Relationship between nutritional adequacy and anthropometric profile characteristics according to playing position in professional female soccer players: a cross-sectional study

Abstract

Background

Anthropometric characterization and somatotype profiling in professional soccer players are essential for understanding the morphofunctional demands associated with playing positions.

Objective

To determine and compare anthropometric profile and somatotype characteristics across playing positions in professional female soccer players, and to analyze their relationship with nutritional adequacy.

Methods

A cross-sectional study was conducted with 43 players from two First Division teams in Trujillo (Peru). Anthropometric measurements followed ISAK standards, and body composition was estimated using Kerr’s five-component fractionation method. Somatotype was assessed using the Heath–Carter method. Nutritional adequacy was calculated according to playing position and international recommendations. Statistical analysis included the Kruskal-Wallis test, Chi-square tests, and Kendall’s Tau correlations. Due to sample size, goalkeeper data (n = 4) were treated purely as a descriptive case series for correlational analyses.

Results

Goalkeepers presented significantly higher adipose mass (18.6 ± 2.5 kg) and muscle mass (33.1 ± 2.2 kg) than outfield players (p < 0.05; ε² ≥0.21). Nutritional adequacy differed significantly by position, with goalkeepers displaying a descriptive 100% prevalence of protein insufficiency. For outfield players, no significant associations were found between nutritional adequacy and body composition when stratified by position (p > 0.05). However, in the total sample, protein adequacy was inversely correlated with adipose mass (Tb = − 0.60, p < 0.001), and lipid adequacy was negatively associated with muscle mass (Tb = − 0.52, p < 0.001).

Conclusions

Although no position-specific associations were identified among outfielders, significant relationships emerged in the overall sample, suggesting that nutritional adequacy is significantly associated with body composition, appearing to be a relevant factor independently of tactical role.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-026-01702-z.

Background

Women’s soccer has experienced exponential growth worldwide, a phenomenon reflected in the significant increase in federated participation and the rising scientific interest regarding the biological and technical development of the sport [1, 2]. As the female game becomes more professionalized, the physical demands on players have intensified, requiring specific morphological characteristics, such as height, body mass, and body composition, to optimize performance, prevent injuries, and execute tactical roles effectively [3, 4]. These anthropometric profiles are not uniform; literature indicates they vary significantly according to playing position due to the distinct physiological demands of each role on the field [5, 6].

Success in football is multifactorial. While technical and tactical proficiency are predominant determinants of match outcome, specific anthropometric and physical characteristics act as fundamental prerequisites to optimize performance, prevent injuries, and execute position-specific roles effectively [3, 4]. These morphological traits facilitate the physical demands of the game, serving as a structural platform upon which technical skills are applied. For instance, goalkeepers typically exhibit greater height, body mass, and absolute muscle mass compared to outfield players, traits necessary to cover the goal area and generate lower-limb power [7, 8]. Conversely, midfielders tend to present a balanced mesomorphic-ectomorphic somatotype with lower body fat levels to support high-volume running and aerobic endurance, while forwards often combine moderate musculature with low adiposity to facilitate acceleration and agility [9, 10]. However, these standards are largely based on European or North American populations. Recent evidence suggests that somatotype and body composition in female athletes can vary significantly based on geographic origin, ethnicity, and competitive level, meaning international references may not apply to all populations [11, 12].

To achieve and maintain these optimal physical profiles, nutritional adequacy is a determining factor. Professional female soccer players face high energy expenditures, often requiring between 2,000 and 3,000 kcal/day depending on training load and match demands [13, 14]. Current consensus statements recommend carbohydrate intakes of 5–8 g/kg/day to replenish glycogen stores and protein intakes of 1.2–2.0 g/kg/day to support muscle repair and adaptation [15, 16]. Furthermore, dietary lipids are crucial for female athletes, with recommendations suggesting they should comprise 20–35% of total energy intake. Adequate fat consumption is vital for meeting energy needs, absorbing fat-soluble vitamins, and maintaining essential hormonal functions, specifically menstrual health [17, 18].

