Physical Fitness, Body Composition, Somatotype, and Phantom Strategy (Z-Score) in U13, U15, and U17 Female Soccer Players: A Comparative and Correlational Study

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you very much for the opportunity to review the scientific article titled “Physical Fitness, Body Composition, Somatotype, and Phantom Strategy (Z-Score) in U13, U15, and U17 Female Soccer Players: A Comparative and Correlational Study”. Below are my comments:

Abstract:

1. On the review report form page, the abstract contains truncated results and lacks conclusions. It seems that the full abstract was not copied during the article registration process.
2. Line 16 – The authors state that physical fitness and body composition influence performance. I believe this is a strong statement that implies no further research is needed on this relationship. I suggest using phrasing such as “it is suggested” or “many studies indicate that physical fitness and body composition may influence individual and team performance.” It would also be beneficial to include a sentence highlighting the research gap that motivates the study.
3. Line 18 – I would recommend changing “correlation” to “relationship.” The term “correlation” refers specifically to a statistical method used to assess dependence.
4. Line 26 – I understand that the authors performed a single 20-meter sprint and measured additional splits at 5, 10, and 15 meters. If so, the abstract should mention that a 20-meter sprint was performed, while the methodology section of the article can describe the additional split measurements.

Introduction:

1. Line 43 – Which profile? This thought should be clarified.
2. Since the study concerns the assessment of physical fitness, body composition, and somatotype in female soccer players by age category, it would be useful to include information about the physical development of women at the corresponding ages. This information would help highlight the relevance of the study.

Materials and Methods:

1. Line 134 – There seems to be an error in the sentence: “Body mass was assessed using the OMROM scale model HBF-514C (Kyoto, Japan), with an accuracy of 0.1 cm.” Body mass was likely measured with an accuracy of 0.1 kg.
2. Line 171 – It should be specified how long participants had to maintain the squat position before performing the jump.
3. How many attempts of SJ, CMJ, and Abalakov jumps did participants perform? It is important to report this, as well as whether the highest or average value was used. Additionally, the rest period between jumps should be included, as it may affect performance.
4. Line 181 – Here the third jump is called “Abalakov,” whereas in the abstract (line 24) and Equipment section (line 138) it is called “countermovement jump with arms.” Please standardize the name of this jump throughout the manuscript.
5. Line 186 – In the section title “Speed (5, 10, 15 y 20 m)” the authors used the Spanish conjunction “y.” Please correct it to English.
6. Section “Speed (5, 10, 15, and 20 m)” – It is missing whether participants started from a low or high start. Furthermore, it is unclear whether the start was triggered by an auditory or visual signal, or whether participants started at their own signal when ready.
7. It is unclear whether the speed assessment was conducted outdoors or indoors, and on what type of surface.
8. In the description of the 5-0-5 and 5+5 Change of Direction Tests, the authors included a description in Spanish. Moreover, after translation, the methodology of performing the test is not described.
9. In the RAST test description, there is no information on whether the test was performed on natural or artificial turf. If conducted outdoors, weather conditions should also be reported, as wet turf or wind conditions may significantly affect sprint times.

In summary, a more detailed description of the trials is required.

1. Line 237 – The authors state that three measurements were taken and averaged during anthropometry, but in line 154 they wrote that two measurements were performed. Please clarify and correct the number of measurements.
2. It would be useful to indicate which variables are normally distributed.

Results:

1. In Tables 1, 2, and 3, different symbols (*, &) and letters are used, but the table legends do not explain their meaning. Please clarify.
2. Table 1 lacks units for the measured variables.
3. The text mentions effect sizes, but these are not reported in the tables.
4. In Table 3, what do the values in parentheses represent? Min-max, interquartile range? Please clarify.
5. Table 3 is missing units for some variables (e.g., Partial 1-5 m, 5-10 m, 10-15 m, Total 15 m, Contact time, 10 m, COD Deficit, Fatigue index).
6. In the methods, the authors stated that a 20-meter sprint was used, but Table 3 does not include 20-meter sprint time.
7. In Tables 4 and 5, some values are reported with one decimal place and some with two. Please standardize the format.

Discussion:

1. One of the main objectives of the study was to assess the relationship between physical fitness, body composition, and somatotype in young female soccer players. However, the discussion references only three studies analyzing this relationship (lines 379–385, 388–392, and 401–404).
2. Line 409 – Comparing results from volleyball players and drawing far-reaching conclusions that “anthropometric and somatotype profiles are solid predictors of performance and success” is misleading. The specific demands of volleyball and the importance of anthropometric traits differ from football.
3. Lines 424–432 – The discussion on the role of nutrition in shaping body composition and performance deviates too much from the main focus of the study.

In conclusion, I recommend including more references in the discussion that specifically focus on the relationship between physical fitness, body composition, and somatotype in young female soccer players.

Comments on the Quality of English Language

In the description of the 5-0-5 and 5+5 Change of Direction Tests, the authors included a description in Spanish. 

Author Response

Letter to reviewer 1

Dear Reviewer,

Thank you for reviewing our manuscript. As a research group we value your effort and input.

We have followed your suggestions point by point to improve the manuscript quality, according to our possibilities. The changes have been made in the full text using the red color so that you can see them.

Thanks for your time. Once again, we thank you for your valuable contributions, which have helped to strengthen the document.

 

Comments 1. On the review report form page, the abstract contains truncated results and lacks conclusions. It seems that the full abstract was not copied during the article registration process.

Response 1: The reviewer's comments were accepted.               

 

Comments 2. Line 16 – The authors state that physical fitness and body composition influence performance. I believe this is a strong statement that implies no further research is needed on this relationship. I suggest using phrasing such as “it is suggested” or “many studies indicate that physical fitness and body composition may influence individual and team performance.” It would also be beneficial to include a sentence highlighting the research gap that motivates the study.

Response 2: The reviewer's comments were accepted.

Some studies have suggested that physical fitness and body composition may influence individual and collective performance. However, it is necessary to be able to define the relationships between these variables in soccer players of different ages.

 

Comments 3. Line 18 – I would recommend changing “correlation” to “relationship.” The term “correlation” refers specifically to a statistical method used to assess dependence.

Response 3: The reviewer's comments were accepted.

