The study employed a cross-sectional correlational research design to investigate the associations between foot measurements and football shooting performance, specifically accuracy and distance. The design also incorporated between-group comparisons based on foot-type classifications and the computation of a study-specific Injury Risk Index to evaluate theoretical biomechanical susceptibility. The analysis design was suitable for investigating connections between anthropometric variables and performance skills without manipulating any variables.

The researchers selected 62 female football players, aged 22 to 28, who were enrolled in the Master of Physical Education program at Pondicherry University. The investigators selected competition football participants who had consistently played with experience and technical ability to form the participant sample. The study only included participants whose backgrounds matched a comparable level of football training experience and participation history to maintain homogeneity and reliability of findings. On average, participants had 5–8 years of competitive experience. The study excluded participants who experienced any injuries to their lower limbs during the previous six months to control for potential confounding variables. The football players whose experiences made up the study had between 5 and 8 years of competitive high-level play. Recent foot and leg injuries within the past six months served as exclusion criteria for participants in this study. Although playing position was not one of the main factors for participant selection, it led to a variety of selections among midfielders, forwards, defenders, and goalkeepers, which created an authentic representation of football-specific performance requirements.

All participants delivered voluntary consent following an explanation about the nature of the research to participate in this study. Subjects were free to withdraw from the study at any time. Ethical permission for this research was obtained from the Institutional Ethics Committee in accordance with the Declaration of Helsinki ethical guidelines.13

The data collection required two organised sessions to obtain anthropometry measurements and performance-related variables. In the first session, participants completed a structured demographic questionnaire capturing age, height, weight, and years of competitive football experience. The second session included three assessment methods. A manual footprint tracing method was employed to measure foot arch characteristics, and the Foot arch classification was conducted using the Chippaux-Smirak Index (CSI). Football shooting performance was assessed using the Mori-Christian General Soccer Ability Skill Test, a standardised protocol recognised for validity in measuring shooting accuracy under controlled conditions. The shooting distance was measured using the Maximal Kicking Distance (MKD) Test. Neuromuscular stability was evaluated using the Y-Balance Test-Lower Quarter (YBT-LQ). The assessments began with standardised instructions and demonstrations to maintain procedural consistency. The participants received strict instructions to avoid vigorous physical activities 24 h before the session, and the testing sessions were conducted under stable conditions to mitigate potential confounding factors such as fatigue and environmental variability.

Data were analysed using IBM SPSS Statistics (Version 27). The Shapiro-Wilk test and review of Q-Q plots were used to assess normality of the continuous variables, enabling the selection of appropriate correlation and group comparison procedures. All variables of the performance and foot measurement were subjected to descriptive statistics (mean and standard deviation). A post hoc power analysis was conducted using G*Power 3.1 based on the primary between-group comparisons (one-way ANOVA), assuming a medium effect size (f = 0.30), an alpha level of 0.05, and a total sample size of N = 62. The achieved statistical power (1−β) was 0.75, indicating moderate statistical sensitivity to detect medium-sized effects. The relationships between foot measurements, shooting accuracy and maximal kicking distance were investigated by Pearson correlation coefficients. One-way ANOVA was used to compare the performance and injury risk of the different foot types (flat foot, neutral foot and high arch). When the ANOVA was significant, Scheffe post-hoc tests were applied to identify pairwise differences. The analysis was conducted using multiple linear regression to determine the extent to which the Stability Score and Foot Measurement predicted Injury Risk. The regression coefficients are given with significance values, and the model fit index (R, R², adjusted R², F-statistic) are reported. Effect sizes were calculated for the main analyses: Pearson r (correlations), partial eta-squared (η2) (ANOVA), and f2 (Cohen) (regression model). The set level of statistical significance was p < .05 (two-tailed).

Table 1 shows the descriptive statistics of the structural and performance variables in the three groups of foot types. The primary analysis of the data showed that there was a clear morphological difference between flat-footed, neutral-footed, and high-arched athletes, with the existence of a significant disparity in performance and neuromuscular indicators.

The scores in Table 1 provide a comprehensive outline of structural gradient by the type of foot. The flat-footed athletes recorded the highest mean foot length (45.32 / 3.4 cm) and high arched athletes recorded the lowest (32.48 / 2.9 cm). The difference in the performance results was based on these structural differences: neutral-footed athletes had the highest mean kicking distance (50.45 ± 8.5 m) and accuracy scores (28.90 ± 5.1 units) which suggests a higher biomechanical efficiency. In contrast, the performance values of flat-footed athletes were significantly lower, with the mean distance of (38.10±7.2 m) and the accuracy of (22.25 ± 4.3) units, and the high-arched athletes demonstrated intermediate performance scores.

The groups were also differentiated by stability and injury risk patterns. The most favourable neuromuscular profile was found in neutral-footed athletes, whose stability score was 9.1, and risk of injury was the lowest (2.3). Flat-footed athletes demonstrated the lowest stability (4.2) and the highest risk of being injured (8.1) which is in line with excessive pronation and a lack of structural support. High-arched participants showed moderate stability (5.3) and high risk of injury (7.2), as a result of reduced shock-absorption capacity of cavus foot morphology.