Despite these clear guidelines, research indicates that professional female athletes frequently fail to meet their energy and macronutrient requirements. Studies in various competitive leagues have reported that players often exhibit low energy availability and insufficient intake of carbohydrates and lipids [19, 20]. This nutritional inadequacy is a significant concern because it can impact body composition negatively, leading to the loss of lean mass or the retention of fat mass due to metabolic adaptation, thereby hindering performance and increasing health risks [21].

In the Latin American context, and specifically in Peru, there is a paucity of data describing the morphological characteristics of professional female soccer players. The average anthropometric profile of the Peruvian female population differs from European standards, characterized by shorter stature and a tendency towards an endomorphic somatotype [22, 23]. Consequently, applying international reference standards to local players may be inappropriate for talent identification or nutritional interventions. To date, no study has examined how nutritional adequacy correlates with position-specific anthropometric profiles in Peruvian professional soccer. Therefore, the aim of this study was to determine and compare anthropometric profile and somatotype characteristics across playing positions in professional female soccer players, and to analyze their relationship with nutritional adequacy.

Methods

Study design and participants

A descriptive, cross-sectional study was conducted during the 2025 competitive season. The study population consisted of 43 professional female soccer players belonging to two First Division clubs in Trujillo, Peru. Census sampling was employed to include the entire eligible population.

Inclusion criteria were: (i) having a valid professional contract for the 2025 season; (ii) age between 18 and 35 years; (iii) participation in at least 50% of official and friendly matches; and (iv) accumulating a minimum of 10 h of training per week. Players were excluded if they had sustained injuries preventing regular training in the two weeks prior to data collection, presented diagnosed metabolic or endocrine disorders (e.g., diabetes, thyroid disorders, PCOS), or had a history of disciplinary sanctions related to doping. The study was conducted in accordance with the Declaration of Helsinki [32] and approved by the Institutional Ethics Committee of Universidad Científica del Sur (Approval No. 132-DACND-DAFCS-U.CIENTIFICA-2025). Authorization was obtained from the sports management of both clubs. All participants provided written informed consent prior to data collection, and data anonymity was strictly preserved.

Anthropometric measurements

Anthropometric variables were measured following the International Society for the Advancement of Kinanthropometry (ISAK) guidelines [24]. All measurements were performed by ISAK-certified evaluators in a private room, with participants wearing light clothing and in a fasting state of at least two hours. To ensure data quality, the Technical Error of Measurement (TEM) was maintained within acceptable limits (< 5% for skinfolds and < 1% for other measures) [25].

Body mass was measured using a digital scale (Omron, precision ± 0.1 kg), and standing height was measured using a stadiometer (Seca 213, precision ± 0.1 cm) with the head in the Frankfurt plane. The anthropometric profile included 25 variables: skinfolds (triceps, subscapular, supraspinale, abdominal, medial calf, and front thigh) measured with a constant-pressure caliper (Slim Guide, precision ± 2 mm); girths (head, arm relaxed/flexed, forearm, chest, waist, gluteal, mid-thigh, and calf) measured with a steel tape (Ava Nutri, precision ± 0.1 cm); and bone breadths (humerus and femur biepicondylar) measured with a small sliding caliper (Vitruvian, precision ± 0.1 cm).

Somatotype was calculated using the Heath-Carter method to determine endomorphy, mesomorphy, and ectomorphy components [26]. Body composition was estimated using the Kerr five-component fractionation method (adipose, muscle, bone, residual, and skin masses), which is considered robust for athletic populations [27].

