Differences in anthropometric characteristics and motor abilities of professional football players from leading and average teams in Serbian super league

Abstract

Aim of study

The aim of the study was to examine the differences between professional football players from leading and average teams in anthropometric characteristics and motor abilities. The sample of participants included 55 professional football players from the Serbian Super League, the top-tier national football competition.

Methods

The sample was divided into players representing the leading team (LT; n = 29) and the average team (AT; n = 26) in the Serbian championship. A total of 16 parameters were measured, including 5 anthropometric parameters and 11 variables of motor abilities, assessing sprint and acceleration performance, agility, explosive power, and endurance. Based on the independent t-test, it was determined that the leading team has a significantly lower fat percentage (0.016) compared to players from the average team.

Results

Regarding motor abilities, a difference has been observed on the side of the LT compared to AT in sprint performance, such as 20 m (0.001), and 30 m sprint (0.005), as well as acceleration index 10/20m (0.006). However, in contrast, the AT achieved better results in agility zig-zag (0.000) and zig-zag with a ball test (0.000), as well as index zig-zag (0.038). Additionally, the AT had better results in the test of explosive lower extremity power - CMJ (0.005). There were no differences between players in other anthropometric and motor performances.

Conclusions

These findings suggest that while the leading team demonstrates superior sprinting and acceleration capabilities, the average team excels in agility and explosive power of the lower extremities. Although certain differences in anthropometric characteristics and motor abilities were observed between the LT and AT groups of football players, further research is needed to examine these differences in more detail and provide a more comprehensive understanding.

Introduction

Anthropometric characteristics and motor abilities are often portrayed as critical determinants of soccer performance, as it describes players’ capacity to meet demands of the sport across various competitive levels [1]. In elite soccer, distinct anthropometric advantages, including body composition, height, and weight, are often demonstrated, which express players’ ability to execute dynamic movements such as sprints, jumps, and directional changes [2, 3]. These attributes often provide distinction between elite and sub-elite players, with those possessing superior anthropometric profiles and motor abilities consistently demonstrating higher levels of performance on the field [4, 5].

Body composition plays an important role in differentiation between playing levels, with lean muscle mass and lower body fat percentages indicating higher physical capabilities. Specifically, Arnason et al. [6] reported body fat percentage of 11.2 ± 4.3% for sub-elite players and 10.0 ± 4.2% for elite players. These attributes are particularly advantageous in executing high-intensity movements that are essential for competitive soccer [7]. Motor abilities, such as agility and quickness, are not solely determined by physical attributes but also by the efficiency of neuromuscular coordination and biomechanical execution [8], which is especially evident in elite players, whose anthropometric and motor profiles enable them to outperform non-elite players in critical game situations [9, 10].

Previous research on soccer players shows that differences in anthropometric characteristics can have impact on the game demands, particularly in tasks requiring explosive movements and can make a difference between levels [2, 11]. For example, elite players often demonstrate better sprinting and endurance abilities, essential for high-intensity actions such as pressing, creating opportunities, and defending. Besides that, agility allows players to keep-up with the dynamic of soccer matches and unpredictable opponent movements [12, 13].

Further, comparisons between elite and sub-elite soccer players consistently reveals differences in motor skills regardless of their age [14,15,16], because elite players are shown to exhibit superior speed, agility, and lower-body power, which are critical for high-intensity, short-duration efforts such as sprints and direction changes [2, 17]. Also, their enhanced endurance capacity is important for sustaining performance over the match duration [4]. Such distinctions are attributed to their advanced training regimens, genetic predispositions, and optimized physical development [1].

Studies have also highlighted the difference in endurance [18] and explosive power [19] between top-tier and mid-tier teams within the same league, which enable elite players to dominate critical moments of the game, such as executing rapid counterattacks or recovering defensively [3]. Despite previously described findings, research focused on evaluating the differences in anthropometric characteristics and motor abilities between leading and average teams within a single league remains limited [8]. This gap highlights the need for more targeted studies to understand what nuances influences performance in different competitive environments. Therefore, the main goal of this research was to assess the differences in anthropometric characteristics and motor abilities between leading and average teams in the same league. We hypothesize that our research will show distinguishable difference in anthropometric characteristics and motor abilities in favour of top teams compared to average teams, thus contributing to the existing body literature.

