Authors: Zeynep Inci Karadenizli
Categories: Research, Single-leg stability, Postural deviation, Direction-specific balance, Soccer, Football
Source: BMC Sports Science, Medicine and Rehabilitation
Authors: Zeynep Inci Karadenizli
In sports such as soccer, which require sudden directional changes and single-leg stability, postural balance is a key determinant of performance. Insufficient knowledge regarding how balance levels influence directional changes and their potential relationship with injury risk remains a relevant practical problem in soccer. However, balance is often evaluated using single composite scores, while the relationships between directional postural deviations and central stability remain underexplored. Addressing this gap may improve the understanding of direction-specific balance demands in athletes. This study examined the associations between four-directional postural deviations and central stability obtained from a controlled dynamic single-leg postural stability test, and their relationships with lower extremity muscle strength and anthropometric characteristics. The applied methodology, incorporating anthropometric characteristics, was used to better approach this problem. A total of 95 male soccer players participated. Before interpretation, it is noted that lateral–medial and anterior–posterior deviation pairs are computed as proportional distributions by the device software; therefore, their strong inverse correlations (ρ = − 1.00) reflect mathematical dependency rather than biomechanical opposition. Significant correlations were observed between height and both body weight (ρ = 0.68) and lower extremity muscle strength (ρ = 0.51). Height was positively associated with lateral postural deviation (ρ = 0.30). Central stability was positively associated with height (ρ = 0.50) and demonstrated moderate directional relationships with lateral (ρ = 0.44) and medial deviation (ρ = − 0.44) (p < .01). In contrast, body weight and relative lower extremity strength showed weak or borderline associations with directional postural deviations. These findings suggest that postural control in soccer players exhibits directional organization influenced by anthropometric characteristics, indicating that individualized balance training approaches may be beneficial, particularly for optimizing direction-specific performance, while causal inferences cannot be made due to the cross-sectional design.
Postural balance is defined as the ability to effectively control the body’s center of gravity in relation to the base of support [1], and it represents a complex motor skill regulated through the integration of the visual [2], vestibular [3], and somatosensory [4] systems. For athletes, this ability not only enhances movement efficiency [5], but also plays a critical role in injury prevention [6], and in the development of motor control strategies [6, 7]. Despite its recognized importance, limited knowledge exists regarding how balance capacity in specific directions influences sport-specific actions such as directional changes and injury-related mechanisms. Particularly in soccer, a sport characterized by multidirectional movement patterns, sudden changes of direction, and frequent demands for single-leg stability [8, 9], postural balance emerges as a fundamental component of performance. Therefore, identifying direction-specific balance characteristics represents a relevant practical and scientific problem in soccer performance and injury prevention. Accordingly, assessing postural control capacity in soccer players not only through composite balance scores but also in relation to directional sway patterns and structural characteristics provides a more comprehensive perspective.
Dynamic balance assessments often employ force platforms, balance boards, or functional tests such as the Star Excursion Balance Test (SEBT) and the Y-Balance Test. However, these tools typically define balance performance using summary parameters, such as total sway distance, sway velocity, or stability indices. This approach does not allow for a detailed analysis of center-of-gravity excursions in specific directions [10, 11]. As a result, potentially meaningful directional deficits that may affect directional change performance or injury susceptibility can remain undetected. Yet, the postural control system generates multidirectional neuromuscular responses to perturbations, and these responses are not equally effective across all directions [12–14]. Accordingly, the decomposition of balance performance into anterior, posterior, medial, and lateral sway components enables a more detailed understanding of individual balance strategies and the identification of potential weak points [15]. Moreover, despite directional deviations, the ability to maintain the center of gravity within the central region—defined as central stability—offers important insights into recovery capacity during balance challenges.
Beyond performance assessment, it is essential to examine the relationships between directional balance parameters and individual physical characteristics. In particular, lower extremity muscle strength plays a decisive role in the effectiveness of postural correction strategies [16, 17]. Adequate strength of the quadriceps and hamstrings allows rapid repositioning of the center of gravity toward equilibrium during perturbations [18, 19]. Previous studies have shown that insufficient muscle strength is associated with increased postural sway and reduced stability [20, 21]. Additionally, anthropometric characteristics such as height and body weight also influence balance [22, 23]. Height determines the elevation of the center of gravity, which may lead to greater sway amplitudes [24], whereas body weight imposes greater physiological demands on corrective balance moments [25]. Considering these anthropometric variables alongside directional balance parameters may therefore contribute to a better understanding of individual balance strategies. Analyzing these variables independently provides more precise biomechanical insights compared to the Body Mass Index (BMI), which can be misleading in athletes with high muscle mass.
