Differences in Soccer Matches' Movement Patterns between Two Young Age Groups Players: Under-17 and Under-19

One of the most important issues in soccer training is the analysis and optimization of the players’ physiological characteristics. This study examines movement characteristics of soccer players in an under-17 (U17, n=20) and under-19 (U19, n=23) age groups. Participants played for over 80 minutes in 13 league matches. Using GPS devices, we measured movement patterns, including total distance (TD), with speeds being classified into five categories: (1) walking, 0–3.6 km/h; (2) jogging, 3.6–10.8 km/h; (3) moderate running, 10.8–18.0 km/h; (4) fast running, 18.0–25.0 km/h; and (5) sprinting, >25.0 km/h. High-speed running (HSR) included speed categories 4 and 5. Maximum sprint speed (Max Speed) and the number of accelerations (ACC) and decelerations (DEC) were also recorded. Statistical analysis included independent T-test samples and ANOVA and showed higher measurements in the distance covered in four of the five categories (1, 2, 4, and 5), as well as increased TD, HSR and Max Speed, and higher ACC and DEC among the U19 players compared to the U17 players. These findings emphasize the need for age-specific fitness characteristics training strategies in young soccer players particularly during the transition of age group categories.

Introduction

Soccer is the worlds’ most popular team sport, with significant efforts dedicated to training professional players. Optimal players’ performance demands a combination of technical, physiological, mental, and tactical skills. which vary between the different field positions. Analyzing player’s movement patterns may optimize training programs and improve the overall players’ performance in competitive setting (Abbottet al., 2018; Bangsboet al., 1991; Mujikaet al., 2009).

Helgerudet al. (2001) demonstrated among young soccer players significant improvements in maximum oxygen consumption, anaerobic threshold, running efficiency as well as total match running distance, number of sprints, and the players’ ball involvement following aerobic training regimen. The researchers concluded that aerobic-type training enhances soccer match performance.

In a later study, Mendez-Villanuevaet al. (2012) found that younger players trained at higher running intensities than more senior players. Significant differences were seen in running demands across age groups and field positions. Average match running speeds did not differ across positions and age groups and aerobic fitness did not affect the total match covered distance. During the second half of the examined matches, all age groups and field positions were able to maintain distances of above-maximum aerobic speed, but distances that were covered below that speed were reduced. This suggests that young players are able to maintain higher intensities in the final match stages.

No difference in maximum oxygen consumption between professional and amateur players at the onset of puberty. In contrast, in late puberty, the fitness level of elite players was significantly higher. There was no difference in mean heart rate between the two halves of the game among elite players (early and late pubertal; Reillyet al., 2008; Torres-Rondaet al., 2016). Midfield and attack positions exhibited the highest absolute maximum oxygen consumption and performed at peak heart-rate levels during the game reflecting the increased physical demands of these positions (Bushet al., 2015; Strøyeret al., 2004).

Bushet al. (2015) found that wing and forward players cover greater distances at higher intensities and performed more sprints than central defenders and midfielders. This highlights the higher physical demands placed on wide and attacking players compared to players with defensive roles (Bushet al., 2015; Modricet al., 2019).

Modricet al. (2019), using GPS metrics to track running performance, reinforced this observation, showing that midfielders run the longest total distances, while wingers performed the greatest number of high-intensity sprints. The study also explored how different team formations impact running performance, finding that players in a 3-5-2 formation covered the most total distance (TD), while players in a 4-2-3-1 formation performed the most accelerations and decelerations. These findings underline the varying physical demands depending on a player’s position and team’s tactical setup (Bangsbo, 1994).

Further studies also showed that defenders cover less distance and perform fewer high-speed runs (HSR) compared to attackers and midfielders. However, reduction in sprint distances towards the final match stages was found among attackers indicating probably overall fatigue (Bangsboet al., 1991; Mohret al., 2003).

These differences suggest that each position in soccer demands unique physical capacities and tactical roles. While midfielders may cover long distances, wingers perform more sprints, and defenders focus on different types of physical efforts, such as positioning and defensive actions. Understanding these position-specific demands is essential for modifying training and improving player performance (Abbottet al., 2018).

