 0.001) *	r = 0.42 (p < 0.001) *
Broad Jump					r = 0.39 (p < 0.001) *
Sprint

.

4. Discussion

To the best of our knowledge, this is the first study in soccer that compares physical assessment test results across different age categories and between playing positions, and correlates the physical tests. The main findings of this study were (i) higher age categories outperformed lower age categories in all tests; (ii) no differences were found between playing positions; and (iii) moderate correlations were seen between the IMTP and all the other tests while a strong correlation was observed between the SJ and CMJ.

In accordance with our initial hypothesis, players from higher age categories achieved generally better results. Indeed, significant differences were found on the IMTP between U23 and U17 and U16, and U19 and U16. These findings could be explained by size-dependent factors, such as muscle mass, as well as size-independent factors like genetics and hormonal influences [32]. Players from higher age categories are also more experienced in strength training, benefiting from the morphological and neural adaptations associated with the recurring strength training stimulus, resulting in a greater maximum force capacity. This is corroborated by studies showing an increase in peak force, measured via IMTP testing, with age throughout different age categories [15,33].

Regarding explosive force, statistically significant differences were found across all tests. The CMJ and SJ tests revealed differences between every age category compared to U16. Moreover, in the BJ, the U23 and U19 age categories performed better compared to the U16 age category. Jumping test performance provides shorter than necessary time-frames for players to achieve their maximal force capacity, and stronger players perform better in jump performance [34]. Stronger players present greater overall force generation capacity independent of the time constraints associated with force production. In fact, late rate of force development and maximum voluntary contraction torque were found to be correlated with muscle mass having a significant influence on the late rate of force development capacity [35]. However previous studies have reported divergent findings. For instance, Castagna and Castellini [19] found that vertical jump was not a suitable metric for distinguishing young Italian national players across different age categories (U17, U20, and U21). The results of the present study are consistent with this observation as the U23, U19, and U17 groups did not exhibit statistically significant differences in vertical jump performance. This lack of differentiation can be attributed to the average ages of the groups examined: 19.7 years for U23 and 18.1 years for U19, which approximately correspond to the U20 category in Castagna and Castellini’s study [19], and 16.6 years for U17, aligning closely with their U17 category. This age similarity could explain the similar performance, particularly between the U23 and U19 age categories.

Regarding sprint performance, significant differences were observed in all age categories outperforming the U16. Faster sprint speeds are associated with greater ground reaction forces [36], which faster players present as superior rapid force capacity. Indeed, players from higher age categories presented superior explosive force performance. This can also be attributed to the distinct maturational status of players since different maturational stages lead to specific physiological and structural changes [37,38,39]. Similar results were reported in two top-level Brazilian clubs in which senior and U20 players presented higher speeds in a linear 20 m sprint compared to U17 and U15 players [40]; significant age-related differences were observed in sprint performance among young soccer players as well [41].

Contrary to our initial hypothesis, no differences were found between playing positions, with previous studies reporting contrasting findings [1,42,43,44,45,46]. For example, greater sprint performance in forwards compared to defenders was observed across different sprint distances (5 m, 10 m, 20 m, and 30 m) [42,43]. On the other hand, no differences in 10 m and 30 m sprints between playing positions were reported [44,45,46]. Authors suggested that approaching the professional level at higher age categories, positional differences occur with forwards becoming the fastest players of the team [47]. One possible explanation could be due to modern soccer’s increasing emphasis on outfield players contributing to overall play, leading to more uniform physical performance across positions [48]. Moreover, a recent study reported no significant differences in sprint performance, knee flexor force capacity, and mechanical properties of the hamstrings between playing positions in players from different competition levels [1]. This finding suggests that such a phenomenon is not exclusive to youth development but also persists in senior competition contexts.

Regarding correlation between tests, a significantly stronger correlation was verified between the CMJ and SJ (r = 0.86; p < 0.001) due to similarities between the two tests since players applied vertical force on the ground (i.e., vertical force vector). The IMTP also revealed a moderate correlation with explosive jumping and sprinting. Previous studies demonstrated a moderate-to-strong correlation between the IMTP and sprint (r = −0.69; p ≤ 0.01) and jumping performance (r = 0.81; p ≤ 0.01), respectively [49,50]. Although stronger players tend to perform better in jumping and sprint performance tests, the moderate correlations found suggest that other factors besides peak torque are determinant for jumping and sprint performance such as neuromuscular coordination and rapid force development [51]. Both the CMJ and SJ were moderately correlated (r = 0.60; p < 0.001) with the BJ. Although these tests encompass a squatting pattern, the SJ and CMJ are essentially vertical-oriented while the BJ has a horizontal force component mediating jump performance [52].

