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European Journal of Sport Science logoLink to European Journal of Sport Science
. 2025 Aug 17;25(9):e70041. doi: 10.1002/ejsc.70041

Comparison of Interlimb Coordination During Soccer Instep Kicking Between Elite and Amateur Players

Zhanyi Zhou 1, Zixiang Gao 2, Fengping Li 1, Dongxu Wang 1, Yucheng Wang 1, Gusztáv Fekete 3, Yaodong Gu 1,✉
PMCID: PMC12358685  PMID: 40820423

ABSTRACT

This study investigates how interlimb joint coordination influences foot speed during soccer instep kicking, using continuous relative phase (CRP) as a quantitative method. The sample includes 15 elite and 15 amateur players to examine potential differences in coordination patterns and their impact on performance. Specifically, we focused on the coordination between hip, knee, and ankle joints in the forefoot‐back kicking motion. Results indicated that elite players exhibited significantly higher hip‐knee CRP in the coronal plane during 62%–81% of movement duration (p = 0.015) and higher knee‐ankle CRP in the vertical plane during 78%–100% (p = 0.013). Moreover, elite players had significantly greater hip‐knee mean absolute relative phase (MARP) and deviation phase (DP) in the coronal plane (p < 0.001), as well as increased knee‐ankle DP (p = 0.04). In the horizontal plane, hip‐knee MARP was also greater in the elite players compared to amateurs (p < 0.001). Further analysis revealed a significant negative correlation between hip‐knee CRP and foot velocity in the sagittal plane (R = −0.66, p < 0.001), whereas a significant positive correlation was observed between knee‐ankle CRP and foot velocity in the horizontal plane (R = 0.56, p = 0.002). These findings suggest that elite players have superior joint coordination, which contributes to a faster foot velocity at the moment of ball impact. Understanding these coordination patterns provides valuable insights into optimizing kicking techniques. The findings of this study suggest that joint coordination may play an important role in enhancing kicking foot speed, which could inform future training approaches aimed at improving soccer performance.

Keywords: continuous relative phase (CRP), hip‐knee coordination, joint kinematics, soccer instep kicking

Summary

  • Elite players displayed significantly greater hip‐knee coordination in the coronal plane and knee‐ankle coordination in the horizontal plane during the forward swing phase compared with amateurs.

  • Higher coronal‐plane coordination variability in elite players suggests greater joint mobility and adaptability to varying task demands.

  • Foot velocity at ball impact correlated negatively with sagittal‐plane hip‐knee CRP and positively with horizontal‐plane knee‐ankle CRP.

  • Superior joint coordination in elite players may enhance power transfer efficiency, contributing to faster and more accurate instep kicks.

1. Introduction

Soccer is a highly dynamic sport in which the ability to execute powerful and accurate shots plays a critical role in a team's offensive strategy (Fernandez‐Navarro et al. 2016). Among various kicking techniques, the instep kick is one of the most commonly used in competitive soccer, especially for generating powerful shots on goal (Kellis and Katis 2007). The instep kick is a complex motor skill that involves coordinated movements of multiple segments. Movement coordination refers to the ability to maintain consistent spatiotemporal relationships—such as relative timing and phase synchronization—between joints or body segments (e.g., limbs, trunk) during movement execution (Chiu and Chou 2012). This coordination ensures that segments work together harmoniously during movement and is a key factor in performance and efficiency (McGill et al. 2003). In multijoint sports (soccer, basketball, gymnastics), coordinated segmental movement contributes to both fluidity—ensuring smooth transitions between motion phases—and stability—maintaining control during rapid or forceful actions, both of which are essential for effective force transmission and athletic performance (Niewiadomski et al. 2019). Studies of interjoint coordination are based on motor coordination theory and dynamic systems theory. Motor coordination theory focuses on how the central nervous system (CNS) realizes the coordinated movement from high‐level motor coordination synergy to low‐level motor organ through a hierarchical control mode (Safavynia et al. 2011). Dynamic systems theory explores how various parts of the body interact to form complex patterns of movement (Ushioda 2015). In these theoretical frameworks, coordination is regarded as a stable and flexible movement pattern that achieves effective motion control by adjusting the timing and intensity relationships between the various segments.