Most existing studies have examined the associations between balance, muscle strength, or body composition using overall balance scores [26–28]. However, the specific relationships between directional postural deviations and central stability remain largely unexplored. Furthermore, studies adopting a multidimensional approach to assess directional balance parameters in conjunction with muscle strength, height, and body weight are scarce. This lack of evidence limits the ability to translate balance assessment findings into targeted training or injury prevention strategies. Such a comprehensive perspective holds significant practical value for designing individualized balance training programs and improving the understanding of injury-related risk factors in athletes.
The purpose of the present study was to investigate the relationships between four-directional postural deviations (anterior, posterior, medial, lateral) and central stability, measured via the single-leg dynamic limits of stability test in soccer players. Additionally, the study aimed to explore the associations of these parameters with lower extremity muscle strength and anthropometric variables such as height and body weight.
Based on previous research indicating that postural control may vary according to anthropometric characteristics and neuromuscular function, we hypothesized (1) directional postural deviations would be significantly associated with central stability, (2) greater lower extremity muscle strength would be related to better stability performance, and (3) height and body weight would demonstrate measurable associations with directional postural control patterns.
To determine the required sample size for this study, an a prior power analysis was conducted using G*Power 3.1.9.7. For the planned correlation analyses, a medium effect size (ρ = 0.30), a significance level of 5% (α = 0.05), and a statistical power of 80% (1–β = 0.80) were assumed. Based on these parameters, a minimum of 84 participants was determined to be necessary to achieve sufficient statistical power. To prevent potential data loss and enhance the reliability of the analyses, the sample size was increased to 95 participants, all of whom were male soccer players. The inclusion criteria were defined according to both demographic and athletic characteristics. Eligible participants were required to be between 18 and 25 years of age, to have at least five years of licensed soccer experience, and to be actively engaged in regular training sessions and official competitions with a registered soccer club at the time of the study. Only male athletes were considered, and participants were required to demonstrate sufficient cognitive ability to comprehend the testing protocols, as well as to have no professional background in other sports disciplines. Regarding health status, participants were required to have a functional vestibular system, no current use of pharmacological agents that could affect balance, and no symptoms of fatigue, pain, or acute physical discomfort on the test day. The exclusion criteria were based primarily on the participants’ injury history and current health conditions. Individuals with any lower extremity injury within the past six months, or with existing acute or chronic musculoskeletal disorders, were excluded. Common and severe soccer-related injuries such as anterior cruciate ligament (ACL) ruptures, meniscal lesions, major ankle sprains, or ligament tears of the knee were considered exclusionary. Furthermore, participants with vestibular dysfunctions, neurological disorders, the use of medications affecting balance, cognitive difficulties in following test instructions, or refusal to provide informed consent were not included in the study. The demographic characteristics of the participants are presented in Table 1.
Table 1Demographic characteristics of the participantsVariable N MinimumMaximumMeanStd. DeviationAge (year)9519.0023.0019.650.85Height (cm)95154.00195.00173.737.90Weight (kg)9547.00113.1068.3212.98Leg strenght (kgf)9569.50255.00147.4041.01
Table 1 presents the demographic characteristics of the participants. The players’ age ranged from 19 to 23 years (mean ± SD: 19.65 ± 0.85 years). Height values varied between 154.00 and 195.00 cm, with a mean of 173.73 ± 7.90 cm. Body weight showed a wide range, from 47.00 to 113.10 kg (68.32 ± 12.98 kg), indicating substantial inter-individual variability within the sample. Lower extremity strength values ranged from 69.50 to 255.00 kgf, with a mean of 147.40 ± 41.01 kgf.