Sprinting and jumping can be categorized as explosive movements. The results of the present study indicated that jumping tests were moderately correlated with sprint performance (r = 0.37–0.42; p < 0.001). However, sprinting and jumping performance present kinetic and kinematic differences due to reliance on distinct attributes. A previous systematic review and meta-analysis demonstrated moderate-to-strong correlations (r = 0.45–0.73; p < 0.001) between standing long jump distance and acceleration (0–30 m) and maximal sprint (30–100 m), respectively [53]. Moreover, moderate correlations were reported between the SJ (r = 0.56; p < 0.05) and CMJ (r = 0.55; p < 0.05) and sprint [54]. In fact, sprinting is associated with a capacity to generate higher ground force reactions, with a specific orientation, in minimal contact times [55], whereas jumps involving a horizontal force vector component (e.g., BJ) are characterized by higher ground contact times, which influences the magnitude of correlations. Indeed, it is expected that players exhibiting greater maximal force production (i.e., higher peak force) generally demonstrate superior outcomes across various performance metrics [56,57,58]. This is primarily attributable to their elevated relative strength (maximum force capacity relative to body mass), which enhances their ability to overcome inertia more efficiently. Additionally, the development of maximal strength, as well as jumping and sprinting capabilities, appears to exert a mutually reinforcing effect, contributing positively to overall athletic performance. This interrelationship is further supported by the significant correlations frequently observed among distinct physical qualities.

In the context of optimizing specific performance attributes in elite youth soccer players, it is suggested for coaches to employ training strategies that incorporate a broader range of exercises. Such an approach may elicit complementary adaptations beyond those directly targeted through the performance-specific training task itself. Furthermore, future research should seek to replicate the current methodological framework across diverse cohorts of elite youth soccer players. This is particularly relevant given that the criteria defining “elite” status may vary between competitive leagues, potentially influencing the physical performance profiles observed.

Furthermore, establishing normative performance benchmarks for youth soccer players using physical assessments may offer valuable reference values for developing evidence-based return-to-play criteria for common injuries in soccer, such as hamstring strains and anterior cruciate ligament injuries [59,60]. Future studies should monitor the progression of performance in the aforementioned tests alongside the incidence rate of these injuries in order to assess their validity.

This study has some limitations. Firstly, the data were collected at a single time point, and it is known that physical performance can fluctuate over the course of a season. However, it could be extremely challenging to evaluate players across all age categories within the same period using an extensive battery of tests without compromising the success of high-level competitions. Secondly, the fact that the club provides strength training to all players may have influenced the results, making them less generalizable as strength training can either enhance or diminish performance outcomes. Finally, the players were grouped by age categories (competitive level) rather than maturational age, which is naturally an important factor to consider. However, this decision was based on a more ecologically valid and realistic approach. Indeed, in the current context, an increasing number of young players are joining teams with older age groups, including at the senior level.

Further research is needed to examine the relationship between chronological age and competition level through physical assessments that include goalkeepers for a more complete analysis.

5. Conclusions

The results of this study showed that age categories can distinguish performance in physical tests with the highest differences being observed between the U23 and U16 categories. It is likely that older players display overall higher performance levels given the effects of maturity and strength training on maximum strength, rapid strength, and speed. However, these results should be considered context-specific. On the other hand, playing position was shown to not be influential to distinguish players physically. However, it should be noted that these results could be task-specific since soccer is a multidisciplinary sport that does not only depend on physical capacity. Moreover, moderate correlations were observed among the different tests, with the CMJ and SJ showing strong correlations, possibly due the vertical applied force vector in both tests.

The present study indicates that the physical characteristics of players from different age categories and from different positions are becoming more similar, possibly due to specific training characteristics and the influence of physical attributes in modern soccer. Finally, it suggested the implementation of different tests to assess physical qualities as demonstrated in the present study. However, if possible, these tests should be applied at multiple points throughout the season, allowing for the identification not only of the athletes’ physical development but also of potential gaps within each age category. This would enable improved monitoring and control of training load.