Because of extensive research in the field of motion control, scholars have developed various methods to quantify motion coordination. In studies characterizing the dynamic system of motion coordination, vector coding analysis and continuous relative phase methods are frequently used (Miller et al. 2010). Both methods describe the pattern of movement coordination in terms of the relative motion between multiple joints. This relative motion can be represented by a point‐to‐point diagram (Sparrow 1992). They can quantify coordination patterns at each moment during the movement, reflecting the relative motion behavior between two segments throughout the process. For example, in discus throwing, different body positions, such as the shoulders, arms, and torso, work together in a coordinated manner. The arms extend, the shoulders rotate, and the trunk shifts weight to generate power and precision. In vector analysis, each moment of movement is represented by a vector on a joint angle‐angle diagram, with the direction of the vector reflecting the relative motion between two joints. By calculating the changes in these vectors over the entire movement cycle, valuable insights into the coordination between joints can be obtained. Conversely, continuous relative phase (CRP) is derived from angle‐angular velocity plots across multiple segments (after normalization), with the added consideration of time‐varying angular velocity. This makes CRP more sensitive than vector coding in quantifying variability in movement coordination, providing a more refined assessment of coordination changes across lower limb segments (Hsu et al. 2014). Kelso first validated the effectiveness of CRP through a finger oscillation experiment. He instructed participants to simultaneously move both hands or fingers at varying frequencies and observed how the coordination between them changed at various oscillation frequencies (Kelso 1994). However, this method has been previously applied mainly in periodic motions, such as walking, running, and swimming (Hamill et al. 2000). Aperiodic motion usually involves nonlinear dynamics in which the relationship between parts is not linear or predictable (Krack 2015). CRP analysis can capture and analyze these nonlinear dynamics to gain a deeper understanding of the complex interactions between different segments. Julian Schardens et al. used it to describe the coordination patterns of the shank‐thigh and thigh‐sacrum segments during the jump in ski jumping (Chardonnens et al. 2013). Previous studies have primarily focused on the kinematic analysis of the support and kicking legs, as well as the muscle activation patterns during the instep kick. For instance, Joanna C. Scurr's study demonstrated that during an accurate shooting task, quadriceps activation in the kicking leg was significantly higher when aiming at the top‐right corner of the goal, suggesting that shooting direction may influence neuromuscular output patterns (Scurr et al. 2011). Similarly, Rodrigo Rabello et al. found that under different ball approach conditions, several muscles in both the support and swinging limbs exhibited significant temporal variations in activation (Rabello et al. 2022). These findings suggest that athletes dynamically adapt their neuromuscular control strategies by modulating intermuscle coordination patterns in response to changes in ball direction, thereby meeting the demands of different movement tasks. However, interlimb coordination is fundamental to efficient movement execution, capturing complex patterns of interaction and coordination between different parts of the body (Dubois et al. 2023). This coordination is crucial for optimizing shot power, accuracy, and overall performance and deserves further in‐depth study.

Instep kicking is a common and crucial offensive technique in soccer. Studies have shown that increasing foot velocity is one of the main goals of soccer players (Barfield 1998). This is because increased shot speed can significantly enhance the threat of an offense during a game, especially during penalty kicks. Higher shooting speed not only reduces the goalkeeper's reaction time but also increases the success rate of shots, giving teams a competitive edge in critical situations (Khorasani et al. 2009). Previous scholars have studied shot velocity, usually using soccer ball velocity as a parameter. However, ball velocity is affected by various factors (e.g., contact time between the foot and the ball, contact point, contact area, etc.) (Shinkai et al. 2008). Moreover, foot velocity is closely related to the coordination between joints within the kicking leg; effective timing and phase relationships among these joints enable the sequential transfer of momentum from proximal to distal segments (Hatsopoulos et al. 2010), which is critical for maximizing foot speed at ball impact. Therefore, this study focused on analyzing lower limb intersegmental coordination patterns to understand the neuromechanical contributions to foot velocity during the instep kick. This study aimed to quantify the movement coordination patterns of soccer players of different levels in instep kicking using CRP. We sought to explore the differences in joint coordination and mobility between elite and amateur players in instep kicking and to explore the relationship between joint coordination patterns and foot velocity. This provides a new perspective for coaches and athletes to understand the performance of this activity.

2. Materials and Methods

2.1. Participants

The required sample size was estimated using G*Power software (v3.1.9.2, University of Düsseldorf, Germany), with a significance level of α = 0.05 and statistical power (1 – β) = 0.80. Based on the inclusion criteria proposed by Matsunaga et al. (Matsunaga and Kaneoka 2018), a total of 30 male soccer players were recruited, including 15 amateur and 15 professional players. Their main characteristics are presented in Table 1. All participants were in good physical condition and had no musculoskeletal injuries or related illnesses in the past 6 months. To minimize the influence of prior physical exertion, participants were instructed to refrain from intensive training or matches for at least 24 h before the testing session. None of the players reported muscle soreness or fatigue on the day of testing. All subjects signed a written informed consent form before data collection. The study protocol was approved by the Scientific Research Ethics Committee of Ningbo University (Approval Number: RAGH20240501).