Nutritional assessment dietary intake

Habitual dietary intake was assessed using a 24-hour dietary recall administered on three non-consecutive days (two training days and one rest day) to account for daily variability. Participants were required to detail all foods, beverages, and supplements consumed during each 24-hour period. To enhance the accuracy of portion size estimation and minimize recall bias, visual aids and photographic atlases from the “Auxiliary Tables for the Formulation and Evaluation of Dietary Regimens” (TAFERA) of the Peruvian Ministry of Health were utilized [28]. The collected nutritional data were processed to quantify Total Energy Intake (TEI) and macronutrient distribution (proteins, carbohydrates, and lipids).

Energy expenditure

Resting Metabolic Rate (RMR) was estimated using the Cunningham equation, which accounts for Fat-Free Mass (FFM) and is widely validated for athletic populations (RMR = 500 + 22×FFM) [29]. Total Energy Expenditure (TEE) was calculated individually for each of the three assessment days (two training days and one rest day) using the factorial method. Daily physical activity energy expenditure was estimated using Metabolic Equivalents (METs) from the Compendium of Physical Activities [30], based on the specific duration and intensity of the activities performed on each specific day. Finally, a weighted mean TEE was computed to represent the habitual energy requirement, ensuring temporal consistency with the dietary intake assessment.

Nutritional adequacy

Nutritional adequacy was calculated as the ratio between the weighted mean intake and the estimated requirement for energy, proteins, carbohydrates, and lipids, expressed as a percentage (Adequacy=[Intake/Requirement]×100). For energy, Total Energy Intake (TEI) was compared against Total Energy Expenditure (TEE). For macronutrients, intake was compared against the specific recommendations previously described. Based on established protocols, adequacy levels were classified as: Insufficient (< 90%), Optimal (90–110%), or Excessive (> 110%) [31].

Statistical analysis

Statistical analyses were performed using SPSS software, version 30.0 (IBM Corp., Armonk, NY, USA). Data normality was assessed using the Shapiro-Wilk test. Descriptive statistics are presented as mean ± standard deviation (SD) for quantitative variables and frequencies (percentages) for categorical data.

Differences in anthropometric and body composition variables between playing positions were evaluated using the Kruskal-Wallis H test. Effect sizes were estimated using Epsilon-squared (ε²). Pairwise comparisons were conducted using the Mann-Whitney U test with Bonferroni correction.

Associations between nutritional adequacy and playing positions were analyzed using the Chi-square test (χ²), with Cramer’s V (V) calculated for effect size estimation. Correlations between nutritional adequacy and body composition were assessed using Kendall’s Tau-b (Tb) coefficients.

Statistical significance was set at p < 0.05. Statistical significance was set at p < 0.05. However, given the small sample size in the goalkeeper subgroup (n = 4) and low cell counts in contingency tables, Chi-square results should be interpreted with caution, serving primarily as descriptive indicators. Furthermore, to maintain methodological rigor, the goalkeeper subgroup was entirely excluded from inferential correlational analyses (Kendall’s Tau and p-values) due to the extreme sensitivity of correlation coefficients to individual variability in small samples. Instead, findings regarding the relationship between nutritional adecuacy and body composition for this specific position are treated purely as a descriptive case series.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki [32] and approved by the Institutional Ethics Committee of Universidad Científica del Sur (Approval No. 132-DACND-DAFCS-U.CIENTIFICA-2025). Authorization was obtained from the sports management of both clubs. All participants provided written informed consent prior to data collection, and data anonymity was strictly preserved.

Results

Anthropometric characteristics

The descriptive analysis of anthropometric profiles (Table 1) revealed statistically significant differences associated with playing positions, primarily distinguishing goalkeepers from outfield players. The Kruskal-Wallis test indicated significant variations across positions for body mass (p = 0.011, ε² = 0.26), height (p = 0.015), and Body Mass Index (p = 0.031). Post-hoc comparisons confirmed that goalkeepers exhibited significantly higher values for these variables compared to forwards, midfielders, and defenders, who showed no significant differences among themselves.

Table 1.