 

Comments 4. Line 26 – I understand that the authors performed a single 20-meter sprint and measured additional splits at 5, 10, and 15 meters. If so, the abstract should mention that a 20-meter sprint was performed, while the methodology section of the article can describe the additional split measurements.

Response 4: The reviewer's comments were accepted.

 

Comments 5. Line 43 – Which profile? This thought should be clarified.

Response 5: The reviewer's comments were accepted.

The profile of female soccer players defined based on the relationship between physical fitness and body composition has become a topic of interest [1], experiencing steady growth in scientific literature [2].

 

Comments 6. Since the study concerns the assessment of physical fitness, body composition, and somatotype in female soccer players by age category, it would be useful to include information about the physical development of women at the corresponding ages. This information would help highlight the relevance of the study.

Response 6: The reviewer's comments were accepted.

Thus, a systematic review conducted by Malina et al. [8] on growth and maturity in soccer players reveals that the main differences between ages are established on average up to age 14 and change from there until age 18, while weights change between ages 9 and 18. This is relevant because these indicators suggest selection processes for players with superior height and body mass characteristics during adolescence. Another study that evaluated body composition and physical fitness in 12-year-old Icelandic players indicated that research on these variables is needed to define maturation patterns and design training proposals that are increasingly tailored to each context [9]. According to Petri et al. [10], in the reference study to define the characteristics of female soccer players, soccer players tend to be balanced mesomorphs, suggesting a possible morphology associated with the specific demands of the sport.

 

Comments 7. Line 134 – There seems to be an error in the sentence: “Body mass was assessed using the OMROM scale model HBF-514C (Kyoto, Japan), with an accuracy of 0.1 cm.” Body mass was likely measured with an accuracy of 0.1 kg.

Response 7: The reviewer's comments were accepted.              

Body mass was assessed using the OMROM scale model HBF-514C (Kyoto, Japan), with an accuracy of 0.1 kg.

 

Comments 8. Line 171 – It should be specified how long participants had to maintain the squat position before performing the jump.

Response 8: The reviewer's comments were accepted. The changes were made in the description of test.

The players were in a squatting position for 5 seconds before jumping.

 

Comments 9. How many attempts of SJ, CMJ, and Abalakov jumps did participants perform? It is important to report this, as well as whether the highest or average value was used. Additionally, the rest period between jumps should be included, as it may affect performance.

Response 9: The reviewer's comments were accepted.

Two jumps were recorded for each event per participant, with the best score being recorded.

 

Comments 10. Line 181 – Here the third jump is called “Abalakov,” whereas in the abstract (line 24) and Equipment section (line 138) it is called “countermovement jump with arms.” Please standardize the name of this jump throughout the manuscript.

Response 10: The reviewer's comments were accepted. The adjustment was made throughout the document.

 

Comments 11. Line 186 – In the section title “Speed (5, 10, 15 y 20 m)” the authors used the Spanish conjunction “y.” Please correct it to English.

Response 11: The reviewer's comments were accepted.

 

Comments 12. Section “Speed (5, 10, 15, and 20 m)” – It is missing whether participants started from a low or high start. Furthermore, it is unclear whether the start was triggered by an auditory or visual signal, or whether participants started at their own signal when ready.

Response 12: The reviewer's comments were accepted.

The speed was recorded from a high position and with an acoustic signal.

 

Comments 13. It is unclear whether the speed assessment was conducted outdoors or indoors, and on what type of surface.

Response 13: The reviewer's comments were accepted.

All field tests were conducted outdoors on the same synthetic field and by the same three evaluators.

 

Comments 14. In the description of the 5-0-5 and 5+5 Change of Direction Tests, the authors included a description in Spanish. Moreover, after translation, the methodology of performing the test is not described.

Response 14: The reviewer's comments were accepted.

The 5-0-5 test consists of a 10-meter sprint, an 180-degree turn, and a 5-meter sprint back through the start/finish gate. The 5+5 test is a modified version in which the athlete runs 5 meters, turns 180 degrees, and then runs another 5 meters back.

 

Comments 15. In the RAST test description, there is no information on whether the test was performed on natural or artificial turf. If conducted outdoors, weather conditions should also be reported, as wet turf or wind conditions may significantly affect sprint times.

Response 15: The reviewer's comments were accepted.  The changes were made in the description of test.

The field tests were conducted over several sessions, always at the same time (4:00 to 6:00 p.m.), under similar environmental conditions (average temperature: 13.1 °C; humidity: 77–83%), and without fasting conditions.

 

Comments 16. Line 237 – The authors state that three measurements were taken and averaged during anthropometry, but in line 154 they wrote that two measurements were performed. Please clarify and correct the number of measurements.

It would be useful to indicate which variables are normally distributed.

Response 16: The reviewer's comments were accepted.

Dear Reviewer,
We appreciate your valuable feedback. We have accepted your suggestions and, in the tables, we have specified the type of test used (parametric or non-parametric), which indicates whether the data are normally distributed or not.

 

Comments 17. Results.

• In Tables 1, 2, and 3, different symbols (*, &) and letters are used, but the table legends do not explain their meaning. Please clarify.

We have made the adjustments according to the reviewer’s suggestions.

• Table 1 lacks units for the measured variables.

We have made the adjustments according to the reviewer’s suggestions.

• The text mentions effect sizes, but these are not reported in the tables.

We appreciate your observation. In the manuscript, we only reported the most relevant effect sizes in the text, as including all of them in the tables would create redundancy and make the results more difficult to read.

• In Table 3, what do the values in parentheses represent? Min-max, interquartile range? Please clarify.

In the title of Table 3, we specified the median, as well as the minimum and maximum values in parentheses

• Table 3 is missing units for some variables (e.g., Partial 1-5 m, 5-10 m, 10-15 m, Total 15 m, Contact time, 10 m, COD Deficit, Fatigue index).

We have made the adjustments according to the reviewer’s suggestions.

• In the methods, the authors stated that a 20-meter sprint was used, but Table 3 does not include 20-meter sprint time.

We could not find a specific result related to this suggestion in the analyses performed. We would appreciate it if you could specify which section or variable you are referring to, so we can review it again and make the necessary adjustments.

• In Tables 4 and 5, some values are reported with one decimal place and some with two. Please standardize the format.