TABLE 1.

Demographic characteristics of the study group.

Group Number Age (Year) Weight (kg) Height (cm) Experience (Year) Training sessions/week Matches/month
Elite 15 21.4 ± 4.9 70.4 ± 6.2 175.4 ± 2.8 7.6 ± 1.9 5 3
Amateur 15 20.8 ± 3.7 71.8 ± 7.6 177.7 ± 5.9 3.1 ± 1.2 2 1
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2.2. Measurement System

The experiment was conducted in the biomechanics laboratory of Ningbo University. Participants were required to complete a full instep kick maneuver at the experimental site, and each complete kicking motion was fully captured. The experiment was conducted on indoor artificial turf (1.27 cm), and the stationary ball was 6 m away from a small indoor goal (2 m wide and 1.5 m high; see Figure 1). Prior to the experiment, participants underwent a 10‐min jogging warm‐up and 5 min of soccer‐specific dynamic stretching. After warming up, participants performed two maximal‐effort instep kicks to acclimate to the kicking force before testing. All participants used the same size 5 soccer ball, and ball pressure was controlled at 10 psi using a pressure testing device. Participants used their dominant leg to kick the ball at their shooting angle (30°–45°) and distance (up to 2 m) (Cerrah et al. 2024). Participants were asked to kick the ball with maximum effort and hit the center of the target as much as possible (Apriantono et al. 2006). All participants performed repeated instep kicks with a 30‐s rest interval between trials until they completed five valid shots. A shot was considered valid if it met two criteria: (1) The ball speed was within ± 5% of the individual target speed, and (2) the ball trajectory was directed toward the center of the goal. The target speed was defined as the mean ball velocity obtained from each participant's three maximum‐effort instep kicks during a familiarization phase conducted prior to testing. Ball speed was measured using a high‐speed radar gun (Net Playz, China). The best performance (maximum foot speed) was selected as the experimental data. Motion trajectory data were collected by the Vicon 3D motion capture system at a frequency of 200 Hz (Vicon Metrics Ltd., Oxford, United Kingdom).

FIGURE 1.

FIGURE 1

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A schematic of experimental design. (A) Experimental procedure, (B) data processing.

The kinematic data were processed in the Visual3D (v6.01.36, C‐Motion, Rockville) biomechanical analysis system using a fourth‐order zero‐lag Butterworth filter for low‐pass filtering with a cutoff frequency of 10 Hz (Sinclair et al. 2013). Based on the kinematic data, the instep kick was divided into three main moments: maximum hip extension moment, maximum knee flexion moment, and ball impact moment. Two main phases are defined (Figure 2): (1) upward swing of the shank, that is, from the instant of maximum extension of the hip joint of the kicking leg to the instant of minimum knee flexion; and (2) forward swing, that is, from the instant of minimum knee flexion to the instant when the instep impacts the ball head‐on (Watanabe et al. 2020).

FIGURE 2.

FIGURE 2

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Definition of phases of kicking legs.

2.3. Continuous Relative Phase

To calculate phase angles and minimize the effects of different motion amplitudes and frequencies, the phase diagram needs to be normalized, as shown below (Equations (1) and (2)).

θnorm=2θθmax−θmin−θmax+θminθmax−θmin (1)
ωnorm=2ωωmax−ωmin−ωmax+ωminωmax−ωmin (2)

The phase angle is calculated by substituting the normalized angle and angular velocity into different equations (Figure 3) for the 4 quadrants based on the positive and negative relationship between the angle and angular velocity. The phase angle represents the velocity as a function of displacement, with the horizontal axis representing angular displacement and the vertical axis representing angular velocity.

ψCRP=∅Distal−∅proximal (3)

FIGURE 3.

FIGURE 3

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Phase angle quadrant.

Coordination modes are distinguished as in‐phase (value of 0°) and antiphase (value of ± 180°) behavior. If ψ > 0, the proximal joint leads the distal joint motion; if ψ < 0, the distal joint leads the proximal joint motion (Lamb and Stöckl 2014). As the result obtained gets closer to 2π (0°), it is considered to be in‐phase; as the result obtained gets closer to π ( ± 180°), it is considered to be antiphase; and ± 30° is considered to be an acceptable range (Lu et al. 2008). Therefore, it belongs to the in‐phase mode at 0 < CRP < 30° or −30° < CRP < 0 and to the antiphase mode at −180° < CRP < −150° or 150° < CRP < 180°.