The aggregate sample means of foot measurement (38.05 8.32 cm), distance (44.63 9.99 m), and accuracy (26.13 5.63 units) place the group-specific patterns into a larger performance framework. These results overall indicate a clear structural-functional gradient in the sample, in which female football players in neutral foot posture have more efficient biomechanics, and those with flat-footed or high-arched foot morphology have quantifiable drawbacks in their performance and injury patterns. Such descriptive tendencies give a definite structural-functional correlation, which forms the basis of the inferential analyses in the following sections.

One-way ANOVA was conducted to identify significant differences in the risk of injuries between the three groups of feet (flat foot, neutral foot and high arch). As demonstrated in Table 2, the effect of foot type on injury risk was statistically significant, which means that differences in the morphology of feet are associated with significant differences in the theoretical injury-related index.

It was found that the Injury Risk Index scores differed significantly among the groups (F = 39.73, p < .001). Post-hoc Scheffe comparisons revealed that neutral-footed athletes had a much lower risk of injury compared to both flat-footed (p < .001) and high-arched athletes (p < .01). Also, High-arched athletes demonstrated a lower injury risk than flat-footed athletes; however, their risk remained substantially elevated compared with neutral-footed players, and this difference was statistically significant (p < .05). All of these findings indicate that there is a definite gradient of injury risk, with the neutral-footed athletes showing the most favourable profile and the flat-footed ones showing the highest susceptibility. The relevance of foot morphology as a predictor of Injury Risk Index values is highlighted by these patterns and gives ground to future correlation and predictive modelling studies.

The correlation coefficients between the foot measurements, kicking accuracy and kicking distance were calculated using Pearson correlation coefficients to test the association between them. The findings showed that all variables had strong positive correlations, which showed that structural foot characteristics have strong ties with performance outcomes. Table 3 shows these correlations

The correlation coefficients between the foot measurements, kicking accuracy and kicking distance were calculated using Pearson correlation coefficients to test the association between them. The findings showed that all variables had strong positive correlations, which showed that structural foot characteristics have strong ties with performance outcomes. Table 3 shows these correlations. Foot measurements and accuracy had a very strong correlation (r = 0.95), meaning that the larger or more structurally efficient the feet, the greater the kicking precision. Similarly high correlation was also observed between foot measures and distance (r = 0.96), which indicates that foot structure has a significant contribution to the production of higher kicking power. Moreover, accuracy and distance had a high correlation (r = 0.93), and this indicates the presence of common neuromuscular and biomechanical factors that define the two dimensions of performance. Taken together, the results underscore the interdependence of structural and functional variables in football performance. These associations are strong and thus should be further investigated using predictive modelling, as discussed in the next section.

A multiple linear regression model was performed to examine the combined associations of neuromuscular stability and foot measurements with the regression-derived Injury Risk Index. The purpose of this analysis was to determine whether these two factors, which were earlier identified as structurally and functionally relevant, demonstrated a strong statistical association with Injury Risk Index scores among the athletes. The overall fit of the model was good and is summarised in Table 4.

The model was significant with a predictive power of 69% (R² = 0.69) explaining the variance in injury risk. Stability score became a major negative predictor (β = –0.68), which proved that the greater the neuromuscular stability, the lower the Injury Risk Index score. Foot measurement was also a strong predictor (β = +0.15), where bigger or structurally different feet were observed to be associated with higher Injury Risk Index values. The combination of the predictors also demonstrated an interaction between the structural and neuromuscular factors in injury risk determination. These findings uphold the categorization of athletes into risk groups in practice, which is discussed later in the next section.

In order to convert the results of the regression model into a practical framework, the results were converted into a practical risk classification by using the anticipated risk scores of injury on athletes. With the help of this categorisation, the level of individual risk can be more clearly interpreted as the stability and foot measure values. The following classification represents a model-based interpretation of predicted Injury Risk Index scores (Table 5).

According to these thresholds, athletes who had predicted scores >5 were included in the high-risk category, which is a combination of reduced neuromuscular stability and increased or morphologically different foot size. The range of scores (0 to 5) had the moderate risk, negative scores represented low risk and more favourable structural-functional profiles. This classification framework provides a structured interpretation of model-derived Injury Risk Index scores, identifying athletes with elevated index values who may require further investigation in prospective longitudinal research.

Our results showed that athletes with more desirable foot structures always ranked higher in the performance categories, and those with less desirable foot structures were found to fall in the lower performance categories in our sample. This pattern is supported by the literature where the structurally efficient foot characteristics like normal medial arches, increased foot length and breadth, and increased plantar musculature are repeatedly linked to better athletic performance.22,23 Athletes whose foot morphology has been well developed normally exhibit high stability, agility and power, which are key components of effective performance and injury resistance in sport.23–25 Past research also indicates that bigger or stronger feet are linked to higher ankle muscle power and better performance in exercises that demand explosive power and dynamic control like jumping and dynamism maneuvers.25–27 Conversely, less ideal foot anatomy including pes planus or pes cavus have been linked to impaired power, impaired balance, and injury vulnerability.28–30 All these lead to poor performance ranking. Accordingly, the available evidence supports the perception that Variations in foot morphology were significantly associated with differences in functional performance outcomes among the athletes. These structural vulnerabilities may be further amplified in women football players, who often exhibit greater joint laxity and altered lower-limb alignment patterns, making them more sensitive to variations in arch posture and foot mechanics.