Descriptive anthropometric characteristics of professional female soccer players by playing position

Variable	Forwards		Midfielders		Defenders		Goalkeepers		comparisons
	Mean	SD	Mean	SD	Mean	SD	Mean	SD	p-value†	ES
Age (years)	25.80	6.43	24.21	5.59	26.19	4.93	30.02	2.91	0.256	0.10
Body Mass (kg)	57.18	8.24a	56.82	6.25a	58.10	3.90a	79.95	3.34b	0.011*	0.26
Height (m)	1.59	0.07ab	1.58	0.03a	1.60	0.04a	1.70	0.04b	0.015*	0.25
BMI (kg/m²)	22.59	3.55ab	22.83	2.36a	22.72	1.76a	27.63	1.96b	0.031*	0.21
Adipose Mass (kg)	12.70	3.10a	12.60	2.20a	12.10	1.90a	18.60	2.50b	0.017*	0.24
Muscle Mass (kg)	22.80	2.80a	22.50	2.10a	24.00	1.80a	33.10	2.20b	0.014*	0.25
Bone Mass (kg)	6.80	0.90	6.30	0.70	6.40	0.60	9.30	0.80	0.094	0.15
Residual Mass (kg)	10.10	1.20a	9.90	0.80ab	10.10	0.70a	12.40	1.10b	0.009*	0.27
Skin Mass (kg)	4.80	0.50a	5.20	0.40ab	5.50	0.30b	6.40	0.40ab	0.009*	0.27
Endomorphy	4.18	1.25	3.68	0.63	3.61	0.72	4.33	0.17	0.152	0.13
Mesomorphy	4.47	0.94	3.77	0.62	4.12	0.52	4.13	0.53	0.755	0.03
Ectomorphy	1.53	0.74	1.67	0.67	1.49	0.45	0.98	0.45	0.474	0.06

SD Standard Deviation, BMI Body Mass Index, ES Effect Size (Epsilon-squared ϵ²). Body composition was estimated using the Kerr five-component method; Somatotype was evaluated using the Heath-Carter method. ^†Statistical comparisons were performed using the Kruskal-Wallis H test. Different superscripts (^{a, b}) within the same row indicate significant differences between groups based on pairwise Mann-Whitney U comparisons with Bonferroni correction (p < 0.05). *Denotes statistical significance

Regarding body composition estimated by the Kerr method, significant differences were observed in absolute muscle mass (p = 0.014, ε² = 0.25) and adipose mass (p = 0.017, ε² = 0.24). Goalkeepers displayed significantly higher absolute muscle (33.10 ± 2.20 kg) and adipose mass (18.60 ± 2.50 kg) compared to all outfield positions. While forwards presented the lowest mean values for body mass and adipose mass numerically, these differences were not statistically significant compared to midfielders or defenders. Furthermore, no significant differences were found for somatotype components (endomorphy, mesomorphy, ectomorphy) across positions (p > 0.05), indicating a relatively homogeneous somatotypic profile across the squad despite the differences in body size.

Nutritional adequacy

The assessment of nutritional intake adequacy revealed widespread dietary imbalances across the sample, with distinct distribution patterns illustrated in Fig. 1. Statistical analysis confirmed that these variations were significantly associated with playing position (Table 2). A highly significant association was found for protein intake (p < 0.001), with a very large effect size (Cramer’s V = 0.58). Specifically, 100% of goalkeepers exhibited insufficient protein intake, whereas a prevalence of excessive intake was observed in midfielders (90.9%) and defenders (87.5%). Similarly, energy intake differed significantly by position (p = 0.002), with a large effect size (V = 0.49); goalkeepers showed the highest rate of insufficiency (75.0%). Carbohydrate intake also showed a significant association (p = 0.010, V = 0.39), characterized by a trend towards excess in outfield players (reaching 100% in midfielders). Conversely, no significant association was found for lipid adequacy (p = 0.827), with insufficiency being the dominant pattern across the entire sample (74.4%).

Fig. 1.