2.4. Interlimb Coupling Relationship

In this study, internal coupling refers to the temporal coordination between joints within the kicking leg. It reflects how these joints interact and synchronize during the execution of the instep kick. To quantify internal coupling, two commonly used phase‐based measures were applied: the mean of the absolute values (mean absolute relative phase, MARP) and the mean of the standard deviations (deviation phase, DP) of the mean of the relative phase angles at all moments in the measurement period were calculated (Galgon and Shewokis 2016).

MARP=∑iP|CRP|p (4)
DP=∑iPSDP (5)

where P is the number of data points in the cycle (101). Lower MARP indicates a more in‐phase movement coordination mode between the two joints. Lower DP values suggest a more stable relationship between the two joints, and higher DP values indicate greater variability in movement coordination.

2.5. Statistical Analysis

Statistical analyses of CRP curves were performed using an independent‐samples t‐test in the open‐source software spm1d (version 0.4.8, developed by Pataky, available at spm1d.org) in Python 3.9 and Anaconda3 environments. Independent‐samples t‐tests for MARP, DP, joint angles, and foot velocities in the ball impact phase were completed using SPSS 20.0 (IBM, USA). Spearman correlation analysis between foot velocity and CRP at the moment of impact was performed using R. Correlation coefficients were considered statistically significant if the p‐value was less than the α level of 0.05. Additionally, correlations with an absolute r‐value greater than 0.5 were interpreted as having a large effect size, following Cohen's criteria (Cohen 2013).

3. Result

Figure 4 demonstrates the joint sagittal plane kinematic parameters at two critical moments in Phase 1. The left panel shows that the maximum hip extension angle was significantly greater in the elite group than in the amateur group (p < 0.001). However, there was no significant difference between the elite and amateur groups in terms of maximum knee flexion angle (p = 0.583). Notably, the angle variability (standard deviation) at both the hip and knee joints was significantly greater in the elite group.

FIGURE 4.

FIGURE 4

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Comparison of kinematic parameters at two critical moments in Phase 1: maximum hip extension (left) and maximum knee flexion (right).

Figure 5 presents the hip‐knee CRP (left) and knee‐ankle CRP (right) curves in three anatomical planes. The blue curve represents elite players, whereas the yellow curve represents amateur players. Standard error is used to indicate the error bands.

FIGURE 5.

FIGURE 5

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(A) Sagittal CRP, (B) coronal CRP, (C) horizontal CRP.

In the sagittal plane, the overall trend of the two curves for elite and amateur players was more consistent, and the variability of hip‐knee CRP was very small in both groups.

In the coronal plane, hip‐knee CRP was significantly higher in elite players than in amateur players during the 62%–81% time domain. Elite players’ hips lead their knees to a greater extent during this time frame. During this period, elite players’ hips led their knees to a greater extent, exhibiting a nearly in‐phase movement of both joints. There was no significant difference in knee‐ankle CRP between the two groups.

In the transverse plane, there was no significant difference in hip‐knee CRP; however, elite players’ knee‐ankle CRP was significantly greater than that of amateur players during 78%–100% of the movement duration. At this stage, amateur players exhibited an ankle‐lead knee coordination mode, whereas elite players’ coordination mode was close to in‐phase coordination.

The MARP and DP results for the hip‐knee and knee‐ankle joints in the three degrees of freedom are shown in Table 2. In the coronal plane, the hip‐knee MARP and DP of the elite group were significantly greater than those of the amateur group (p < 0.001); the elite knee‐ankle DP was significantly greater than that of the amateur group (p = 0.04). In the horizontal plane, the hip‐knee MARP was significantly different between the two groups (p < 0.001).

TABLE 2.

Internal coupling relationship of lower limb.