Differences in performance across players’ position were described in several aspects including: (a) total distance: wingers (11,321 m), central midfielders (11,154 m), strikers (10,726 m), full-backs (10,452 m), and center-backs (10,206 m); (b) high-intensity running and sprints: wingers (1,015 m), full-backs (967 m), strikers (966 m), central midfielders (604 m), and center-backs (590 m); (c) running (19.8–25.2 km/h): wingers (533 m), full-backs (473 m), strikers (461 m), central midfielders (396 m), and defenders (343 m); and (d) sprints (> 25.2 km/h): forwards (505 m), full-backs (494 m), wingers (482 m), defenders (247 m), and central midfielders (208 m). In summary, central midfielders cover the greatest running distance, but the shortest sprint distances. Wingers exhibit the highest match physiological demands in terms of both total distance and speed intensity (Malloet al., 2015).

Therefore, the aim of the presents study was to examine differences in match movement patterns between U17 and U19 elite soccer players over the initial official league games (13 consecutive matches). We hypothesized that U19 players cover greater total match running distane and greater high-intensity sprints distance compared to the U17 players.

Method

Participants

The study included two groups of soccer league players: 20 U17 players [age M = 16.9 ± 0.4 years, height M = 176.1 ± 6.1 cm, weight M = 68 ± 8.4 kg, body fat% M = 9.2 ± 2.3] and 23 U19 players, [age M = 18.3 ± 0.5 years, height M = 176.0 ± 6.1 cm, weight M = 71. 6 ± 7.3 kg, body fat% M = 9.4 ± 2.1]. The two groups compete for one of the biggest soccer clubs in the country and usually ranked among the leading teams in their leagues. All players performed a thorough medical examination at a certified sports testing center before participating in the league. Study inclusion criteria were: (1) no physical injury over four months prior to data collection; and (2) players participated in at least 80% of the training sessions from four months prior to and during the intervention.

Ethical Considerations

The study was conducted in accordance with the Declaration of Helsinki, and was approved by the Ethics Committee at the authors’ affiliated academic institution (Reference number: 323, 12/04/22).

Procedure

All participants played for at least 80 minutes during 13 league matches in the first half of the season. To assess the players’ physical performance, specific movement patterns were measured: (1) Total distance (TD) covered by the player in the game, and (2) speeds at which these distances were covered, divided to several categories: Category 1, walking at a pace of 0–3.6 km/h; Category 2, walking and slow running, 3.6–10.8 km/h; Category 3, slow-to-moderate running, 10.8–18.0 km/h; Category 4: fast running, 18.0–25.0 km/h; and Category 5, sprinting at a pace of ≥25.0 km/h. In addition, Categories 4 and 5 were combined to create a high-speed running (HSR) measure. The players’ highest speed during a single sprint was also documented (Max Speed). Finally, the number of accelerations (ACC) and decelerations (DEC) >4 meters per second were also measured.

Tools

To measure and document the player’s physiological data on the field, each player wore a GPS performance tracker (Catapults Ltd.). Anthropometric data were gathered using a standard digital scale, a portable stadiometer, and a caliper for measuring body fat percentage.

Statistical Analysis

The SPSS software v25 was used for all statistical analyses. Data were gathered from the players over 13 league games, with the analysis including nine of these games, from the beginning, middle, and end of the first half of the season. For analysis, these games were grouped as follows: (1) games 1–3 (beginning); (2) games 6–8 (middle); and (3) games 11–13 (end). All data were normally distributed, except for the number of years playing professional soccer.

Comparisons of the mean anthropometric data between the two age groups were conducted through independent samples T-tests for parameters with normal distribution, and through median comparisons for non-normally distributed variables. Mean movement patterns across the 13 games were calculated based on the number of players who had played for more than 80 minutes in each game, and then again separately for each game category. The comparison of trends in game averages over the season, divided into three categories between groups, was conducted using a repeated measures ANOVA. This test enabled comparisons by time (over all 13 games), group (the two age groups across the three game periods), and group × time interactions.

Results

Total running distance (Fig. 1), of the U19 players was significantly greater than the U17–during games 11–13 (M = 09.5 ± 1.1 vs. 08.6 ± 0.9, respectively) and on average across all games (M = 09.2 ± 0.5 vs. 08.9 ± 0.5, respectively).

Fig. 1. Total match running distance (TD) of the U17 and U19 players. *p < 0.05; **p < 0.01.