Nutritional adequacy percentages for energy and macronutrients stratified by playing position. The box plots illustrate the distribution of nutritional adequacy. The central horizontal line represents the median, while the ‘X’ indicates the mean. Whiskers extend to 1.5 times the interquartile range. Individual dots represent outliers. Note the distinct trend of insufficiency in goalkeepers versus excessive protein/carbohydrate intake in outfield players, with generalized lipid insufficiency across all positions

Table 2.

Frequency of nutritional adequacy levels stratified by playing position and statistical association analysis

Nutrient	Adequacy Level	Forwards (n = 12)		Midfielders (n = 11)		Defenders (n = 16)		Goalkeepers (n = 4)		Total (n = 43)		Statistics
		n	%	n	%	n	%	n	%	n	%	p-value	Cramer´s V
Energy	Insufficient	0	0.0	0	0.0	0	0.0	3	75.0	3	7.0	0.002*	0.49
	Optimal	6	50.0	1	9.1	10	62.5	1	25.0	18	41.9
	Excessive	6	50.0	10	90.9	6	37.5	0	0.0	22	51.2
Proteins	Insufficient	0	0.0	0	0.0	0	0.0	4	100.0	4	9.3	< 0.001*	0.71
	Optimal	4	33.3	1	9.1	2	12.5	0	0.0	7	16.3
	Excessive	8	66.7	10	90.9	14	87.5	0	0.0	32	74.4
Carbohydrates	Insufficient	0	0.0	0	0.0	0	0.0	2	50.0	2	4.7	0.003*	0.48
	Optimal	3	25.0	0	0.0	1	6.3	2	50.0	6	14.0
	Excessive	9	75.0	11	100.0	15	93.8	0	0.0	35	81.4
Lipids	Insufficient	8	66.7	7	63.6	13	81.3	4	100.0	32	74.4	0.827	0.18
	Optimal	3	25.0	3	27.3	3	18.8	0	0.0	9	20.9
	Excessive	1	8.3	1	9.1	0	0.0	0	0.0	2	4.7

Data presented as frequency (n) and percentage (%). Statistical analysis performed using Chi-square test of independence. Effect size calculated using Cramer’s V (V) interpreted as: 0.10 small, 0.30 medium, 0.50 large. * Denotes statistical significance (p < 0.05)

Global association analysis

Correlation analysis of the total population (n = 43) revealed robust and highly significant associations between nutritional adequacy and body composition (Table 3). Protein adequacy demonstrated a strong inverse correlation with adipose mass (Tb=-0.60, p < 0.001) and a strong negative correlation with muscle mass (Tb=-0.53, p = 0.003). Similarly, lipid adequacy displayed a strong negative correlation with muscle mass (Tb=-0.52, p < 0.001). Unlike proteins and lipids, energy intake did not show a significant correlation with adipose mass (p = 0.205). but maintained a significant negative association with muscle mass (Tb=-0.52, p < 0.001).

Table 3.

Relationship between nutritional adequacy and body compositions in the total sample

Nutritional Adequacy	Body Compositions	p	Kendall´s Tau b
Calories	Adipose Mass	0.205	-0.20
	Muscle Mass	< 0.001*	-0.52
Proteins	Adipose Mass	< 0.001*	-0.60
	Muscle Mass	0.003*	-0.53
	Bone Mass	0.041*	-0.37
Carbohydrates	Adipose Mass	0.010*	-0.35
	Muscle Mass	0.040*	-0.34
Lipids	Muscle Mass	< 0.001*	-0.52

Correlations determined by Kendall’s Tau-b coefficient. Interpretation of Tb: <0.10 (trivial), 0.10–0.30 (small), 0.30–0.50 (moderate), > 0.50 (large). * Denotes statistical significance (p < 0.05)