Parameter Elite Amateur p
Hip‐knee MARP (sagittal)/(°) 52.55 ± 1.58 56.28 ± 1.49 0.101
Hip‐knee DP (sagittal)/(°) 30.27 ± 1.18 30.63 ± 1.08 0.819
Hip‐knee MARP (coronal)/(°) 79.53 ± 2.71 49.17 ± 3.71 0.000 *
Hip‐knee DP (coronal)/(°) 41.23 ± 1.56 22.69 ± 2.08 0.000 *
Hip‐knee MARP (horizontal)/(°) 76.96 ± 3.52 56.49 ± 11.66 0.000 *
Hip‐knee DP (horizontal)/(°) 36.55 ± 1.58 28.35 ± 5.93 0.195
Knee‐ankle MARP (sagittal)/(°) 49.72 ± 9.53 56.09 ± 5.86 0.575
Knee‐ankle DP (sagittal)/(°) 28.2 ± 4.83 30.92 ± 2.60 0.624
Knee‐ankle MARP (coronal)/(°) 77.21 ± 5.87 61.31 ± 10.19 0.193
Knee‐ankle DP (coronal)/(°) 39.97 ± 2.67 28.85 ± 4.26 0.040 *
Knee‐ankle MARP (horizontal)/(°) 61.64 ± 8.60 71.07 ± 7.01 0.405
Knee‐ankle DP (horizontal)/(°) 31.69 ± 3.79 28.84 ± 3.81 0.603
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*

p < 0.05.

The correlation of hip‐knee CRP and knee‐ankle CRP with foot velocities for the three anatomical planes is illustrated in Figure 6. A significant negative correlation (R = −0.66, p < 0.001) was found between hip‐knee CRP in the sagittal plane and foot velocity. A significant positive correlation (R = 0.56, p = 0.002) was found between knee‐ankle CRP in the horizontal plane and foot velocity.

FIGURE 6.

FIGURE 6

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Correlation between CRP and foot velocity at impact phase.

Table 3 shows the angles of each joint of the kicking leg in three planes at the impact phase, as well as the resultant velocity of the kicking leg for both groups. The results showed that the hip flexion angle of the elite group was significantly smaller than that of the amateur group (p < 0.001), and there was also a significant difference between the two groups in the transverse plane of the knee joint (p = 0.045). In addition, the kicking leg resultant velocity of the elite group was significantly higher than that of the amateur group (p < 0.001).

TABLE 3.

The angle of each joint at the impact phase and the resultant velocity of the foot velocity.

Parameter Elite Amateur p
Hip (flexion/extension)/(°) 14.75 ± 1.36 24.17 ± 0.67 0.000 *
Hip (adduction/abduction)/(°) 19.72 ± 1.19 17.06 ± 0.42 0.053
Hip (internal/external)/(°) −8.67 ± 1.91 −7.11 ± 1.38 0.518
Knee (flexion/extension)/(°) −48.16 ± 2.12 −53.32 ± 2.46 0.127
Knee (adduction/abduction)/(°) −2.72 ± 0.82 −2.59 ± 0.73 0.249
Knee (internal/external)/(°) 23.99 ± 2.38 15.79 ± 1.66 0.025 *
Ankle (flexion/extension)/(°) −57.89 ± 2.81 −52.08 ± 5.59 0.367
Ankle (adduction/abduction)/(°) −4.29 ± 1.65 −3.74 ± 1.16 0.786
Ankle (internal/external)/(°) −18.99 ± 1.16 −25.05 ± 3.89 0.159
Foot velocity (resultant velocity)/(m/s) 14.71 ± 0.45 12.45 ± 0.69 0.000 *
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*

p < 0.05.

4. Discussion

In this study, we comparatively analyzed the coordination patterns of elite and amateur soccer players in three anatomical planes of the lower limb using the continuous relative phase (CRP) method. The aim of this study was to gain insight into the effect of technical level on joint coordination modes and to investigate their role in athletic performance. We also sought to further explore the optimal coordination modes and to reveal the intrinsic mechanism between lower limb joint coordination and efficient athletic performance, providing a scientific basis for improving sports performance.