Methods

Participants

In this analytical cross-sectional study, the sample of participants included 55 professional football players from the Serbian Super League, the top-tier national football competition. The sample was divided into players representing the leading team (LT; n = 29, aged 23.38 ± 3.36 yrs) in the football championship and players from the average team (AT; n = 26, aged 22.96 ± 3.78 yrs). The criteria for inclusion in the study were players aged ≥ 18 to ≤ 35 years, with a training age of ≥ 6 years, without a recent injury (> 12 months) or any illness at that moment. The criteria for exclusion were goalkeepers due to their specific role [20–21], players younger than 18 years, or injured players, and players for whom all data were not collected. Based on similar previous studies [22,23,24,25], it has been observed that the minimum sample size based on previous research on football players, where participant groups typically range from 15 to 25. In this regard, for the purposes of this study, it was decided to ensure a slightly larger sample, specifically 30 participants per group. Four teams were selected, each consisting of 15 field players. Randomly, two teams were chosen from the top five leading teams (LT) and two teams from the five mid-table teams (AT) in the Serbian Super League during the 2021/22 season, at the time of testing in March 2022. From these teams, we gathered complete data for 55 players. All participants voluntarily participated and were informed about the purpose, benefits, and risks of the study, and they all provided written consent to participate in the study. Additionally, all data have been anonymized to ensure the confidentiality of the players and teams. The description of the sample is presented in Table 1. Therefore, all procedures conducted in the study involving human participants were in accordance with the Helsinki Declaration [26]. Also, the research was approved by the Ethics Committee of the Faculty of Medical Sciences, University of Kragujevac (decision number: 01-15731; date 29 December 2021).

Table 1 The main characteristics of the sample

Procedures

All participants were familiar with the test procedures. Each test was explained and demonstrated to the subjects beforehand. The test battery was composed based on frequently used tests in football [27]. Participants initially assessed for anthropometric characteristics using five parameters such as body height (BH), body mass (BM), calculated body mass index (BMI), as well as the percentage of body fat (BF) and muscle mass (MM). Prior to the physical testing, participants completed a standardized warm-up (Table 2) that included moderate jogging (8 min), static stretching (5 min), and brief periods of high-intensity running (2 min). Following the warm-up, all participants underwent a battery of motor tests, consisting of 11 variables. The order of motor tests was as follows: participants first performed a 30 m sprint (with split times recorded at 10 m and 20 m; speed). After that, lower limb explosive power was measured using the SJ and CMJ tests. Then, they performed an agility zig-zag test both without and with a ball, and finally, a shuttle run test was conducted. All tests were conducted on a football field in the morning, at approximately the same time (11 a.m.), and ended around 3:00 p.m. Two researchers (R.R. and B.K.) conducted all tests, and they motivated the players encouragement to enhance motivation. All participants were tested on Wednesdays and Thursdays to ensure at least 72 h had passed since their previous match while avoiding disruptions to their preparation for the upcoming Sunday matches. The same procedure was repeated the following week with the remaining participants. As a result, all measurements were conducted over a total of four days, although there was a seven-day gap between the first two and the last two testing days. All tests were conducted during the competitive season 2021/22, precisely in March 2022.

Table 2 The Warm-up protocol

A total of sixteen variables were divided into two groups, with 5 variables representing anthropometric characteristics and 11 variables representing motor abilities. The first group included anthropometric characteristics such as body height (BH), body mass (BM), body mass index (BMI), fat mass percentages (%FM), and muscle mass percentages (%MM). The second group included motor abilities parameters such as 10–30 m sprints (10–30 m), acceleration indexes (10/20 m, 10/30m), zig-zag agility with and without a ball, squat jump (SJ) and countermovement jump (CMJ), and the shuttle run test.