This paper has also demonstrated that foot measurements and general structural efficiency were strongly related to enhanced kicking accuracy and greater kicking distance in players. This trend is in line with the available literature, which has shown that athletes that have bigger or more biomechanically efficient feet are more likely to produce higher foot velocities during the kicking action and thus have a higher ball speed and increased kicking distance.31,32 Research also reports that higher ankle rigidity and enhanced structural support on the foot lead to better impact mechanics and better transfer of forces at ball contact and therefore adds to support the performance benefits of good foot morphology.32,33 Also, there is prior evidence that relative lean mass in the kicking leg, which is strongly related to structural efficiency, is positively correlated with kicking accuracy, implying that the structure of the foot, as well as the morphology of the lower limbs can determine the results of technical performance.33,34 However, although the foot characteristics are evident biomechanical advantages, the literature highlights that the performance of kicking is multifactorial and no less depends on motor control, muscular strength, coordination, and the ability to perform the technical skills.35,36 Foot morphology is therefore to be considered as one of the determinants of successful kicking but not exclusive.

Foot morphology and neuromuscular stability assessment provides strong multidimensional associative explanatory capacity for Injury Risk Index scores and explaining skill performance among football players. This is further supported by the current literature in sports science which points out the multifactorial nature of risk of injury, caused by the interaction of the structural, functional, and neuromuscular determinants, but not by univariate predictors.52,53 Foot being the major point of contact with the ground defines the efficiency of the movements, the transmission of the force, and biomechanical positioning, and neuromuscular stability controls the positioning of the posture as well as the preservation of the dynamic joints.29 Our analysis shows that the combination of these qualities can provide a complete idea of the variability of variability in performance and variation in Injury Risk Index scores, which is why it is necessary to include assessment procedures. These implications are especially relevant for women football players, whose increased joint laxity, altered lower-limb alignment tendencies, and sex-specific neuromuscular characteristics may heighten sensitivity to foot-structure deviations and stability deficits. The practical implications of this model may inform future screening research of the foot morphology, the identification of deficits in stability, as well as the study of the movement patterns to offer individual training and areas for further prospective investigation and prevention measures. Orthotic support, along with specific neuromuscular and balance training, and custom footwear have been shown to be evidence-based interventions that maximise the biomechanical efficiency, and potentially influences injury-related outcomes. These multidimensional strategies can subsequently be incorporated in football training programmes to not only improve performance outcomes but also the health of the athletes in the long run. However, as the Injury Risk Index is a theoretical, unvalidated model, these implications should be interpreted cautiously and confirmed through longitudinal injury surveillance studies.

Despite providing novel insights into the relationship between foot morphology, neuromuscular stability, performance, and injury-related outcomes in football players, several limitations should be acknowledged. To begin with, the sample size is rather small, which can affect the external validity of the results. External validity would be enhanced by future research using larger, more diverse groups at various levels of competition. Second, the cross-sectional design limits causal inference, as measurements were recorded at only a single time point. There is a need for longitudinal, prospective cohort studies with repeated measures during a competitive season, and for systematic injury monitoring, to clarify the relationships over time between foot morphology, neuromuscular stability, performance outcomes, and injury-related outcomes. Notably, injury occurrence was not rigorously recorded in the current study. The Injury Risk Index used in this study is a theoretical value derived from a regression model, but it is based on biomechanical variables rather than recorded injury data. Hence, it cannot be understood as a validated clinical prediction instrument. Prospective research with systematic injury surveillance is required to estimate its predictive validity and practical use. Moreover, the foot structure was evaluated primarily based on static measurements, which did not provide a complete picture of dynamic foot behaviour during sport-specific movements. Three-dimensional motion analysis, in-shoe plantar pressure measurements, or wearable sensors are dynamic biomechanical measures that may be beneficial for future research. In spite of the fact that the Y-Balance Test offers a validated assessment of dynamic balance and neuromuscular control, it does not isolate the intrinsic foot function, and additional foot-specific testing might give additional evidence. Examples include ankle dorsiflexion range of motion (knee-to-wall test) or windlass mechanism test (Hubscher test), to further specify foot-specific contributions. Moreover, the measured performance variables were limited to controlled kicking measures, which may not reflect the multidimensional physical requirements of competitive football. There is the possibility that the incorporation of match-based measures like the high-speed running distance, sprint frequency, accelerations and decelerations measured using GPS technology may enhance ecological validity. Lastly, a number of extrinsic and contextual variables, such as training load, fatigue, history of injury, footwear properties, stud formation, playing surface and playing position were not incorporated into the current analysis. Future studies can be improved by adding these variables, which can also increase the specificity of the application and the ecological validity of the suggested multidimensional framework.