This study was structured as a cross-sectional design within a non-causal correlational survey model. The study was conducted in accordance with the ethical decision numbered 2025/386 of the Düzce University Scientific Research and Publication Ethics Committee in accordance with the Helsinki Declaration and with signed informed consent forms obtained from the participants. The data collection process was organized into three stages with all measurements performed in a single session. In the first stage basic anthropometric characteristics including age, body height, and body weight, were measured and recorded using a calibrated stadiometer and a digital scale. In the second stage, lower extremity muscle strength was assessed using a digital isometric leg strength dynamometer (Takei T.K.K. 5402, Japan). Participants were positioned on the platform with their knees flexed at approximately 120° and instructed to produce maximum voluntary contraction. Each participant performed two trials and the higher value was retained for analysis. In the third stage postural balance was evaluated. Balance assessment was conducted in a single-leg stance using a high-precision force platform (Sigma System, CosmoGamma, Italy). Participants were instructed to stand barefoot on their dominant leg, focusing on a fixed visual target, while attempting to maintain balance for 30 s. During the trial, postural deviations in the anterior, posterior, medial, and lateral directions, as well as the percentage of “central stability” were recorded. The system automatically calculated the extent of directional sway and deviations from the stability center in percentage values. Before testing all participants were thoroughly briefed about the procedures and completed two practice trials to ensure familiarity. Measurements were conducted in the morning under quiet and well-lit conditions, with ambient temperature maintained between 22 and 24 °C. To minimize fatigue effects, a rest period of at least two minutes was provided between trials. Participants were also instructed to refrain from performing strenuous physical exercise within 24 h prior to testing.
The measurement of participants’ body height and body weight was conducted in accordance with the standards set by the International Society for the Advancement of Kinanthropometry (ISAK). To ensure data reliability and reproducibility, all measurements were performed by the same investigator under similar environmental conditions [29]. Height measurement was taken with participants standing barefoot on a flat surface in an upright posture. During the measurement, the heels, buttocks, and upper back were aligned against the wall, while the head was positioned parallel to the Frankfurt Horizontal Plane (aligned with the tragus and the inferior orbital margin). Height was measured using a calibrated portable stadiometer (Seca 213, Seca GmbH & Co, KG, Hamburg, Germany) and recorded in centimeters (cm) to the nearest 0.1 cm. Body weight measurement was performed in the morning, with participants barefoot, wearing light clothing, and standing motionless on a firm surface. A digital weighing scale (Omron HN-289, Omron Healthcare Co., Ltd., Kyoto, Japan) was used. The device was reset before each measurement. and calibration was verified prior to use. Weight values were recorded in kilograms (kg) with a precision of 0.1 kg.
Lower extremity muscle strength was assessed using a leg dynamometer (Takei T.K.K. 5402, Takei Scientific Instruments Co., Ltd., Niigata, Japan), a widely employed device for isometric strength testing. Dynamometers have been used for many years to determine force, and numerous studies have demonstrated that dynamometer-based force measurements are reliable and valid for assessing lower extremity strength [30–32]. Prior to the measurements, participants completed a standardized 5-minute warm-up protocol consisting of low-intensity general exercises and dynamic stretching movements targeting the lower extremity muscles. During testing, participants stood barefoot on the platform of the dynamometer with full plantar contact. The knees were positioned at approximately 120° of flexion, the back was kept straight, and the trunk was slightly inclined forward. Participants were instructed to pull the bar vertically upward with maximal effort using only the lower extremity muscle groups, while keeping their arms fully extended, elbows fixed, and hands firmly gripping the bar. The testing protocol was explained in detail, and each participant performed one familiarization trial prior to data collection. Subsequently, two maximal trials were completed with a one-minute rest interval between attempts. Force values were recorded in kiloponds (kgf), and the higher value of the two trials was retained for further analysis. The dynamometer was reset and checked for safety prior to each measurement. Movements not consistent with the testing protocol, such as excessive trunk extension, shoulder elevation, or contribution from the upper extremities, were not permitted. Trials were repeated if technical errors, improper execution, or device-related deviations were observed, in order to ensure standardization and internal validity. In addition to absolute strength values, relative lower extremity strength was calculated for use in the correlation analyses. Absolute leg strength values recorded in kiloponds (kgf) were first converted to Newtons (N) using the standard gravitational conversion factor (1 kgf = 9.80665 N). Subsequently, relative strength values were obtained by normalizing the converted force values to the participant’s body mass, resulting in relative leg strength expressed in N/kg. These relative strength values were used in the statistical analyses to account for inter-individual differences in body mass and to allow for a more physiologically meaningful comparison of lower extremity strength across participants.
Postural stability was assessed using a controlled dynamic single-leg postural stability test performed on the Sigma Balance System (CosmoGamma, Italy). The Sigma Balance System is a portable balance assessment device designed to quantify postural control under dynamic stability constraints. The platform is equipped with sensors that detect changes in platform position and swing angle, and the recorded signals are transmitted wirelessly in real time to a computer for analysis. The system software computes postural deviation parameters and central stability indices based on center-of-pressure displacement metrics, as previously described [33–35]. Participants were tested barefoot, standing on their dominant leg with eyes open. Each trial lasted 30 s. Participants were instructed to maintain balance near the central stability region of the platform without performing voluntary center-of-mass shifting movements. The Sigma software applies a 20% tolerance boundary around the central stability zone, requiring continuous corrective adjustments to remain within the defined limits. Accordingly, although this procedure does not follow the classical Limits of Stability paradigm involving intentional, target-directed center-of-mass excursions, it also does not represent a static postural sway assessment. Instead, the procedure reflects controlled dynamic postural stability, in which spontaneous sway is regulated under constrained deviation limits [36–39].