Anthropometric characteristics

Anthropometric assessments were conducted following the guidelines of the International Biological Program [28]. A Tefal 6010 scale (Rumilly, Haute-Savoie, France) was used to measure body mass, and the result was read from the scale’s display with an accuracy of 0.1 kg. Body height was measured using an anthropometer (GPM, Zurich, Switzerland), and the measurement result was read with an accuracy of 0.1 cm. Body mass index (BMI) was calculated based on the standard formula: BMI = BM (kg)/BH (m)² (BM—body mass, BH—body height). The fat and muscle tissue in the body was indirectly assessed using the laboratory method of bioelectrical impedance analysis (BIA). The Omron BF 300 apparatus from Japan was employed for bioelectrical impedance analysis. Data on the percentage of body fat and muscle mass are read from the device display with an accuracy of 0.1% [29]. These measures have been taken in most studies with football players [12, 30,31,32].

Motor abilities

Sprint performance

The tests involve the subject’s task to cover distances of 10, 20, and 30 m in the shortest possible time, i.e., at maximum speed. Time was recorded using electronic timing gates (Witty, Microgate, Bolzano, Italy) placed 1 m above the ground at the start line, 10 m, 20 m and at the finish line (30 m). The test begins with the subject breaking the beam of a photoelectric cell at the start and ends with breaking the beam of a target photoelectric cell. During this test, the time from breaking the beam at the starting point to breaking the beam at the target point is measured. Two sprints were performed with 2 min rest between trials, and 10-m, 20-m and 30-m split times recorded during each trial. A better attempt is recorded. Additionally, acceleration indexes were calculated for the distance of 20 m relative to 10 m and the distance of 30 m relative to 10 m. Sprint performance has been measured this way in previous studies, specifically for sprints of 10–30 m [33, 34], as well as the 10–20 m sprint [35, 36].

Agility tests

Agility was assessed using tests such as the zig-zag test without a ball and with a ball, also utilizing an electronic timing gate system (Witty, Microgate, Bolzano, Italy). During the execution of these tests, the subject is instructed to cover four segments of 5 m each in the shortest time possible, i.e., at maximum speed, both without a ball and with a ball. The segments are set at an angle of 100 degrees relative to each other. This test measures the time it takes for the subject to traverse the segments and then calculates the speed and acceleration. The Skill Index (SI) is calculated as the quotient of the results of the Zig-zag Test and the Zig-zag Test with a ball. This Zig-zag test with and without the ball has been used in numerous studies with football players [33, 35].

Jump performance

To assess explosive power of the lower extremities, Squat Jump (SJ) and Countermovement Jump (CMJ) were used. All jumps were performed on a photocell mat (Optojump, Microgate, Bolzano, Italy). The Squat Jump test is executed from a squatting position (knee flexion at a 90-degree angle) without a swing of the arms. The CMJ is performed from a squatting position (knee flexion at a 90-degree angle). The participant performs a maximum vertical jump preceded by a strong swing of the arms and body. The tests measure the maximum height of the vertical jump in cm. The validity and reliability of the Optojump system have been confirmed in previous research [37], as well as specifically these SJ and CMJ tests [28, 38]. These tests have also been described and used in the same manner in other studies on football players [30, 31, 36].

Shuttle run test

For the assessment of endurance, the shuttle run test was used. It is conducted by having players run between two cones placed at a distance of 20 m, with the running pace determined by an auditory signal from an audio recording of the protocol. The initial running pace for the test is set at 8 km/h, and the speed increases by 0.5 km/h every minute. When the participant fails to reach the starting marker within the specified time interval for the first time, they receive a warning. If they are delayed again (consecutive mistakes), the test concludes. The measure of the test is the distance covered in m by the participant during the test. Shuttle Run Test is indirectly used as a measure of VO2max and is highly correlated with VO2max [39, 40]. Also, the Shuttle Run test correlates with football players’ movement performance during matches [41, 42], and is therefore frequently used in football [31, 32, 43],

Statistics

For all data obtained through testing, basic central and distributional parameters were calculated, including the mean, and standard deviation. The t-test for independent samples was used to calculate the difference between the leading and average groups. The effect size (ES) within each group was assessed using Cohen’s d effect size. Criteria for determining the magnitude of the effect were as follows: <0.20 trivial, 0.20–0.50 small, 0.50–0.80 moderate, 0.80–1.3 large, and > 1.3 very large [44]. Statistical significance was set at p < 0.05. Data analysis was performed using IBM SPSS Statistics 27 software (Statistical Package for Social Sciences, v27.0, SPSS Inc., Chicago, IL, USA).