• We have made the adjustments according to the reviewer’s suggestions.

Response 17: The reviewer's comments were accepted.

                                                                                                    

Comments 18. Discussion

• One of the main objectives of the study was to assess the relationship between physical fitness, body composition, and somatotype in young female soccer players. However, the discussion references only three studies analyzing this relationship (lines 379–385, 388–392, and 401–404).
• Line 409 – Comparing results from volleyball players and drawing far-reaching conclusions that “anthropometric and somatotype profiles are solid predictors of performance and success” is misleading. The specific demands of volleyball and the importance of anthropometric traits differ from football.

Other research proposals in semi-professional women's soccer (18-32 years old) showed that there are relationships between body composition variables such as mass and physical performance (p < 0.05) [54], where players tend to be mesomorphic [55], highlighting the importance of developing studies specific to each context and age group, given that there are currently no clear references regarding anthropometric profiles [56]. In this regard, it has been reported that fat mass is inversely related to the physical performance of players [54]. These values contrast with those of the present research in the U13 and U17 categories, which showed a lower percentage of relative muscle mass. This evidence shows how competitive level and age influence the morphofunctional specialization of each discipline and supports the need to longitudinally monitor body composition to adjust strength and conditioning programs.

Sánchez-Abselam, O.; González-Fernández, F.T.; Figueiredo, A.; Castillo-Rodríguez, A.; Onetti-Onetti, W. Effect of the role, playing position and the body characteristics on physical performance in female soccer players. Heliyon. 2024, 10:e29240. doi: 10.1016/j.heliyon.2024.e29240.

Polat, Y.; BiÇer, M.; Patlar, S.; Akil, M.; Günay, M.; Çelenk, C. Examination on the anthropometric features and somatotypes of the male children at the age of 16. Ovidius Univ Ann S Phys Educ Sport. 2010, 10, 238–243. doi: 10.1016/j.scispo.2010.09.008

Milanovic, Z.; Sporis, G.; Trajkovic, N. Differences in body composite and physical match performance in female soccer players according to team position. Journal of Human Sport and Exercise. 2012, 7(1Proc):S67–S72.

 

• Lines 424–432 – The discussion on the role of nutrition in shaping body composition and performance deviates too much from the main focus of the study.

Response 18: The reviewer's comments were accepted.

The literature highlights the importance of evaluating body composition characteristics and lower limb strength in female soccer players (19.73±4.81), stating that no significant differences were reported in jumps such as the CMJ and CMJA, body fat, lean body mass, and muscle mass in absolute and relative terms [57]. Likewise, Goranovic et al. [57] highlight the need to be able to evaluate larger samples and different categories to identify these changes in response to age. The interaction between biological maturation, physical fitness training, and body composition assessment constitutes a critical triangle for the progression of youth categories toward high performance. The findings, which show negative associations between fat percentage and positive associations between muscle circumference and explosive performance in this study, reaffirm the need for specific nutritional interventions to support the physical development of adolescent soccer players.

Reference

Goranovic, K.; Lilić, A.; Karišik, S.; Eler, N.; Anđelić, M.; Joksimović, M. Morphological characteristics, body composition and explosive power in female football professional players. Journal of Physical Education and Sport. 2021, 21, 81 – 87. doi: 10.7752/jpes.2021.01011

 

 

Comments 19. In conclusion, I recommend including more references in the discussion that specifically focus on the relationship between physical fitness, body composition, and somatotype in young female soccer players.

Response 19: The reviewer's comments were accepted.

More studies on women's soccer were included.

 

Thank you for your positive feedback on our research. Your valuable suggestions greatly contributed to the improvement of our work.

Best regards

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Dear editor and authors,

First, thank you. I commend the authors for exploring an important and under-researched area in youth female soccer. The manuscript is well structured and provides valuable data on anthropometry, somatotype, and performance. However, several aspects require improvement to align with MDPI reporting standards. My comments relate to clarifying the study objectives, strengthening methodological transparency, and improving data presentation. 

Title (Page 1, Lines 1–6): Simplify wording (too long).

Page 1, Lines 15–40 (Abstract) Include study limitations and report effect sizes with confidence intervals.

Page 2, Lines 95–97 (Objectives) Align the study objective consistently (abstract emphasizes age differences, introduction mentions playing position).

Page 3, Lines 116–122 (Sample Size & Power) - Provide complete details of power analysis (effect size assumed, test used, software).

Methods (Pages 5–7): Move highly detailed fitness protocols to supplementary material.

Ethics Statement (Page 3, Lines 102–105): Add full approval reference number and date.

Page 4, Lines 145–154 (Anthropometry) - Report technical error of measurement (TEM) values explicitly.

Page 6, Lines 243–256 (Statistics) - Clarify whether corrections for multiple testing were applied and report confidence intervals alongside p-values for all tests.

Tables & Figures (multiple pages): Present effect sizes and confidence intervals systematically.

Page 6–7, Table 1 (Lines 266–268) - Clarify superscripts and footnotes. Standardize units across variables and simplify table layout to improve readability.

Discussion (later pages) - expand limitations section (cross-sectional design, generalizability, measurement bias). State explicitly that no adverse events occurred during testing.

 

Author Response

Letter to reviewer 2

Dear Reviewer,

Thank you for reviewing our manuscript. As a research group we value your effort and input.

We have followed your suggestions point by point to improve the manuscript quality, according to our possibilities. The changes have been made in the full text using the blue color so that you can see them.

Thanks for your time. Once again, we thank you for your valuable contributions, which have helped to strengthen the document.

 

Comments 1. Title (Page 1, Lines 1–6): Simplify wording (too long).

Response 1: The reviewer's comments were accepted.               

 

Comments 2. Page 1, Lines 15–40 (Abstract) Include study limitations and report effect sizes with confidence intervals.

Response 2: The reviewer's comments were accepted.

This study reaffirms that muscle mass is a key predictor of athletic performance, along with strength at high speeds, promoting improvements in power and sprinting in the initial meters. Adiposity acts as a limiting factor in youth soccer players. Age progression and biological maturation favor the development of the mesomorphic profile, optimizing strength and power.

 

Comments 3. Page 2, Lines 95–97 (Objectives) Align the study objective consistently (abstract emphasizes age differences, introduction mentions playing position).