U19 players covered significantly greater distances compared to the U17 in all speed Categories (Fig. 2) except for Category 3 (10.8–18 km/h): Category 1 (0–3.6 km/h), M = 1033.2 ± 76.1 m vs. 974.9 ± 62.7 m, respectively; Category 2 (3.6–10.8 km/h), M = 5132.9 ± 196.2 m vs. 4954.6 ± 248. 8 m, respectively); Category 4 (18.0–25.0 km/h), M = 744.6 ± 118.4 m vs. 661.2 ± 91.6 m, respectively; and Category 5 (>25 km/h), M = 88.6 ± 29.4 m vs. 64.2 ± 20.7 m, respectively.

Fig. 2. Overall running distance of the players in the different speed categories. *p < 0.05.

U19 players performed significantly greater number of decelerations above 4 m/s compared to the U17 players (Fig. 3): in games 6–8 (M = 33.1 ± 13.7 vs. M = 25.4 ± 10.4, respectively), games 11–13 (M = 29.3 ± 11.3 vs. M = 23.6 ± 10.7, respectively), and on average across all games (M = 30.8 ± 3.3 vs. M = 25.6 ± 4.5, respectively).

Fig. 3. Number of declarations (DEC) above 4 m/s of the players. *p < 0.05; **p < 0.01.

U19 players performed significantly higher number of accelerations above 4 m/s compared to the U17 players (Fig. 4): in games 6–8 (M = 21.6 ± 7.4 vs. M = 16.6 ± 6.6, respectively), games 11–13 (M = 19.4 ± 5.4 vs. M = 15.6 ± 6.7, respectively), and on average across all games (M = 19.8 ± 3.7 vs. M = 16.5 ± 2.7, respectively).

Fig. 4. Number of accelerations (ACC) above 4 m/s of the players. *p < 0.05; **p < 0.01.

The Max Speed during single sprint of the U19 players was significantly greater compared to the U17 players (Fig. 5): games 1–3 (M = 29.2 ± 1.7 vs. M = 27.7 ± 1.8, respectively) and on average across all games (M = 28.9 ± 0.6 vs. M = 27.9 ± 0.6, respectively).

Fig. 5. Maximal speed in a single sprint (Max Speed) of the players. *p < 0.01.

Finally, HSR was significantly greater in U19 compared to the U17 players (Fig. 6). In games 1–3 (M = 353.8 ± 53.6 vs. M = 290.9 ± 84.8, respectively) and on average across all games (M = 805.4 ± 137.8 vs. M = 710.0 ± 103.5, respectively).

Fig. 6. High-speed running (HSR) of the players. *p < 0.05.

Discussion

The purpose of this study was to compare 10 common soccer movement patterns between 17-year-old and 19-year-old elite players during the first 13 regular season league matches. Such information can identify gaps in physical fitness characteristics between the two age groups and may assist to determine the type of training required to prepare younger players for future competition against older counterparts. This is especially important since these two age groups represents the transition stage young players have to cross while moving from the youth to the adult team.

The results of the study indicated significant higher performance level in all the examined parameters, except for Zone 3 speed (speed range 10.8–18 km/h), in the U19 players. In addition, examination of differences across the three season periods—early season (matches 1–3), mid-season (matches 6–8), and late season (matches 11–13)—revealed no distinct characteristics of any specific period, suggesting that the differences observed represent the entire season rather than a specific phase.

Several factors may explain the performance differences. First, simply the chronological age and maturational status can influence the player’s body composition development. Differences in peak height velocity, peak muscle mass and peak bone mass may result in significant changes in fitness characteristics and lead to improved performance in the U19 age group. However, no significant differences in body height, weight and body fat percentage were found between the U17 and U19 players in the current study. The findings align with Pichardoet al. (2018), who proposed more specific long-term athletic development models focusing on training modalities and physical qualities, such as speed, agility, strength, endurance, resistance training, plyometric training, and weightlifting. These models integrate technical skills, developmental stages, maturation, and training age to optimize long-term athletic development. The current study results support the need for specific models, as the U19 players demonstrated superior physical performance compared to the U17 players (Pichardoet al., 2018).