The system automatically calculated the percentage of central stability and directional deviations (anterior, posterior, medial, lateral). Participants completed one familiarization trial followed by one recorded trial. A standardized 2-minute seated rest interval was provided between these trials to minimize fatigue-related alterations in postural control. All assessments were conducted by the same examiner in a controlled laboratory environment. Single-leg stance trials of similar duration have demonstrated acceptable reliability and sensitivity for postural control assessment [40].
All All data analyses were performed using GraphPad Prism software (GraphPad Prism v.X; GraphPad Software Inc., La Jolla, CA, USA). Initially, the distributional characteristics of the variables were examined using the Shapiro–Wilk test for normality. Since the assumption of normality was not satisfied (p < .05; Table 2), non-parametric statistical methods were deemed appropriate and therefore employed.
Table 2Normality analysis of right-side balance parameters (Shapiro–Wilk test)ParameterWp valueNormal distribution (α = 0.05)Lateral0.970.04NoMedial0.960.02NoAnterior0.940.00NoPosterior0.940.00No
To evaluate the associations between directional postural deviation percentages and central stability, as well as the relationships of these balance parameters with lower extremity muscle strength, height, and body weight, Spearman’s rank-order correlation analysis was applied. For each variable pair, the Spearman correlation coefficient (ρ) and corresponding p-value were calculated. The direction (positive/negative) and magnitude (weak, moderate, strong) of the correlations were interpreted in accordance with conventional standards reported in the literature. The correlation results were presented in both tabular and graphical formats. In particular, heatmaps were utilized to visualize multivariate correlation patterns, with the strength of associations represented through color intensities. For all statistical analyses, a significance level of p < .05 was adopted. It should be noted that the directional postural deviation variables (anterior, posterior, medial, and lateral) are derived from the same center-of-pressure trajectory and therefore do not represent fully independent biomechanical constructs. Accordingly, the observed strong inverse correlations between certain directional deviation pairs were interpreted as reflecting the inherent mathematical dependency within the device’s calculation procedures rather than distinct physiological control mechanisms. The interpretation of directional correlations was therefore approached cautiously, and no causal inferences were drawn based on these relationships.
Normality of the balance parameters was assessed using the Shapiro–Wilk test, and none of the variables satisfied the assumption of normal distribution (p < .05), supporting the use of non-parametric correlation analyses.
Before presenting the correlation findings, a methodological clarification regarding the directional deviation variables is necessary. The Sigma Balance System calculates lateral–medial and anterior–posterior deviations as proportional distributions of the total sway. Therefore, these opposite directional pairs are mathematically dependent. As a result, the observed perfect inverse correlations (ρ = − 1.00) reflect the system’s calculation structure rather than a biomechanical relationship, and these values were not interpreted functionally in this study. The results reported below were evaluated with this methodological characteristic in mind.
The significance values obtained from the Spearman correlation analyses are presented in Table 3, and the correlation coefficients are shown in Table 4. In addition, Fig. 1 displays a heatmap illustrating the relative strength and direction of the associations among variables.
Table 3p-values from Spearman correlation analyses among study variablesAgeHeightWeightLeg StrengthLateralMedialAnteriorPosteriorCentering0.100.780.640.920.920.340.340.61Height—0.010.010.010.010.610.610.01Weight—0.010.260.260.140.140.18Leg Strength—0.620.620.320.320.36Lateral—0.010.580.580.01Medial—0.580.580.01Anterior—0.000.55Posterior—0.55**p* < .01
Table 4Spearman correlation coefficients (ρ) and p-values among postural deviation variables, centering stability, and physical characteristicsVariable 1Variable 2ρ p Lateral Postural Deviation (%)Medial Postural Deviation (%)-1.00< 0.01Anterior Postural Deviation (%)Posterior Postural Deviation (%)-1.000.01Centering Stability (%)Lateral Postural Deviation (%)0.440.01Height (cm)Centering Stability (%)0.500.01Height (cm)Lateral Postural Deviation (%)0.300.01Weight (kg)Directional Deviations−0.05–0.180.05Leg Strength (N/kg)Directional Deviations−0.10–0.220.05ρ: Spearman’s rank correlation coefficient, p: significance level
Fig. 1Heatmap of spearman correlations among variables
Table 3 shows that body height was significantly correlated with body weight, leg strength, lateral and medial postural deviations, and centering stability (p < .05). A significant correlation was also observed between body weight and leg strength (p < .05). Among postural control variables, lateral–medial and anterior–posterior deviation pairs demonstrated statistically significant associations (p < .01). Furthermore, both lateral and medial deviations were significantly correlated with centering stability (p < .01). In contrast, age did not show significant correlations with the examined variables (p > .05), and anterior–posterior deviations were not significantly associated with centering stability (p > .05).