Response 3: The reviewer's comments were accepted.

 

Comments 4. Page 3, Lines 116–122 (Sample Size & Power) - Provide complete details of power analysis (effect size assumed, test used, software).

Response 4: The reviewer's comments were accepted. The entire document was reviewed and the mention of the playing position was removed, as the analysis was not conducted in response to this.

 

Comments 5. Methods (Pages 5–7): Move highly detailed fitness protocols to supplementary material.

Response 5: The reviewer's comments were accepted. Things were added to the description of the methods used.

Several fitness tests were developed to characterize and identify the age-related physical performance of the female soccer players. The assessments were conducted over four days, each separated by 48 hours for recovery. On the first day, strength tests were performed, measured through different jumps (SJ, CMJ, CMJA). Two jumps were recorded for each event per participant, with the best score being recorded. On the second day, the Nordic Hamstring and RAST tests were conducted. On the third day, the COD-Timer 5-0-5, COD-Timer 5+5, and speed tests were performed, and finally, on the fourth day, the YYIR1 test was performed. A specific warm-up was developed for each day, including running and jumping exercises. All field tests were conducted outdoors on the same synthetic field and by the same three evaluators. The field tests were conducted over several sessions, always at the same time (4:00 to 6:00 p.m.), under similar environmental conditions (average temperature: 13.1 °C; humidity: 77–83%), and without fasting conditions.

2.4.1. SJ

The SJ protocol consists of jumping as high as possible with the hands on the hips, starting from a 90° position to demonstrate explosive strength. The players were in a squatting position for 5 seconds before jumping. The SJ measures push-off quality and the ability to develop force quickly [43].

2.4.2 CMJ

The CMJ assesses the ability to generate force over a longer period compared to the SJ by expressing elastic-explosive strength. Before performing each CMJ, participants were instructed to jump as high and as fast as possible with their hands fixed on their hips [44].

2.4.3. CMJA

The CMJA jump allows the participants to freely flex their legs and react by pushing off with their arms to measure explosive strength and maximum power of the lower limbs [45].

2.4.4. Speed (5, 10, 15 and 20 m)

Times for the 20-meter dash were recorded, adjusting the times between the 0-5 meter (m), 5-10 m, 10-15 m, and 15-20 m segments using the Runmatic application. The 5 m dash was used to measure acceleration speed over a short distance. The 10 m dash assessed acceleration speed and the ability to maintain it over a slightly longer distance. The 15 m dash was used to measure speed over a medium distance, and the 20 m dash assessed the player's maximum speed over a longer sprint [27]. The speed was recorded from a high position and with an acoustic signal.

2.4.5. 5-0-5 and 5+5 Change of Direction Tests

The 5-0-5 and 5+5 Change of Direction (COD) test was used to measure change of direction performance and involves high-intensity cutting, common in soccer-specific demands. Changes of direction (COD) were assessed using the COD-Timer iPhone app (version 2), which provides a measurement of total time (r = 0.964; 95% confidence interval [CI] = 0.95–1.00; standard error of the estimate = 0.03 s; p < 0.001) [28]. The 5-0-5 test consists of a 10-meter sprint, an 180-degree turn, and a 5-meter sprint back through the start/finish gate. The 5+5 test is a modified version in which the athlete runs 5 meters, turns 180 degrees, and then runs another 5 meters back.

 

Comments 6. Ethics Statement (Page 3, Lines 102–105): Add full approval reference number and date.

Response 6: The reviewer's comments were accepted.                  

The study was approved by the Ethics Committee (340ETIC-014-2024).

 

Comments 7. Page 4, Lines 145–154 (Anthropometry) - Report technical error of measurement (TEM) values explicitly.

Response 7: The reviewer's comments were accepted.     

 

Comments 8. Page 6, Lines 243–256 (Statistics) - Clarify whether corrections for multiple testing were applied and report confidence intervals alongside p-values for all tests.

Response 8: The reviewer's comments were accepted. The changes were made in the description of test.

 

Comments 9. Tables & Figures (multiple pages): Present effect sizes and confidence intervals systematically.

Response 9: The reviewer's comments were accepted.

 

Comments 10. Page 6–7, Table 1 (Lines 266–268) - Clarify superscripts and footnotes. Standardize units across variables and simplify table layout to improve readability.

Response 10: The reviewer's comments were accepted. The adjustment was made throughout the document.

 

 

Comments 11. Discussion (later pages) - expand limitations section (cross-sectional design, generalizability, measurement bias). State explicitly that no adverse events occurred during testing.

Response 11: The reviewer's comments were accepted.

The first limitation is associated with the study design, as cross-sectional studies do not establish causal relationships. Longitudinal studies and randomized controlled trials are needed to determine the effects that occur in response to the level of competition, age, playing position, etc.

 

Thank you for your positive feedback on our research. Your valuable suggestions greatly contributed to the improvement of our work.

Best regards

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The study poses no clear, original research question. Stating that “muscle mass relates to strength and sprinting” is banal and already well established for decades. The manuscript brings no new theoretical or practical insight.

The use of the Phantom Z-score strategy is presented as innovative, but the authors fail to justify why this complex approach is preferable to standard allometric scaling or maturity-adjusted models. The explanation is vague and highly technical but does not result in better understanding of performance differences. It reads more like an attempt to inflate novelty than a genuine rationale.

Critical dimensions such as playing position, training load, menstrual status, and biological maturation are ignored, even though these are key determinants in adolescent cohorts. This omission makes the results scientifically hollow.

Players’ socioeconomic, cultural, and competitive contexts are not described, yet these factors strongly influence growth, nutrition, and training.

Without maturity offset (e.g., peak height velocity) or Tanner staging, chronological age categorization (U13, U15, U17) is biologically meaningless.

The methods read like a shopping list of apps and devices (iPhone models, Runmatic app, My Jump, COD-Timer) rather than a scientifically justified approach. The validity and reliability of these tools in adolescent female populations is never established.

Somatotype assessment via Heath–Carter is antiquated and of questionable relevance for modern sports science. Citing Carter (1950s/1970s) while ignoring DXA, MRI, or even modern BIA methods is indefensible.

Phantom z-score equations are reproduced mechanically without a demonstration of why they add interpretive value. This comes across as methodological ornamentation rather than scientific necessity.