Hip extension is essential in the kicking motion (Shan and Westerhoff 2005). From the results in Figure 4, it can be seen that elite players usually have a greater hip extension angle to maximize the power output of the shooting action. This helps them accumulate more potential energy during the swing phase, which can be converted into mechanical energy at the ball impact moment. This is consistent with Kawamoto's findings that experienced athletes had significantly greater peak mean hip flexion moments during the upward swing phase of the shank, further supporting the critical role of the hip in generating shot power (Kawamoto et al. 2007). The lack of significant difference in the maximum knee flexion angle may be due to the high variability (standard deviation) in elite players. The main task of the knee joint is to control the amplitude and velocity of the leg swing during the shooting process, especially during the swing of the leg prior to impacting the ball. This may be attributed to elite players' greater ability to adapt their movement coordination to different environmental and task constraints, allowing them to perform the kicking action with more consistent control and higher foot velocity. The CRP curves in Figure 5 indicate that on the sagittal plane, the trends of hip‐knee CRP and knee‐ankle CRP are relatively consistent between the two groups. Particularly for the hip‐knee CRP, during the first 53% of the movement time, which corresponds to the shank upward swing phase, the knee joint is more active, driving the hip joint. As the leg swing progresses into the forward swing phase (the remaining 46% of the movement time), the hip joint begins to lead the knee joint, resulting in a shift in their phase relationship. Similar results were found by Weineck et al., who observed that during the transition from the shank upward swing to the forward swing phase, the knee continues to flex, the thigh advances forward, and the angular velocity of the hip joint increases rapidly (Weineck and Fussballtraining 1992). Furthermore, the results (Figure 5) suggest that during the forward swing phase, the hip joint leads the knee joint in executing the kicking motion. At the critical moment just before ball impact, the coordination between the hip and knee joints becomes highly synchronized, with the CRP value indicating a near in‐phase coordination pattern. This suggests that in the late stages of the movement cycle, the flexion and extension movements of the hip and knee joints become increasingly synchronized. At that moment, the ankle joint leads the knee joint's motion, preparing the entire leg for the kicking action. This is consistent with the findings of Nunome et al., who reported that the ankle joint exhibits higher angular velocity at the impact moment (Nunome et al. 2006). By the critical moment when the foot impacts the ball, the movements of the knee and ankle tend to be synchronized. This synchronization ensures that the power is effectively transferred from the knee to the foot, enhancing the power and accuracy of the shot. On the coronal plane, the knee joint showed more active behavior during the upward swing phase of the calf, leading the motion of the ankle and hip joints. After entering the forward swing phase, the knee‐ankle CRP curves showed that the ankle consistently leads the motion of the knee. In addition, hip‐knee CRP was significantly greater in the elite group than in the amateur group in the later stages of the forward swing phase (62%–81%), suggesting that the hip joint of elite athletes leads the knee joint abductively or adductively to a greater extent. The hip joint serves as a major source of strength in lower limb movements, and elite players typically possess a greater hip range of motion (Khan et al. 1997), which allows elite soccer players to generate greater abduction and adduction forces during goal kicking by directing knee abduction or adduction through the stronger hip joint. A study by Watanabe et al. pointed out that the hip adductors (adductor magnus and longus) play a key role in generating power and controlling movement during kicking (Watanabe et al. 2020). As a result, the hip muscle groups of elite players may be more developed, which enables them to optimize not only the transmission of power, but also to control the angle and direction of the shot more precisely through flexible adjustment of the hip joint, improving the effectiveness and accuracy of the shot. On the horizontal plane, the hip joint leads the knee joint to rotate during the shank upward swing phase in both the elite and amateur groups, whereas it shifts to the knee joint leading the hip joint during the forward swing phase. For the knee‐ankle CRP, the two joints were close to in‐phase motion during the initial moments of the shank upward swing phase (at maximal hip extension) but gradually shifted to an ankle‐dominated coordination mode as the upward swing progressed. Significant differences were demonstrated between elite and amateur players during the forward swing phase. Amateur players consistently had the ankle joint leading knee motion throughout the forward swing phase, suggesting a more fixed kinematic chain coordination and a lack of knee initiative and acceleration, resulting in a less efficient power transfer. Although the ankle joint is able to adjust foot posture (Delahunt et al. 2006), it is unable to effectively drive knee acceleration, limiting the power output of the foot during the kick. In contrast, elite players were more flexible in their coordination during the forward swing phase. Initially, the ankle leads the knee, but as the knee continues to accelerate, the knee gradually leads the ankle movement later in the forward swing phase, creating a more efficient power chain. This shift allows elite players to generate greater power and achieve more precise shot control later in the forward swing phase, significantly improving power output during the shot.