Figure 1 illustrates the Spearman correlation coefficients among anthropometric variables, relative lower limb strength, directional postural deviation measures, and centering stability using a color gradient. The color scale ranges from dark purple (− 1.00) to bright yellow (+ 1.00), and the diagonal cells equal 1.00, representing each variable’s self-correlation. In the heatmap, body height appears positively correlated with body weight and leg strength. The lateral–medial and anterior–posterior deviation pairs display correlation coefficients of − 1.00. As noted previously, this inverse relationship reflects the mathematical dependency inherent in the Sigma Balance System’s directional deviation calculations, where opposite directional components are derived as proportional complements; therefore, these values do not represent independent biomechanical relationships and were not interpreted functionally in this study. Centering stability shows a positive correlation with lateral deviation and a negative correlation with medial deviation. Age demonstrates generally low correlation values across variables. The heatmap visually represents the relative strength and direction of associations, while detailed numerical correlation coefficients and corresponding p-values are provided in Table 4.
Table 4 summarizes the Spearman rank-order correlation coefficients (ρ) and corresponding p-values among postural deviation variables, centering stability, and selected physical characteristics. The lateral–medial and anterior–posterior directional deviation pairs exhibited perfect negative correlations (ρ = −1.00, p ≤ .01), which are attributable to the reciprocal and proportional calculation structure of the balance measurement system rather than independent biomechanical control mechanisms. Centering stability demonstrated a moderate positive correlation with lateral postural deviation (ρ = 0.44, p = .01). Body height was moderately correlated with centering stability (ρ = 0.50, p = .01) and weakly correlated with lateral postural deviation (ρ = 0.30, p = .01). In contrast, body weight and relative lower extremity strength (N/kg) showed weak and borderline associations with directional postural deviations (|ρ| ≤ 0.22, p = .05), suggesting a limited contribution of these variables to single-leg postural deviation behavior in the present sample.
This study examined the relationships between four-directional postural deviations (anterior, posterior, medial, lateral) and central stability, as measured by the controlled dynamic single-leg postural stability test, and evaluated their associations with lower extremity muscle strength and anthropometric characteristics (height and body weight) in soccer players. Before interpreting the findings, it is important to reiterate that the lateral–medial and anterior–posterior deviation pairs are computed as proportional components derived from the same center-of-pressure trajectory. Therefore, the perfect inverse correlations observed between these directional pairs reflect the mathematical structure of the device’s calculation procedures rather than independent biomechanical or neuromuscular control strategies. Accordingly, these associations should be interpreted with caution and should not be considered as evidence of distinct neuromuscular control mechanisms.
The results of this study indicate that body height and body weight are positively associated with leg strength in soccer players. Previous research focusing on body composition has shown that increases in lean body mass and total muscle mass improve athletic performance and are directly linked to force production [41]. In soccer-specific contexts, maximal leg strength has been shown to correlate significantly with sprinting and jumping performance, and squat-based training has been reported to improve acceleration and jump capacity [42]. Moreover, increases in leg muscle mass have been strongly correlated with leg strength, supporting the close association between body weight and force capacity [43]. Thus, height and body weight likely contribute to soccer performance, particularly through muscle mass. However, this relationship may vary depending on player position, maturation, and training adaptations, and therefore should not be generalized without caution. Because player positions were not recorded in the present study, potential position-specific differences in strength and anthropometric profiles could not be examined, which may have influenced the observed associations.