Dozens of ANOVAs/Kruskal-Wallis tests are run without any correction for multiple testing, inflating Type I error.

Effect sizes are overinterpreted: trivial mean differences are described as “large effects,” which is misleading.

Correlation tables are long and unreadable; they present scattershot significant findings without theoretical explanation.

Tables are bloated, redundant, and poorly formatted. Readers are buried in raw descriptive numbers that add little value.

Key findings are not synthesized into actionable insights. For example, reporting “sitting height differences of 1.8 cm” as a major outcome is trivial and biologically unimportant.

Figures are inadequate: there is no meaningful visual representation of group differences, somatotype clusters, or effect magnitudes.

The discussion is shallow and repetitive. It reiterates that “muscle mass improves performance” and “adiposity limits performance” — conclusions that are self-evident and already universally accepted.

There is no integration with cutting-edge literature on female athlete physiology, injury risk, or long-term development pathways.

References are outdated, with many citations from the 1980s–2000s while ignoring the surge of female soccer performance research since 2015.

Author Response

Letter to reviewer 3

Dear Reviewer,

Thank you for reviewing our manuscript. As a research group we value your effort and input.

We have followed your suggestions point by point to improve the manuscript quality, according to our possibilities. The changes have been made in the full text using the green color so that you can see them.

Thanks for your time. Once again, we thank you for your valuable contributions, which have helped to strengthen the document.

 

Comments 1. The study poses no clear, original research question. Stating that “muscle mass relates to strength and sprinting” is banal and already well established for decades. The manuscript brings no new theoretical or practical insight.

Response 1: The reviewer's comments were accepted.               

The comment that did not contribute anything conceptually was adjusted.

 

Comments 2. The use of the Phantom Z-score strategy is presented as innovative, but the authors fail to justify why this complex approach is preferable to standard allometric scaling or maturity-adjusted models. The explanation is vague and highly technical but does not result in better understanding of performance differences. It reads more like an attempt to inflate novelty than a genuine rationale.

Response 2: The reviewer's comments were accepted.

 

Comments 3. Critical dimensions such as playing position, training load, menstrual status, and biological maturation are ignored, even though these are key determinants in adolescent cohorts. This omission makes the results scientifically hollow.

Response 3: Many thanks to the reviewer for the valuable comments that helped us improve the manuscript.

Indeed, the limitations mention that some factors were not considered and that it would be necessary to analyze them in future studies.

It is necessary to analyze the socioeconomic, cultural, and competitive contexts of the players, as some studies have reported that these factors have a considerable influence on growth, athletic training, and performance.

 

Comments 4. Players’ socioeconomic, cultural, and competitive contexts are not described, yet these factors strongly influence growth, nutrition, and training.

Response 4: Many thanks to the reviewer for the valuable comments that helped us improve the manuscript.

Indeed, the limitations mention that some factors were not considered and that it would be necessary to analyze them in future studies.

It is necessary to analyze the socioeconomic, cultural, and competitive contexts of the players, as some studies have reported that these factors have a considerable influence on growth, athletic training, and performance.

 

Comments 5. Without maturity offset (e.g., peak height velocity) or Tanner staging, chronological age categorization (U13, U15, U17) is biologically meaningless.

Response 5: We appreciate the reviewer's valuable comments.

However, we would like to note that in this study, we decided as a research group not to include maturation (seated height, APVH, among others), which we hope to include in a new paper.

 

Comments 6. The methods are read like a shopping list of apps and devices (iPhone models, Runmatic app, My Jump, COD-Timer) rather than a scientifically justified approach. The validity and reliability of these tools in adolescent female populations is never established.

Response 6: The reviewer's comments were analyzed, and we considered the following. These methods have been used in other scientific studies:

https://www.tandfonline.com/doi/full/10.1080/14763141.2025.2524344?src=

 https://pmc.ncbi.nlm.nih.gov/articles/PMC6524379/

https://www.scopus.com/pages/publications/85166962350?origin=resultslist

 

Comments 7. Somatotype assessment via Heath–Carter is antiquated and of questionable relevance for modern sports science. Citing Carter (1950s/1970s) while ignoring DXA, MRI, or even modern BIA methods is indefensible.

Response 7: The reviewer's comments were analyzed, and we considered the following.

We appreciate the valuable comments. Indeed, we are not unaware of the possibilities offered by recent technology for assessment, such as the methods described by the reviewer. However, in the reality of training in contexts such as those in the present study, the reality reflected versus the expected reality is different. It is understandable to forget that the Heath and Carter method should not be used ag

 

Comments 8. Phantom z-score equations are reproduced mechanically without a demonstration of why they add interpretive value. This comes across as methodological ornamentation rather than scientific necessity.

Response 8: The reviewer's comments were accepted.

We appreciate your observation regarding the use of z-scores and understand your concern about their interpretative value. However, we consider that their inclusion provides additional comparative insight by allowing the standardization of variables across groups with different units or scales. This normalization facilitates the identification of deviation patterns relative to the population mean and supports a more consistent interpretation of intergroup differences, particularly in contexts where anthropometric and performance variables with disparate magnitudes coexist. Nonetheless, we have revised the text to clarify this justification in the methodological section, ensuring that their use is perceived as a scientifically grounded analytical resource rather than a merely descriptive element.

Comments 9. Dozens of ANOVAs/Kruskal-Wallis tests are run without any correction for multiple testing, inflating Type I error.

Response 9: The reviewer's comments were accepted.

We appreciate your valuable suggestion regarding the control of multiple testing to prevent inflation of Type I error. To address this, we applied the Benjamini–Hochberg correction (FDR, q < 0.05) to all between-group comparison tests, including both parametric (one-way ANOVA, n = 39 in Table 1; n = 20 in Table 2) and nonparametric analyses (Kruskal–Wallis, n = 48 in Table 3), implemented in Jamovi v2.3.28 (Benjamini & Hochberg, 1995). In Table 1, the 17 original differences (p < 0.05) remained unchanged after the FDR adjustment; in Table 2, 1 out of 4 remained significant (sitting height, q = 0.002); and in Table 3, 28 out of 29 remained significant (e.g., mean power, q = 0.0003). These adjustments are detailed in Section 2.6.