As shown in Table 2, the joint coupling relationships indicate that the maximum relative phase (MARP) of the hip‐knee in the coronal and horizontal planes is significantly greater in the elite group than in the amateur group. A larger MARP value suggests that the motion between joints is more oppositional. This indicates a greater relative phase difference between the hip and knee joints and thus greater independence in joint movement. This implies that elite players can more flexibly adjust hip and knee joints during abduction/adduction and external/internal rotation, adapting to various technical demands and improving performance. In contrast, the smaller MARP values in the amateur group suggest that their hip and knee joints tend to move more synchronously (in‐phase coordination), lacking the flexible joint dissociation seen in elite players, which leads to less efficient movement adjustments. This difference in ability may be attributed to the nervous system's precise control over specific functional muscle and joint combinations. The ability to perform skilled movements relies on the nervous system's coordination of different muscle and joint combinations, which are referred to as “coordinative structures” and are developed through repetitive practice and experience (Beek et al. 1995). Through long‐term training, elite players develop complex neuromuscular pathways that enable them to control movements more efficiently and precisely (Matsunaga and Kaneoka 2018; Brewer 2017). These complex neuromuscular pathways likely enhance joint independence, enabling more intricate joint coordination. Oishi's research shows that athletes with more extensive training experience have nervous systems that can quickly activate the correct muscle groups, optimizing force transmission while flexibly adjusting among different joints, thereby achieving precise motor control and coordination (Oishi and Maeshima 2004). In contrast, amateur athletes, due to shorter training durations, exhibit weaker neuromuscular adaptation, with less efficient muscle activation by the nervous system, leading to more fixed and simplified joint coupling patterns and more synchronous joint coordination. This fixed coupling pattern restricts the mobility and adaptability of their hip‐knee joints during complex movements in the coronal and horizontal planes, potentially decreasing lateral stability and direction control, thus impacting overall performance. Additionally, the hip‐knee and knee‐ankle DP values in the coronal plane are significantly higher in elite players than in amateurs. A higher DP value indicates greater variability or mobility in joint coordination, which aids in responding to complex movement situations (Galgon and Shewokis 2016). This suggests that elite players exhibit higher variability in joint coordination, allowing them to dynamically adjust interjoint phase relationships according to different situations and demands. This may also reflect the fact that they have greater freedom of redundancy in joint coordination. Motor redundancy refers to the fact that the body's neuromuscular system can use more than one joint, muscle, or movement pathway when accomplishing a given motor task, which means that the task can be accomplished through many different modes of coordination (Martin et al. 2009). This redundancy helps players maintain mobility and adaptability in the abduction and adduction functions of the joints of the lower extremity, especially when dealing with complex, changing game situations. In the coronal plane, hip abduction and adduction are critical to the athlete's lateral balance and directional control. Higher kinematic variability may help elite players to flexibly choose their movement strategies in different contexts, enhancing shot accuracy and kicking velocity.

It was explained in the previous section that in the sagittal plane (anterior‐posterior direction), hip and knee flexion‐extension synergy is critical for generating the kinetic energy of the shot. The significant negative correlation (R = −0.66) indicates that foot velocity increases when hip‐knee CRP values decrease. When hip‐knee CRP values are low, two possible scenarios exist: 1. In‐phase coordination mode (CRP > 0): A low hip‐knee CRP value means that the hip and knee movements are close to being in‐phase coordinated, suggesting a high degree of synchronization between the two movements. In this case, the transfer of force is more efficient. This may be due to more synchronized movement of the hip and knee joints and a smoother transfer of force from the hip to the knee and then to the foot. When hip‐knee CRP values are high, the motion between the joints is more independent, resulting in less efficient force transfer and ultimately affecting foot velocity. 2. Knee‐leading coordination mode (CRP < 0): The knee leads the hip, as indicated by a CRP less than 0. Although the hip usually plays a dominant role early in the movement, rapid knee extension may lead the hip at critical moments in the shooting maneuver. This knee‐dominant coordination mode may help to transfer forces to the foot more efficiently, which, in turn, may increase foot velocity. Therefore, a coordinated mode of hip‐knee in‐phase flexion and extension or a coordinated mode of knee‐guided hip flexion and extension may be able to improve an athlete's kicking velocity. However, based on the discrete plots, it can be seen that the subjects in this study had almost no CRP less than 0 at the moment of impact, which suggests that their hip joints still maintained their leading effects on the knee joints at this critical moment. In other words, at the moment of impact, the hip joint still dominates the movement chain, whereas the leading role of the knee joint may be more manifested in other stages (e.g., the middle of the shank upward swing). Therefore, greater synchronization of hip and knee flexion and extension movements may result in faster foot velocity. The possibility of the knee leading the hip at the moment of impact can be further explored in subsequent studies. In addition, in the vertical direction, the internal and external rotation synergy of the knee and ankle joints is usually responsible for regulating the lateral stability and directional control of the movement (Besier et al. 2001). Previous studies have shown that knee internal rotation and ankle joint adjustment play a vital part in controlling shooting direction, ball spin, and stability (Lees et al. 2009). In this study, foot velocity was found to be significantly correlated with knee‐ankle CRP in the horizontal plane, and the results in Table 3 showed that at the impact phase, the knees of both groups of athletes were usually in external rotation, whereas the ankles were in internal rotation. This antiphase coordination mode helps the athlete to adjust the contact angle with the ball more precisely, which, in turn, affects the trajectory and velocity of the soccer ball. The stronger positive correlation suggests that the more pronounced the knee leads the ankle, the faster the foot velocity. Combined with the results in Table 3, it can be seen that the external rotation angle of the knee joint of elite players is significantly greater than that of amateur players. This may be because increased external rotation of the knee joint increases the rotational moment of inertia of the leg, requiring players to apply a greater moment to propel the leg and complete the rotational movement, thus increasing power output during kicking. Thus, external rotation of the knee not only helps to optimize force transfer during shooting, but may also be one of the most important factors in the ability of elite players to generate greater shot power.