The findings also highlight the influence of height on postural sway, particularly in the medial and lateral directions. Some studies have suggested that height may act as a covariate in sway parameters [44]. However, a large-sample study found that age and sex were significant predictors, while height did not exert an independent effect [45]. Other studies, focusing on factors such as obesity or prolonged standing, have reported changes in sway behavior, but these investigations emphasized body weight, age, or sensory input rather than directly linking height to medial or lateral deviations [46, 47]. Therefore, while the literature implies that height may influence postural sway, evidence regarding its specific effects on medial–lateral deviations remains inconsistent. In soccer, taller players may benefit from aerial duels, yet they could be disadvantaged in balance tasks requiring a lower center of gravity.
Another important finding of this study is that postural control involves direction-specific but mathematically interdependent regulation patterns, particularly between medio-lateral and antero-posterior deviations. Postural stability is inherently complex, and interactions among deviations in different directions can significantly influence overall balance. Research on static and dynamic stability has shown that medio-lateral and antero-posterior directions contribute differently to stabilization over time, especially during single-leg stance and jump-landing tasks [48]. Studies using galvanic vestibular stimulation have also demonstrated that antero-posterior sway may be particularly sensitive to vestibular inputs [49]. However, in the present study, the observed perfect inverse relationships between opposite directional deviations should be interpreted as computational artifacts rather than physiological constraints. In soccer, this distinction is relevant during rapid directional changes, single-leg balance challenges, and re-stabilization following physical contact.
The positive association between body height and centering stability observed in this study suggests that anthropometric characteristics may influence postural control strategies during controlled dynamic balance tasks. Although a higher center of mass is often assumed to impair balance, the present findings indicate that taller players may compensate through neuromuscular adaptations developed via sport-specific training. Differences in sport-specific demands are also important in understanding this relationship. For instance, shorter gymnasts have been shown to outperform taller athletes in balance tasks, while taller athletes dominate in sports such as swimming [50]. Nevertheless, sport-specific training can compensate for potential anthropometric disadvantages [15]. In soccer, taller goalkeepers may hold an advantage in aerial challenges, but they could be disadvantaged in tasks requiring rapid low-level reactions and balance recovery. Therefore, training strategies that consider individual anthropometric profiles may be beneficial.
Finally, the relationships observed between lateral and medial deviations and central stability highlight the directional specificity of postural control. Limited lateral sway has been reported to assist in maintaining balance by stabilizing the alignment between the center of mass (COM) and center of pressure (COP) [51, 52]. Conversely, increased medial sway has been associated with instability, particularly among older adults and individuals with high anxiety levels, thereby increasing the risk of falls [53]. In athletic populations, controlled lateral sway may reflect adaptive balance regulation rather than instability, particularly during dynamic tasks such as cutting and landing maneuvers.
This study has several limitations. First, the sample was homogeneous, consisting only of similarly trained male soccer players, which limits generalizability. Second, no control group from different sports or non-athletic populations was included. Third, the laboratory-based protocol, while controlled, may not fully reflect sport-specific balance demands. Additionally, player positions were not documented, which may have introduced variability in postural control and strength outcomes due to differing positional demands. Moreover, the relatively high variability in anthropometric characteristics within the sample may have contributed to inter-individual differences in postural stability measures. Additionally, factors such as limb dominance, proprioceptive acuity, fatigue, and psychological state were not assessed and may influence postural control. Future studies should consider larger and more heterogeneous samples, including position-specific analyses, longitudinal monitoring, and intervention-based designs to determine whether direction-specific balance profiles predict injury risk or performance outcomes.
The findings of this study suggest that four-directional postural deviations and central stability in soccer players are influenced by direction-specific postural control characteristics and individual anthropometric factors. Because directional deviation values are computed as proportional distributions derived from the same center-of-pressure trajectory, interpretations of inverse relationships between paired directions should be made cautiously and not considered to represent independent biomechanical control patterns. Accordingly, these relationships should be interpreted as reflecting the computational structure of the assessment system rather than distinct physiological regulation strategies. The results also indicate that body height may influence stabilization demands during controlled single-leg stance tasks, suggesting that anthropometric characteristics may contribute to individual postural control strategies. In contrast, relative lower extremity muscle strength demonstrated only weak or borderline associations with directional postural deviations, indicating a limited contribution within the present sample. Rather than supporting generalized balance assessments or uniform training strategies, these findings highlight the potential value of incorporating individual physical characteristics and direction-specific postural control behaviors into balance evaluation and training planning. Given the variability in anthropometric profiles, the homogeneous sample composition, and the absence of position-specific analyses, conclusions should be interpreted within the context of the study’s limitations. Future research should examine whether personalized balance training programs based on directional deviation profiles and player-specific characteristics are associated with improved movement control and reduced injury risk in soccer players using longitudinal or intervention-based designs.