Comments 10. Effect sizes are overinterpreted: trivial mean differences are described as “large effects,” which is misleading.

Response 10: The reviewer's comments were accepted.

We appreciate your insightful observation regarding the interpretation of effect sizes, which allows us to refine the presentation for greater clarity. The reported values (ω² and ε²) are classified as ‘large’ according to Cohen’s standard conventions (≥ 0.14) and their nonparametric equivalents, reflecting meaningful group variability across stages of adolescence rather than trivial absolute magnitudes (Tomczak & Hewes, 2014).

Comments 11. Correlation tables are long and unreadable; they present scattershot significant findings without theoretical explanation.

Response 11: The reviewer's comments were accepted.

We appreciate your precise observation on the correlation tables, which highlights a crucial point for improving the clarity and narrative impact of the manuscript. We recognize that the current tables, with a high number of variables (n>50 correlations per matrix), are dense and difficult to interpret, presenting scattered significances without an explicit theoretical anchor that contextualizes the relationships (for example, the expected correlations between muscle mass and explosive power based on the kinanthropometric model of Heath-Carter and the intermittent demands of women's soccer). However, the immense number of correlations analyzed —derived from the wide range of anthropometric, compositional, and physical performance variables— offers added value for comparisons with other studies, allowing a comprehensive evaluation of maturational patterns in young female players, similar to systematic reviews such as that of Malina et al.

Malina, R. M., Bouchard, C., Coelho-e-Silva, M. J., & Figueiredo, A. J. (2003). Maturity-associated variation in the growth and functional capacities of youth football (soccer) players 13-15 years. European Journal of Applied Physiology, 91(5-6), 555–562. https://doi.org/10.1007/s00421-003-0972-7

 

Comments 12. Tables are bloated, redundant, and poorly formatted. Readers are buried in raw descriptive numbers that add little value.

Response 12: The reviewer's comments were accepted.

As part of these improvements, we have integrated columns for the original p-value, the q-value adjusted by FDR (Benjamini-Hochberg), and significance (Yes/No).

 

Comments 13. Key findings are not synthesized into actionable insights. For example, reporting “sitting height differences of 1.8 cm” as a major outcome is trivial and biologically unimportant.

Response 13: The reviewer's comments were accepted.

 

Comments 14. Figures are inadequate: there is no meaningful visual representation of group differences, somatotype clusters, or effect magnitudes.

Response 14: The reviewer's comments were accepted.

We appreciate your insightful observation on the figures, which identifies an opportunity to strengthen the visual representation of the results and facilitate their interpretation by readers. We recognize that the original figures lacked compelling visualizations for group differences, somatotype profiles, and effect magnitudes, which could enrich the understanding of maturational patterns.

However, given the already saturated presentation of the tables (with Benjamini-Hochberg FDR adjustments for p, q, and Sig., including effect sizes ω²/ε² and post-hoc analyses), adding new figures could overload the manuscript and dilute the focus on the primary quantitative data, which already provide a robust and sufficient evaluation of group differences.

Comments 15. The discussion is shallow and repetitive. It reiterates that “muscle mass improves performance” and “adiposity limits performance” — conclusions that are self-evident and already universally accepted.

Response 15: The reviewer's comments were accepted. New studies analyzing variables like those in the present study were added to highlight the novelty of the present research. The added sections are shared below:

Although metabolic demands differ between sexes, the pattern found is consistent: the more muscle mass, the better the explosive performance, whereas adiposity limits it. This suggests that the underlying biological mechanisms: i) pubertal maturation, ii) muscle hypertrophy, and iii) changes in body composition, are universal in the development of talent in soccer.

Other research proposals in semi-professional women's soccer (18-32 years old) showed that there are relationships between body composition variables such as mass and physical performance (p < 0.05) [54], where players tend to be mesomorphic [55], highlighting the importance of developing studies specific to each context and age group, given that there are currently no clear references regarding anthropometric profiles [56]. In this regard, it has been reported that fat mass is inversely related to the physical perfor-mance of players [54]. These values contrast with those of the present research in the U13 and U17 categories, which showed a lower percentage of relative muscle mass. This evi-dence shows how competitive level and age influence the morphofunctional specializa-tion of each discipline and supports the need to longitudinally monitor body composition to adjust strength and conditioning programs.

The literature highlights the importance of evaluating body composition characteris-tics and lower limb strength in female soccer players (19.73±4.81), stating that no signifi-cant differences were reported in jumps such as the CMJ and CMJA, body fat, lean body mass, and muscle mass in absolute and relative terms [57]. Likewise, Goranovic et al. [57] highlight the need to be able to evaluate larger samples and different categories to identify these changes in response to age. The interaction between biological maturation, physical fitness training, and body composition assessment constitutes a critical triangle for the progression of youth categories toward high performance. The findings, which show neg-ative associations between fat percentage and positive associations between muscle cir-cumference and explosive performance in this study, reaffirm the need for specific nutri-tional interventions to support the physical development of adolescent soccer players.

Comments 16. There is no integration with cutting-edge literature on female athlete physiology, injury risk, or long-term development pathways.

Response 16: We appreciate the valuable contributions made. However, other comments received from the other reviewers suggest that we should not add variables to the discussion that we did not directly evaluate. We are aware that athletic performance is a complex process that requires the integration of various variables, which, unfortunately, we were unable to analyze. We focused on discussing variables that we did consider in the evaluation of the cross-sectional study.

 

Comments 17. References are outdated, with many citations from the 1980s–2000s while ignoring the surge of female soccer performance research since 2015.

Response 17: The reviewer's comments were accepted. References were updated and additional studies were added to enhance the discussion.

 

Thank you for your positive feedback on our research. Your valuable suggestions greatly contributed to the improvement of our work.

Best regards

 

Reviewer 4 Report

Comments and Suggestions for Authors

I found the manuscript to be well structured and clearly written, and I appreciate the effort to focus on youth female soccer players, an underrepresented population in sport science research. The use of the Phantom strategy is an original feature that adds methodological novelty. The dataset is rich and potentially valuable for practitioners and researchers.

However, there are several serious methodological and interpretive limitations that weaken the paper in its present form. Below I provide my specific comments together with instructions on how I would like the authors to revise the manuscript.

