Impact of Modified Competition Formats on Physical Performance in Under-14 Female Volleyball Players: The Role of Biological Maturity

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript tests whether modified competition formats in U14 female volleyball (MD1: lower net, ban on jump serves, max two consecutive serves; MD2: MD1 plus smaller court) change external-load metrics (accelerations/decelerations, impacts, jumps) and whether biological maturity (% predicted adult height, %PAH) moderates these effects. Across three tournaments (ST, MD1, MD2) with 29 players, the authors report higher counts—often greatest in MD2—for accelerations, decelerations, impacts, and jumps, plus moderation ranges identified via Johnson–Neyman analyses (MEMORE) for several outcomes (e.g., jumps and impacts).

Major Recommendations

Significance and Novelty

The topic—age-/maturity-aligned rules in youth volleyball—is timely and practically relevant. However, the contribution is limited by design and analysis choices that weaken causal interpretation (see Design below). Current claims that modified formats “enhance kinematic performance” and “create a safer environment” extrapolate from device-derived counts without injury/wellness or technique data, so they should be tempered or explicitly framed as hypotheses.

Structure and content of the Introduction

The Introduction motivates rule scaling and biobanding reasonably well, with volleyball-specific mechanisms (net height, court size) described. It would benefit from integrating recent analytical approaches that couple task constraints with contextualized modeling (e.g., DOI: 10.1080/02640414.2022.2099077; DOI: 10.1371/journal.pone.0254900) to justify why context (rally length, rotation/role, set duration) should be modeled alongside external-load metrics.

The claim that experimental evidence “in real competitive contexts” is scarce is fair, but the present study does not analyze technical–tactical performance or rally structure, which narrows the “real competition” insight (only kinematics were captured).

Methods: Quality of used Methods, Methodological Limitations

Design / internal validity

The tournaments appear sequential (ST → MD1 → MD2) with each team playing only two matches per tournament, increasing vulnerability to order effects, opponent variability, set/rally duration differences, and temporal confounding. None of these contextual factors is modeled or controlled, which can directly inflate/deflate counts of accelerations, impacts, and jumps.

Instrumentation and setting

Data were collected with WIMU PRO (UWB LPS + IMU) in an indoor basketball court, but crucial implementation details (anchor placement, calibration, sampling rate, occlusions) and a validation reference specific to volleyball/LPS accuracy are not reported; the single sentence “validated in previous study [28]” is insufficient for context-specific validity.

Anthropometry and maturity

The device listed as a “Tanita stadiometer (Tanita BF-522W)” is, by model code, commonly a bioimpedance scale, not a stadiometer; please clarify the actual instrument and how parental heights were obtained (measured vs. self-report), given %PAH sensitivity to parental height error.

Descriptives and plausibility checks

The sample table reports height 1.63 ± 0.96 m, an implausible SD (~96 cm) suggesting a typographical or unit error; this needs correction and a full audit of descriptive statistics.

Rule descriptions / replicability

The MD1/MD2 description contains garbled text and duplication, obscuring serve-limit implementation and risking misinterpretation (e.g., repeated “two serves per player and rotation” clause). Please rewrite for clarity and confirm whether the 8×8 m vs 9×9 m refers to per-side dimensions (which is standard in volleyball) .

Data Interpretation and Analysis, Statistics

Frequentist vs Bayesian contradictions

The manuscript reports p-values, partial η², BF₁₀, and posterior odds but does not reconcile conflicts. Example: 5–8 g impacts show p = .010 but BF₁₀ = 0.124 (evidence for H₀ by Bayesian standards), while average landing (g) shows p = .121 but BF₁₀ = 28.67 (strong evidence for H₁). You must predefine the primary evidential framework and explain decision rules when indices disagree.

Multiplicity / familywise error

Dozens of variables across three conditions with multiple post hocs are tested. Beyond the Bayesian post hoc correction, there is no strategy to control experimentwise error across the whole battery (accel/decels, several g-bands, jump metrics). Consider dimension reduction (PCA/composites) or hierarchical/multivariate models and pre-specified primary endpoints.

Effect size and practical significance

Some statistically “significant” findings have very small partial η² (e.g., .006 for 5–8 g impacts), which undermines practical significance. Include confidence intervals and standardized mean differences with interpretive thresholds to aid applied readers.

Moderation analysis

The Johnson–Neyman ranges are often narrow and near the upper %PAH spectrum (e.g., many effects >~88–90% PAH). Provide raw-data visualizations (scatter/violin by %PAH deciles or bins) and robustness checks (e.g., excluding extremes, robust regression). Current figures lack individual data overlays and clear axis units/labels.