Association analysis stratified by playing position

The analysis of the relationship between nutritional adequacy and body composition markers stratified by playing position is detailed in Additional file 1. Consistent with the reduced sample sizes within subgroups (n = 4 to n = 16), statistical significance was not reached for any association across positions (p > 0.05). However, strong correlation coefficients were observed in specific groups, suggesting potential trends that were likely masked by limited statistical power. For instance, forwards exhibited a strong negative correlation between protein adequacy and muscle mass (Tc = − 0.69,p = 0.060) and adipose mass (Tc = − 0.47,p = 0.235). Similarly, defenders showed a moderate-to-strong negative correlation between protein adequacy and adipose mass (Tb = − 0.49,p = 0.051). Crucially, inferential statistics (Kendall’s Tau and p-values) were completely omitted for the goalkeeper subgroup (n = 4) to prevent mathematically unreliable conclusions; their data are presented solely as a descriptive case series.

Somatotype analysis

Finally, the relationship between nutritional adequacy and somatotype components (Endomorphy, Mesomorphy, and Ectomorphy) was evaluated. No statistically significant associations were found in either the analysis stratified by playing position or the global analysis of the total sample (p > 0.05 for all comparisons). Detailed statistical results are provided in Additional file 2.

Discussion

Guided by the objective to determine and compare anthropometric profile and somatotype characteristics across playing positions in professional female soccer players, and to analyze their relationship with nutritional adequacy, this study reveals a complex interaction between morphological specialization and nutritional strategies. While anthropometric profiles exhibited clear differentiation based on playing position, consistent with the functional demands of the sport, nutritional intake patterns appeared largely homogeneous and unbalanced across the squad. A critical observation was the robust statistical association found in the global population between high nutritional adequacy and favorable body composition (lower adiposity and higher muscle mass), a relationship that was statistically attenuated when stratified by specific playing positions due to sample size limitations.

Regarding morphological characteristics, the data confirm that goalkeepers possess a distinct phenotype characterized by significantly greater height, body mass, and absolute muscle and adipose mass compared to outfield players. This aligns with recent international evidence, such as the findings by Petri et al. [8] and Strauss et al. [7], which describe goalkeepers as the tallest and heaviest players, a morphological adaptation necessary to maximize aerial reach and blocking presence in the goal area. However, a quantitative comparison with elite international cohorts reveals notable differences. For instance, while the height of the goalkeepers in this study is comparable to that of Chilean national team players (1.72 m) reported by Hernández-Mosqueira et al. [33], the sample exhibited a significantly higher body mass, approximately 13 kg heavier than the 66.7 kg average reported in the Chilean study. This suggests that while the structural requirement of height is met, there may be an excess of body mass not solely attributable to muscle tissue. Conversely, the outfield players presented an average height of approximately 1.59 m and weight of 57 kg, which mirrors almost exactly the profile of other South American professional cohorts as described by Hernandez-Martinez et al. [33], yet remains notably lower than elite European players who average between 1.65 and 1.68 m (Ruiz et al., 9). This reinforces the existence of a specific “regional phenotype” characterized by a lower center of gravity, which may offer biomechanical advantages in rotational agility and balance to compensate for the lack of vertical stature in match play, as suggested by biomechanical principles in soccer physiology [6].

Furthermore, the findings underscore the limitations of relying solely on Body Mass Index (BMI) for athletic screening. While traditional metrics might classify players with substantial muscular development as “overweight”, a trend frequently observed in power dependent positions like forwards, the use of the Kerr five component method allowed for a precise discrimination between adipose and muscle tissue [27]. This distinction is supported by the systematic review of Sebastia-Rico et al. [5], which emphasizes that BMI fails to capture functional body composition in elite populations where skeletal muscle mass contributes disproportionately to total weight [34]. Consequently, specific players in the studied cohort presented elevated BMI values yet maintained low adipose mass, indicating a favorable lean to fat ratio that would be misclassified by simpler anthropometric indices.