Another variable that may influence performance is movement efficiency. Mechanically efficient players conserve energy better, enabling improved decision-making and sustaining advantage over the opponents, particularly in latter match stages (Mohret al., 2003). Efficient movement reduces energy expenditure, allowing players to execute more high-intensity actions than less efficient counterparts. Dolciet al. (2018) discussed the importance of mechanical efficiency in aerobic fitness during soccer matches. However, this parameter is generally tested only under constant-speed laboratory conditions, limiting its assessment in “real-life” soccer. High-intensity and other movements during a match may impose unique energy efficiency demands that may affect the players fatigue levels. Mechanical efficiency indeed improves with age and pubertal maturation, however, as stated earlier, we were unable to test these differences in the current study.

Training regimen differences may also explain our findings. While there is greater focus on tactical and technical skills among the younger players, the physical training demands in players in the older age group increase markedly, and as a results match movement patters are enhanced. Reports from coaching staff revealed that the U19 players trained at higher frequency, intensity, and volume than the U17 players. The U19 group conducted one additional weekly training session, resulting in greater weekly total running distance and higher intensity levels, particularly at speeds exceeding 18 km/h. Helgerudet al. (2001) demonstrated that increasing aerobic training volume improved match performance by increasing distance covered, work intensity, and the number of sprints. Contrasting findings were reported by Mendez-Villanuevaet al. (2012), who observed that younger players trained at higher relative running intensities than older players. However, despite these training differences, no significant differences in match heart rate or average running speeds were observed across age groups or playing positions. Such discrepancies may arise from differing training methodologies across European nations and leagues.

This study also highlighted that higher match intensity correlates with more accelerations and decelerations across all player’s positions. Parameters such as high-speed running and sprinting, accelerations and decelerations were significantly higher in the U19 players. These findings align with (Dalenet al., 2016), who found that accelerations and decelerations accounted for 7%–10% and 5%–7% of total match workload, respectively. In addition, our study suggests that the age-related differences in match movement patterns don’t just resolve with time and growth since movement parameters of the U17 players in towards the end of the season (games 11–13) were still lower compared to the movement patterns of U19 platers at the beginning of the season (games 1–3). Therefore, coaches should incorporate these insights into the workload assessments and training protocols among players of different ages to optimize training.

In summary, U19 soccer players demonstrated superior match movement patterns throughout the season, possibly due to biological pubertal maturation, advanced motor skills, and more intensive training. It should be noted, however, that U19 players covered also significantly more Zone 1 speed (walking speed). This may suggest that while U19 players perform at higher intensity and volume during matches, the more intense performance leads to greater fatigue and necessitate longer recovery (more walking between the high intensity bouts). The significant differences between the two age groups imply that while talented U17 soccer players may possess advanced technical skills, they often struggle during the transition to senior-level competition due to higher physical demands emphasizing the importance of bridging the physiological gaps by targeted training. Future studies should explore training modifications to minimize these gaps and examine position-specific comparisons across age groups. It should be noted that this study was conducted during the COVID-19 pandemic, which limited training routines and match schedules. Repeating the study in a regular season with approximately 30 matches and “normal” training conditions is recommended.

Conclusion

Match movement characteristics of elite U19 soccer players outperformed U17 players, regardless of the period of the season. U19 players covered greater match running distances at most speeds, performed more accelerations and decelerations, and reached higher maximum speeds. Training program should therefore be tailored to meet the specific age-related physical characteristics and physiological demands of the trainees.

Limitations and Future Research Directions

This study offers important insights into the physical capabilities of elite soccer players at different ages. Yet several research limitations should be addressed. First the study was conducted during the COVID-19 pandemic, when certain social restrictions were in place. Although the participants played in all 13 games, the pandemia may shortened the preparation period prior to the season and decreased the number of regular training sessions during the season. Similar research during a regular season will enable better generalization of the results. Moreover, the study only covered the first half of the season. As such, future studies should gather similar data over the full soccer season. Furthermore, this study compared only U17 to U19 male players at top national league. Future studies should investigate other age group transitions (for example U15 to U17, U19 to U21 etc.), age group transitions of national team level players and similar data collection among female soccer players. Additionally, specific information regarding training sessions was not collected in the present study, despite their possible impact on the outcomes. Finally, larger studies should also focus on age related differences among players at different game positions.