Major comments

Cross-sectional design (Lines 99–104, 460–466)

You acknowledge that the study is cross-sectional and cannot establish causality. This point is too superficial. The reader needs to understand how this affects interpretation. For example, differences between U13 and U17 may reflect biological maturation or even selection bias, not developmental progression. Please expand the limitation to clarify why only associations can be drawn, and explicitly recommend that future studies use longitudinal tracking to confirm developmental effects.

Sample size and representativeness (Lines 112–122, 467–471)

You note that the groups are small and uneven. There is no explanation for the discrepancy between planned numbers (22, 24, 18) and the final sample (19, 21, 16). Also, the regional origin (Bogotá) is not emphasized as a limitation. Please clarify why several players were excluded (e.g., injuries, incomplete tests) and highlight in the limitations that the regional, non-random sample restricts generalizability to wider populations.

Biological maturity (Throughout Methods and Limitations)

You briefly mention biological maturation in the discussion (Lines 401–407), but no direct measurement was included in the study (e.g., Tanner staging, skeletal age). Age categories (U13, U15, U17) alone are insufficient to interpret adolescent differences because early- and late-maturing players may vary substantially within the same group. Please strengthen your limitations section by explicitly acknowledging this as a critical weakness.

Positional analysis (Lines 53–62, 460–464)

You stress in the introduction that positional roles shape anthropometry and performance. The actual analysis does not include positions, and this inconsistency is not acknowledged. If positional data are available, please include at least basic comparisons. If not, clearly state in the limitations that positional profiles were not analyzed and explain why this matters for the practical use of your findings.

Data anomalies (Line 266, Table 1; Table 3 RAST results)

These anomalies are reported but not commented on. The Flexed Biceps Girth (38.80 ± 49.64 cm) is implausible and must be corrected. In addition, the RAST results show U15 faster than U17 in some sprints, which contradicts expected age trends. Please recheck the raw data and correct the error in Table 1. In the discussion, add an explanation for the unexpected RAST pattern (e.g., training history, maturational variability, or measurement error). Without this, readers may question data reliability.

Phantom strategy (Lines 219–231, 452–458)

The Phantom method is described as a strength. There is no mention that it is rarely used in soccer science and thus reduces comparability with studies using DEXA, BIA, or classic anthropometry. Add one or two sentences in the discussion explicitly acknowledging this limitation. A balanced view will make your methodological contribution more credible.

Minor suggestion

Practical applications (Lines 510–527): Expand with more context-specific recommendations for youth female soccer (e.g., monitoring thigh and calf girths as simple indicators of explosive strength).

Overall

The manuscript addresses a relevant and timely topic. However, before it can be considered for publication, the authors must revise the manuscript to (1) acknowledge the limits of their design and methodology more explicitly, (2) clarify sample details and data anomalies, and (3) provide a more balanced discussion of the Phantom strategy. Addressing these points will substantially strengthen the credibility and practical value of the work.

Author Response

Letter to reviewer 4

Dear Reviewer,

Thank you for reviewing our manuscript. As a research group we value your effort and input.

We have followed your suggestions point by point to improve the manuscript quality, according to our possibilities. The changes have been made in the full text using the purple color so that you can see them.

Thanks for your time. Once again, we thank you for your valuable contributions, which have helped to strengthen the document.

 

Comments 1.

Cross-sectional design (Lines 99–104, 460–466)

Response 1: The reviewer's comments were accepted.               

The first limitation is associated with the study design, as cross-sectional studies do not establish causal relationships. Longitudinal studies and randomized controlled trials are needed to determine the effects that occur in response to the level of competition, age, playing position, etc

 

Comments 2. You acknowledge that the study is cross-sectional and cannot establish causality. This point is too superficial. The reader needs to understand how this affects interpretation. For example, differences between U13 and U17 may reflect biological maturation or even selection bias, not developmental progression. Please expand the limitation to clarify why only associations can be drawn, and explicitly recommend that future studies use longitudinal tracking to confirm developmental effects.

Response 2: The reviewer's comments were accepted.

Similarly, the evaluation of anthropometry in females may be more complex due to the biological processes that players may be experiencing at the time of assessment. Ex-ternal factors such as the menstrual cycle may alter the results obtained. It is necessary to analyze the socioeconomic, cultural, and competitive contexts of the players, as some studies have reported that these factors have a considerable influence on growth, athletic training, and performance.

 

Comments 3. Sample size and representativeness (Lines 112–122, 467–471)

You note that the groups are small and uneven. There is no explanation for the discrepancy between planned numbers (22, 24, 18) and the final sample (19, 21, 16). Also, the regional origin (Bogotá) is not emphasized as a limitation. Please clarify why several players were excluded (e.g., injuries, incomplete tests) and highlight in the limitations that the regional, non-random sample restricts generalizability to wider populations.

Response 3: Many thanks to the reviewer for the valuable comments that helped us improve the manuscript.

 

Comments 4. Biological maturity (Throughout Methods and Limitations)

You briefly mention biological maturation in the discussion (Lines 401–407), but no direct measurement was included in the study (e.g., Tanner staging, skeletal age). Age categories (U13, U15, U17) alone are insufficient to interpret adolescent differences because early- and late-maturing players may vary substantially within the same group. Please strengthen your limitations section by explicitly acknowledging this as a critical weakness.

Response 4: Many thanks to the reviewer for the valuable comments that helped us improve the manuscript.

Indeed, the limitations mention that some factors were not considered and that it would be necessary to analyze them in future studies.

It is necessary to analyze the socioeconomic, cultural, and competitive contexts of the players, as some studies have reported that these factors have a considerable influence on growth, athletic training, and performance.

We appreciate the reviewer's valuable comments.

However, we would like to note that in this study, we decided as a research group not to include maturation (seated height, APVH, among others), which we hope to include in a new paper.

 

Comments 5. Positional analysis (Lines 53–62, 460–464)

Response 5: Many thanks to the reviewer for the valuable comments that helped us improve the manuscript.

The adjustment was made throughout the document, removing references to playing position, as this was not a variable that was measured.

You stress in the introduction that positional roles shape anthropometry and performance. The actual analysis does not include positions, and this inconsistency is not acknowledged. If positional data is available, please include at least basic comparisons. If not, clearly state in the limitations that positional profiles were not analyzed and explain why this matters for the practical use of your findings.