Results

When it comes to differences between the LT and AT in anthropometry, the only significant difference found is in the percentage of body fat, where players from the leading team have a significantly lower fat percentage (0.016) compared to players from the average team (Table 3).

Table 3 Differences between leading and average team football players in anthropometric characteristics and motor abilities

A significant difference has been identified on the side of LT compared to AT in sprint performance, such as 20 m (0.001), 30 m (0.005), and Index 10/20m (0.006). However, in contrast, LT achieved better results in agility tests Zig-zag (0.000), Zig-zag B (0.000), and Index zig-zag (0.038), as well as in the test of explosive lower extremity power - CMJ (0.005). There were no differences between players in other anthropometric and motor performances.

Discussion

This research aimed to explore the differences in soccer players’ physical and motor abilities between leading (LT) and average teams (AT) in the Serbian Super League. Key findings revealed that players from LT had lower body fat percentages, better sprint times over 20 m and 30 m, and better acceleration index. In contrast, the AT achieved better results in agility tests as well as in the CMJ test of explosive power. However, no significant differences were found in body mass, BMI, muscle mass, squat jumping, and endurance. These results underscore the importance of attributes like lean body composition and speed, but gives mixed results when it comes to agility in high-level football performance, highlighting specific areas that may define top-tier players.

This study examined several anthropometric characteristics, including body height, body mass, BMI, fat mass (FM), and muscle mass (MM). The findings revealed that players from LT were slightly taller and had a lower percentage of body fat compared to their counterparts from AT, though there were no significant differences in body mass or muscle mass. Specifically, the LT’s fat mass percentage was notably lower (8.49% ± 2.56) compared to the AT (10.11% ± 2.24), supporting previous research that underscores the importance of lower body fat for optimal football performance [45] especially when it comes to distinguishing between top and average players. While there were no significant differences in body height or mass, Sutton, Scott, Wallace & Reilly [46] suggest that body size can influence physical performance, especially in sprint and jumping abilities. Although leading team players tended to have leaner body compositions, differences in overall body size were less pronounced, a finding in line with Abrantes, Maçãs, & Sampaio [47] who highlighted the variability in body mass and composition among professional players depending on their position and playing style. Ultimately, while body composition may play a role in distinguishing players, factors like muscle strength and agility appear to be more critical in determining team performance.

Building on the role of anthropometric characteristics, sprint performance proved to be another key factor in distinguishing leading team players from their counterparts. Our analysis revealed that players from the leading teams were faster, with statistically significant differences in both 20 m and 30 m sprint times. Specifically, the leading team players recorded 20 m sprint times of 2.88s ± 0.11, compared to 2.99s ± 0.10 for the average team, and 30 m sprint times of 4.02s ± 0.13, versus 4.14s ± 0.17 for the average team. These findings are in agreement with Keiner, Kapsecker, Stefer, Kadlubowski, & Wirth [48] who observed that elite players generally outperform sub-elite in short-distance sprints. The faster sprint times of the leading team players are likely indicative of superior neuromuscular adaptations, such as enhanced explosiveness and quicker reaction times. This aligns with the conclusions of Newans, Bellinger, Dodd, & Minahan [49] which suggest that short-distance sprinting ability is a key physical trait differentiating elite players from sub-elite ones. Superior sprint performance likely reflects more advanced neuromuscular adaptations, including greater rate of force development, enhanced stride mechanics, and more efficient intermuscular coordination. Taken together, these results reinforce the idea that while anthropometric characteristics provide a useful baseline, dynamic physical abilities—particularly acceleration and sprinting speed—offer more predictive value when distinguishing performance levels in professional football.