The nutritional analysis uncovered a widespread pattern of imbalance, characterized by excessive protein intake and insufficient lipid consumption. Paradoxically, the global correlation analysis revealed that players with higher protein adequacy exhibited significantly lower adipose mass (Tb = − 0.60, p < 0.001). From a bioenergetic perspective, this inverse relationship may be explained by the high Thermic Effect of Food associated with protein metabolism [16]. However, a compelling finding from this research challenges the misconception that higher protein intake automatically translates to greater muscle mass accretion. While outfield players exhibited excessive protein consumption (exceeding international recommendations in > 87% of cases), they did not display superior absolute muscle mass compared to goalkeepers, who conversely had 100% insufficient protein intake yet the highest muscle mass values. This aligns with recent evidence by Baranauskas et al. [12], who observed that exceeding protein thresholds does not yield additional anabolic benefits if energy balance or training stimuli are not optimized. Furthermore, this “muscle protein paradox” suggests that protein intake beyond the saturation point may be oxidized for energy rather than used for hypertrophy, particularly when carbohydrate availability is high [17]. Thus, the superior muscle mass in goalkeepers appears to be driven more by their specific resistance training demands and total body size rather than dietary protein quantity per se. Moreover, the global correlation analysis revealed inverse relationships between nutritional adequacy and muscle mass (Table 3). This finding must be interpreted with caution due to the presence of ‘ratio bias’ or mathematical coupling. Since the nutritional requirement (denominator) is directly proportional to fat-free mass, players with higher muscle mass (e.g., goalkeepers) inherently have higher calculated needs. Consequently, even with high absolute intake, they are statistically more likely to fall into the ‘insufficient’ category compared to smaller players. Therefore, the observed strong inverse correlations (e.g., Protein vs. Muscle Mass, Tb = − 0.60) are largely structurally induced by the calculation method rather than implying that adequate nutrition hinders hypertrophy. This highlights the difficulty larger athletes face in meeting their elevated metabolic demands relative to smaller counterparts.

Conversely, the generalized insufficiency in lipid intake (83.7% of the sample) was strongly associated with lower muscle mass (Tb = − 0.52, p < 0.001). This finding highlights a critical physiological concern documented by Slater et al. [17], as dietary lipids are essential substrates for the synthesis of cholesterol and anabolic hormones. In female athletes, chronic low lipid availability can suppress the hypothalamic pituitary gonadal axis [18], creating a subclinical environment that may compromise muscle repair and hypertrophy. These data suggest that the restriction of dietary fats, likely adopted as an empirical weight control strategy, might be inducing a counterproductive state, potentially limiting the capacity of players to accrue or maintain muscle mass despite high protein intake.

A key methodological insight addresses the divergence between the stratified and global analyses. When data were segmented by playing position, statistical significance diminished (p > 0.05) for most variables (see Additional file 1). This absence of positional correlation does not necessarily imply different physiological responses among positions, but rather reflects a Type II statistical error driven by reduced statistical power in small subgroups, particularly in goalkeepers. However, when analyzed as a total population, robust physiological associations became evident. This indicates that metabolic responses to nutrient intake appear consistent across the cohort, meaning that regardless of tactical role, the physiological demand requires sufficient energy and lipids to sustain muscle mass, and high protein availability to minimize adiposity [15]. Therefore, the global analysis benefits from higher statistical power to detect associations that remain obscured in smaller stratified subgroups, suggesting that nutritional status is a relevant correlate of body composition quality in this population.

Finally, the relationship between nutritional adequacy and somatotype components was evaluated. No statistically significant associations were found in either the stratified or global analysis. This suggests that while nutritional adequacy was significantly associated with modifiable tissues such as muscle and adipose mass, it was not related to the somatotypic profile in this cross sectional assessment, likely because somatotype represents a more stable phenotypic trait compared to body composition components [10].