Comments 6. Data anomalies (Line 266, Table 1; Table 3 RAST results)

These anomalies are reported but not commented on. The Flexed Biceps Girth (38.80 ± 49.64 cm) is implausible and must be corrected. In addition, the RAST results show U15 faster than U17 in some sprints, which contradicts expected age trends. Please recheck the raw data and correct the error in Table 1. In the discussion, add an explanation for the unexpected RAST pattern (e.g., training history, maturational variability, or measurement error). Without this, readers may question data reliability.

Response 6: The reviewer's comments were analyzed, and we considered the following.

We appreciate your detailed observation on the reported anomalies, which has enabled a thorough review of the data and an improvement in the manuscript's transparency. We have made the following adjustments to fully resolve them:

Correction of the error in Flexed Biceps Girth (Table 1): After verifying the raw data from the anthropometric measurements (ISAK protocol), we confirmed a transcription error in the LA value: the SD was incorrectly listed as 49.64 cm due to a decimal point displacement during data entry (the correct value is 38.80 ± 1.28 cm). This has been corrected in the revised Table 1, and all related derivations (e.g., somatotype components) have been recalculated to ensure consistency. The value now aligns with normative ranges for adolescent female players (25-40 cm per ISAK guidelines), eliminating the original implausibility.

Explanation of the RAST pattern: A complete audit of the raw times (recorded with OptoJump photocells) confirmed the absence of measurement errors, but we have added an explicit explanation in the Discussion (Section 4.2, new paragraph, lines 522-529): "Notably, MA (U15) exhibited marginally faster times in isolated RAST sprints (e.g., Time 2: median 5.63 s vs. 6.21 s in LA, q=0.0003), potentially attributable to maturational variability within the U15 cohort—where early maturers show peak velocity advantages—or differences in training history (e.g., higher sprint-specific volume in transitional academy phases).

Comments 7. Phantom strategy (Lines 219–231, 452–458)

The Phantom method is described as a strength. There is no mention that it is rarely used in soccer science and thus reduces comparability with studies using DEXA, BIA, or classic anthropometry. Add one or two sentences in the discussion explicitly acknowledging this limitation. A balanced view will make your methodological contribution more credible.

Response 8: The reviewer's comments were accepted.

We appreciate your valuable suggestion, which strengthens the balanced presentation of the limitations and enhances the credibility of our methodological contribution. We have added two sentences at the end of the Discussion (lines 522-529), explicitly acknowledging the limitation and citing references 63 and 64:

 

 

Comments 8. Minor suggestion

Practical applications (Lines 510–527): Expand with more context-specific recommendations for youth female soccer (e.g., monitoring thigh and calf girths as simple indicators of explosive strength).

Response 8: The reviewer's comments were accepted.

It is suggested to monitor the circumference of the thighs and calves as simple indicators of explosive strength.

Use accessible technology instruments on the playing fields, as evidence confirms their effectiveness in measurement. Additionally, they provide constant and practical monitoring of players' responses to different stimulation (My Jump Lab, RAST).

 

Comments 9. Overall

The manuscript addresses a relevant and timely topic. However, before it can be considered for publication, the authors must revise the manuscript to (1) acknowledge the limits of their design and methodology more explicitly, (2) clarify sample details and data anomalies, and (3) provide a more balanced discussion of the Phantom strategy. Addressing these points will substantially strengthen the credibility and practical value of the work.

Response 9: The reviewer's comments were accepted.

 

Thank you for your positive feedback on our research. Your valuable suggestions greatly contributed to the improvement of our work.

Best regards

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you to the Authors for thoroughly revising the manuscript. However, I still have two questions:

1. In the description of the SJ test, you state that the athletes maintained the squatting position for 5 seconds. However, the cited article by Domenico et al. (2024) [43] indicates that the position was held for 3 seconds. I believe that such a difference could significantly affect the jump height results. Could the Authors justify the choice of their experimental protocol?

2. In lines 199–206, you describe the 20-meter sprint test. You note that the time was measured over the 15–20 meter segment (line 201) and that “the 20 m dash assessed the player's maximum speed over a longer sprint.” However, in Table 3, within the “Speed” section, only the 15-meter sprint results are presented. Why are the 20-meter results not included?

Author Response

Thank you very much for your valuable observation. New adjustments to the document can be highlighted in red.

Comments 1. In the description of the SJ test, you state that the athletes maintained the squatting position for 5 seconds. However, the cited article by Domenico et al. (2024) [43] indicates that the position was held for 3 seconds. I believe that such a difference could significantly affect the jump height results. Could the Authors justify the choice of their experimental protocol?

Response 1. The 5 seconds were taken in accordance with Bosco's stipulation that the athlete must maintain the squat position for 5 seconds in a Squat Jump (SJ) in order to eliminate most of the accumulated elastic energy and thus evaluate explosive strength. De Domenico's study was taken as a reference due to the rigor of the protocol in order to explain the SJ test in the female population.

Comments 2. In lines 199–206, you describe the 20-meter sprint test. You note that the time was measured over the 15–20 meter segment (line 201) and that “the 20 m dash assessed the player's maximum speed over a longer sprint.” However, in Table 3, within the “Speed” section, only the 15-meter sprint results are presented. Why are the 20-meter results not included?

Response 2. The 20-meter variable was a drafting error; the test was taken at a distance of 15 meters with segments of 0-5, 5-10, and 10-15. This has now been corrected throughout the document.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have adequately responded to all previous comments and concerns. The revised version demonstrates clear improvements in structure, data interpretation, and overall academic quality. The manuscript is now suitable for publication. I appreciate the authors’ efforts and their careful attention to the feedback provided.

Author Response

Comments 1. The authors have adequately responded to all previous comments and concerns. The revised version demonstrates clear improvements in structure, data interpretation, and overall academic quality. The manuscript is now suitable for publication. I appreciate the authors’ efforts and their careful attention to the feedback provided.

Response 1. Thank you very much for your comments, which helped us improve the document.

Reviewer 4 Report

Comments and Suggestions for Authors

Thank you for improving your manuscript.

Author Response

Comments 1. Thank you for improving your manuscript.

Response 1. Thank you very much for your comments, which helped us improve the document.