There are several limitations to this study. One important limitation is the limited ecological validity of the kicking task. Because of space constraints in the laboratory, participants were asked to perform maximal‐effort instep kicks toward a small target at a distance of 6 m. Although this setup allowed for greater experimental control, it does not fully replicate the complex perceptual, spatial, and decision‐making demands of real‐game scenarios. As such, the findings should be interpreted within the context of this controlled, nonecological environment. Another limitation is that foot velocity was used as the primary indicator of kicking performance. However, in real‐game situations—particularly during penalty kicks—performance is determined by a trade‐off between speed and accuracy, as characterized by Fitts' law (Palucci Vieira et al. 2021). Our task focused on maximizing foot speed under simplified conditions, which may not fully reflect real‐game kicking effectiveness. Therefore, the findings should be interpreted as reflecting only the speed‐related aspect of performance.

5. Conclusion

In this study, it was found that the athletic level had a significant effect on the joint coordination and mobility during soccer instep kicking. In the forward swing phase, the hip joint of the elite group players was able to lead the movement of the knee joint to a greater extent in the coronal plane, whereas the knee joint was able to lead the rotation of the ankle joint more effectively in the horizontal plane. In addition, players in the elite group showed significantly higher joint coordination variability in the coronal plane than the amateur group, and this variability may have contributed to their demonstration of higher joint mobility in different environments or athletic tasks. Further analyses showed that the more closely synchronized the knee and hip flexion‐extension were at the impact phase, and the more pronounced the knee's leading of the ankle's movement in the horizontal plane, the faster the foot velocity. These results suggest that joint coordination is closely related to kicking velocity and is an important factor in kicking performance.

Author Contributions

All authors have made substantial contributions to the manuscript. Zhanyi Zhou: conceptualization, methodology, data analysis, and writing the original draft. Zixiang Gao: experiment execution and reviewing the manuscript and providing critical insights. Fengping Li: preliminary data processing. Dongxu Wang: post‐processing of experimental data and coding. Yucheng Wang: literature review and sourcing relevant references. Gusztáv Fekete: supervision and editing the final draft. Yaodong Gu: funding acquisition, project administration, and overall supervision.

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

The authors thank the Zhejiang Key Research and Development Program (Grant No. 2023C03197), the Zhejiang Province Science Fund for Distinguished Young Scholars (Grant No. LR22A020002), the Ningbo Key Research and Development Program (Grant No. 2022Z196), the Ningbo Natural Science Foundation (Grant No. 2022J065), and the K. C. Wong Magna Fund in Ningbo University for their financial support. It is important to note that the funding agencies were not involved in the collection, analysis, or interpretation of any data.

Zhou, Zhanyi , Gao Zixiang, Li Fengping, et al. 2025. “Comparison of Interlimb Coordination During Soccer Instep Kicking Between Elite and Amateur Players.” European Journal of Sport Science: e70041. 10.1002/ejsc.70041.

Funding: This study was sponsored by the Zhejiang Key Research and Development Program (Grant No. 2023C03197), the Zhejiang Province Science Fund for Distinguished Young Scholars (Grant No. LR22A020002), the Ningbo Key Research and Development Program (Grant No. 2022Z196), the Ningbo Natural Science Foundation (Grant No. 2022J065), and the K. C. Wong Magna Fund in Ningbo University.

Data Availability Statement

Because of the nature of this research, the data are not publicly available. However, additional details regarding the methodology and analysis are available from the corresponding author upon reasonable request. The code for calculating continuous relative phase (CRP) is publicly available at the GitHub repository (https://github.com/teresashchen/crpdp). Independent‐samples t‐tests were performed in the open‐source package spm1d (https://spm1d.org/).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Because of the nature of this research, the data are not publicly available. However, additional details regarding the methodology and analysis are available from the corresponding author upon reasonable request. The code for calculating continuous relative phase (CRP) is publicly available at the GitHub repository (https://github.com/teresashchen/crpdp). Independent‐samples t‐tests were performed in the open‐source package spm1d (https://spm1d.org/).

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