A substantial limitation of this study is the statistical power associated with the small sample size, particularly in the goalkeeper subgroup (n = 4). Consequently, all inferential correlational statistics for this position were omitted, requiring these position-specific findings to be interpreted strictly as a descriptive case series and preliminary observations. Furthermore, stratified analyses for outfield players may be underpowered; thus, non-significant results should not be interpreted as definitive evidence of no association. Additionally, the cross-sectional design strictly precludes causal inferences regarding the impact of diet on morphological changes. Methodologically, self-reported dietary data is subject to potential underreporting. Moreover, the application of fixed adequacy thresholds (90–110%) was employed to provide a standardized definition of habitual sufficiency, although this aggregates daily variations inherent to training periodization. Also, we did not specifically quantify internal training load (e.g., RPE) beyond weekly duration, limiting the isolation of training stimulus versus nutrition effects. Finally, we did not control for menstrual cycle phase or hydration status at the time of measurement, which introduces potential transient variability in body composition.

Future research perspectives

Based on the findings and limitations of the current work, future investigations should aim to overcome the constraints of cross-sectional designs by adopting longitudinal, multicenter approaches with larger sample sizes and appropriate control groups to establish causal links between nutrition and morphological changes. It is imperative to integrate performance metrics, encompassing motor and functional skills, anaerobic-glycolytic capacities, strength assessments, and external load monitoring via GPS, to determine how the ‘regional phenotype’ described here translates to match-play efficiency. Furthermore, considering the complex interaction between training stress and nutrient intake, future studies should incorporate physiological biomarkers, including immune system markers, hormonal status, and energy stores such as glycogen, to provide a holistic view of the player’s health status, fatigue, and adaptation processes. Establishing these connections will be crucial for standardizing nutritional guidelines specific to the Latin American female soccer context.

Conclusions

No statistically significant associations were found between nutritional adequacy and body composition when stratified by playing position among outfielders, suggesting that dietary habits are largely homogeneous across the squad. However, global analysis of the overall sample revealed that caloric adequacy was inversely associated with muscle mass (p < 0.001), indicating that players with higher muscle mass faced greater difficulty in meeting their estimated energy requirements. Similarly, macronutrient adequacy (proteins, lipids, and carbohydrates) showed inverse relationships with muscle mass, largely driven by the mathematical coupling of requirements to body size. Furthermore, the somatotype (meso-endomorphic) appeared stable and unrelated to current nutritional intake. Ultimately, these findings highlight the urgent need for individualized nutritional strategies that account for the specific metabolic demands of the South American female player phenotype, serving as a critical baseline for future interventionist research. Practically, these results provide significant guidelines for tailoring nutritional structures and supplementation protocols within the training and competitive processes of professional female soccer players in this developing context.

Abbreviations

BMI

Body Mass Index

ES

Effect Size

FFM

Fat-Free Mass

ISAK

International Society for the Advancement of Kinanthropometry; METs: Metabolic Equivalents

mTORC1

Mammalian Target of Rapamycin Complex 1

PCOS

Polycystic Ovary Syndrome

RMR

Resting Metabolic Rate

SD

Standard Deviation

TAFERA

Tablas Auxiliares para la Formulación y Evaluación de Regímenes Alimentarios (Auxiliary Tables for the Formulation and Evaluation of Food Regimens)

TEE

Total Energy Expenditure

TEF

Thermic Effect of Food

TEI

Total Energy Intake

TEM

Technical Error of Measurement

Authors’ contributions

LAKL, NLC and BSMG conceived and designed the study. LAKL and NLC performed data collection. LAKL and BSMG performed the statistical analysis and data interpretation. LAKL, NLC, BSMG, NECP and RA drafted the manuscript and provided critical revision for important intellectual content. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki [32] and approved by the Institutional Ethics Committee of Universidad Científica del Sur (Approval No. 132-DACND-DAFCS-U.CIENTIFICA-2025). Authorization was obtained from the sports management of both clubs. All participants provided written informed consent prior to data collection, and data anonymity was strictly preserved.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.