Given the significant differences in sprint performance, it is essential to delve deeper into acceleration and speed-related metrics, such as the 10/20m and 10/30m indexes, which provide more insight into players’ explosive capabilities. These indexes, which measure a player’s relative speed and acceleration, were also part of this study. Our findings showed that players from the leading team had superior 10/20m and 10/30m indexes, with values of 0.56 ± 0.02 and 0.40 ± 0.02, respectively, compared to 0.54 ± 0.02 and 0.40 ± 0.03 for the average team. Statistically significant differences were observed in the 10/20m index, which aligns with the findings of Newans, Bellinger, Dodd & Minahan [50] who highlighted the importance of acceleration and the ability to swiftly transition between high-speed movements. Furthermore, the notable difference in the 10/20m index supports the work of Bradley et al. [2] who demonstrated that elite players accelerate faster over short distances, enhancing their overall match performance. These results suggest that superior acceleration, particularly over short distances, is a defining factor that sets leading team players apart from their peers.

Acceleration represents another critical ability that enables football players to adapt to the fast-paced and dynamic demands of the game by quickly changing direction and responding to the flow of play. Unlike previous results that favored the LT team, in agility, players from the AT team outperformed their counterparts in the zig-zag and zig-zag with ball tests, recording times of 7.29s ± 0.20 and 9.10s ± 0.50, compared to 6.15s ± 0.22 and 7.45s ± 0.44 for the average team. These findings diverge from the trends observed in previous literature. For instance, Kaplan, Erkmen, and Taşkın [13] reported that elite players typically outperform their sub-elite counterparts in agility-based tasks, primarily due to superior neuromuscular control, quicker ground contact times, and sharper anticipatory skills. Similarly, Yauch [51] identified agility—particularly in response to game-relevant cues—as a strong predictor of performance among top-level players. However, the lack of alignment with these findings in our study may be explained by contextual variables. Unlike studies comparing players across different leagues or levels of professionalism, our sample was composed entirely of professional players competing within the same national league. This competitive proximity likely results in a narrower performance gap, particularly in abilities that are heavily trained across all levels of professional football. Another potential explanation could be the difference in training priorities or tactical roles across the two teams. For instance, AT players may be exposed to more position-specific drills emphasizing reactive agility, especially if their playing style relies more on counterattacks or one-on-one situations where quick directional changes are frequent. Meanwhile, LT players might focus more on structured pressing and ball retention, placing a greater emphasis on endurance, tactical discipline, and positional awareness than isolated agility drills. The inclusion of the ball in the zig-zag test also introduces technical demands that could favor players with more refined individual ball-handling skills, regardless of team status. Ultimately, while agility remains a critical differentiator at higher levels of play, our findings highlight that within a single competitive tier, variations in agility performance may reflect tactical roles, training methodologies, and positional demands rather than overall team quality.

In overall athletic performance, jumping ability further enhances player performance, especially in aerial duels and vertical movements during matches. While no significant differences were observed in squat jump results (42.14 ± 4.48 cm vs. 42.73 ± 6.28 cm), the AT significantly outperformed the LT in CMJ performance, with results of 55.60 ± 7.94 cm compared to 50.16 ± 5.72 cm, respectively. These findings stand in contrast to previous research, such as that by Cerrah et al. [52], who reported that CMJ performance typically favors elite-level players, attributing this advantage to superior neuromuscular coordination and lower-body power. Similarly, Markovic and Mikulic [53] emphasized that CMJ is not only indicative of leg strength but also reflects the efficiency of the stretch-shortening cycle, a quality often refined through high-level plyometric training and frequent exposure to explosive game scenarios. The discrepancy in our results may point toward contextual or structural variables rather than intrinsic physical capacity. One plausible explanation for the CMJ advantage observed in the average team could lie in training focus or positional demands—players from the AT may be exposed to specific drills targeting reactive strength or plyometric capacity more regularly. Additionally, while both teams compete in the same league and therefore share similar seasonal demands, the scheduling of high-intensity matches, recovery strategies, or periodization of strength training could differ. It is also possible that LT players, due to their higher match workload and strategic focus on possession and pressing, prioritize other performance areas such as agility and tactical awareness, potentially compromising explosive jump development. The absence of significant differences in SJ outcomes may reflect comparable general lower-body strength among both groups, as this movement minimizes the contribution of the stretch-shortening cycle and instead isolates concentric strength. Overall, while CMJ performance is often linked to elite status in football, our findings highlight that explosive qualities do not always align neatly with team success and may instead be shaped by positional roles, training strategies, or club-specific performance models.

Alongside speed-strength abilities, endurance metrics provide an additional perspective on overall fitness levels. In our study, endurance, as measured by the shuttle run, did not reveal any significant differences between the two groups. Players from the leading team covered an average distance of 2469.66 ± 256.22 m, while the average team completed 2498.46 ± 216.29 m. These findings suggest that endurance levels may not serve as a primary differentiator of performance between top-tier and mid-tier teams within the Serbian Super League. This is consistent with prior research by Ostojic [54], who highlighted that while aerobic endurance is foundational for sustaining match performance over 90 min, it may plateau across competitive levels, especially among professional players who all undergo similar aerobic conditioning. Likewise, studies by Rampinini et al. [55] and Castagna et al. [56] reported minimal differences in VO₂max or intermittent endurance capacity between elite and sub-elite footballers, pointing instead to greater variability in neuromuscular and anaerobic markers such as repeated sprint ability, acceleration, and change of direction speed. Moreover, the relative homogeneity in endurance performance could reflect the universal demands of modern football, which requires all players—regardless of team ranking—to maintain high-intensity effort throughout the match. As such, coaching staff across different teams may emphasize endurance training to a comparable extent, leveling this particular attribute. However, what may set leading teams apart are subtle nuances in tactical efficiency, sprinting patterns, or recovery between high-intensity bouts, rather than absolute endurance capacity.

Although it was expected that the LT group would show better results in physical fitness parameters compared to the AT group, this was only partially confirmed, as the LT group achieved higher values in speed performance and acceleration, along with a lower body fat percentage. On the other hand, the AT group performed better in agility and the CMJ test, while there were no differences between the groups in other parameters. It is clear that many factors could influence the outcomes, such as the type of training the players underwent, and the specific nature of the physical conditioning training applied is not known. It is important to note that the team’s playing philosophy and style of play affect the role of physical preparation within the overall technical-tactical training. All these factors could not be controlled, yet they influence the results.

Despite that, this study has its strengths, as it is one of the few studies examining differences in anthropometric characteristics and motor abilities between higher and lower ranked elite soccer players. It is also the first study that have investigated these parameters among top-level football players in Serbia. In this context, the results contribute to filling the gap in previous research concerning professional football players from this region.

Limitations

Despite its valuable findings, this study has several limitations. First, the sample size was relatively small which may limit the generalizability of the results to broader football populations or different competitive levels. Second, the study primarily focused on physical performance attributes, leaving psychological, tactical, and technical factors unexplored, even though they are critical for football performance. Additionally, the cross-sectional design captures a snapshot in time, preventing insights into long-term player development or training adaptations. Finally, while anthropometric and performance metrics were measured, external factors such as match demands, playing styles, and recovery practices were not accounted for, which could influence the observed results. It should be added that it is not known what player profile the coach needed at a given time, and this could also be one of the factors. Also, for future research, strength tests, and more specific ball-related tests should be included.

Conclusion

Considering the obtained results, it can be concluded that the differences between LT and AT cannot be generalized, especially taking into account the fact that in certain abilities players from AT were better than players from LT. The results obtained in this way further indicate that body composition and motor skills are not a decisive factor in team sports such as football, especially when it comes to the nuances that decide the winner of the championship.

Practical application

Based on everything stated, a practical recommendation to coaches and practicioners would be to never reject or discriminate against players based on body composition and motor skills tests until all other possible factors are taken into consideration. Although the tests may indicate some strengths or weaknesses, they cannot tell for sure how the team will perform during the season. Also, taking into account the psychological profile and a larger number of tests could provide a wider picture and better understanding on ability to utilize maximum potential.