Results: results, Figures and tables

Internal inconsistencies exist between table labels and the narrative. Table 2 lists “< 8 g impacts”, yet the text interprets “higher than 8G” among the significant variables; please harmonize the label, threshold direction, and narrative claims.

Several post hoc summaries (e.g., “T1 < T3; T2 < T3”) lack exact contrasts with CIs and sometimes conflict with Bayesian evidence gradations (anecdotal vs strong) for the same rows; include the actual contrast estimates (mean differences, CI/HDI) next to each symbol code.

Define the operational cut-offs for “high accelerations/decelerations” and g-bands within Methods once, with a brief rationale and source.

Discussion: Conclusion

Assertions that MD2 promotes “more frequent but less intense actions” and a “safer environment” are not directly supported without injury, soreness, or wellness indices; they should be toned down or explicitly couched as hypotheses for future work.

The Discussion should acknowledge design limitations (non-randomized order, contextual variability, unmeasured technical–tactical factors) and the frequentist–Bayesian conflicts noted above, which are currently underplayed.

Bring the moderation takeaway into sharper focus: specify which maturity bands benefit most and for which variables, and avoid broad generalizations (e.g., “above ~90% PAH”) without consistent evidence across outcomes.

Minor Points

Language and Clarity

Numerous typos/formatting issues interrupt readability (e.g., duplicated/garbled MD1/MD2 rule sentence; spacing around units; mixed capitalization)—please copy-edit thoroughly.

Ensure consistent units and symbols (g, m/s²) and correct anomalies in descriptives (height SD).

 

Final Recommendation

Major revisions. The dataset is promising and the topic relevant, but conclusions require a firmer analytical foundation, clearer reporting, and explicit treatment of design limitations before the work can support the practical claims it makes. Thank you for the opportunity to review this manuscript.

     

Author Response

Dear Reviewer,

The authors recommend reading the attached document as it includes some figures that cannot be attached to the body of the message.

 

Dear reviewer, thank you very much for your comments.  We will answer all your suggestions point by point in the following paragraphs. All changes will be right in red letters in the manuscript.

 

Reviewer 1:

Structure and content of the Introduction

The Introduction motivates rule scaling and biobanding reasonably well, with volleyball-specific mechanisms (net height, court size) described. It would benefit from integrating recent analytical approaches that couple task constraints with contextualized modeling (e.g., DOI: 10.1080/02640414.2022.2099077; DOI: 10.1371/journal.pone.0254900) to justify why context (rally length, rotation/role, set duration) should be modeled alongside external-load metrics.

The claim that experimental evidence “in real competitive contexts” is scarce is fair, but the present study does not analyze technical–tactical performance or rally structure, which narrows the “real competition” insight (only kinematics were captured).

 

A paragraph has been added incorporating your valuable suggestion and the references you previously indicated. Furthermore, we refer to the scarcity of studies conducted in real competitive settings in a general sense, since in youth volleyball categories, research remains limited regardless of whether physical, technical–tactical, or cognitive variables are analyzed.

 

Methods: Quality of used Methods, Methodological Limitations

Design / internal validity

The tournaments appear sequential (ST → MD1 → MD2) with each team playing only two matches per tournament, increasing vulnerability to order effects, opponent variability, set/rally duration differences, and temporal confounding. None of these contextual factors is modeled or controlled, which can directly inflate/deflate counts of accelerations, impacts, and jumps.

Instrumentation and setting

Data were collected with WIMU PRO (UWB LPS + IMU) in an indoor basketball court, but crucial implementation details (anchor placement, calibration, sampling rate, occlusions) and a validation reference specific to volleyball/LPS accuracy are not reported; the single sentence “validated in previous study [28]” is insufficient for context-specific validity.

Anthropometry and maturity

The device listed as a “Tanita stadiometer (Tanita BF-522W)” is, by model code, commonly a bioimpedance scale, not a stadiometer; please clarify the actual instrument and how parental heights were obtained (measured vs. self-report), given %PAH sensitivity to parental height error.

Descriptives and plausibility checks

The sample table reports height 1.63 ± 0.96 m, an implausible SD (~96 cm) suggesting a typographical or unit error; this needs correction and a full audit of descriptive statistics.

Rule descriptions / replicability

The MD1/MD2 description contains garbled text and duplication, obscuring serve-limit implementation and risking misinterpretation (e.g., repeated “two serves per player and rotation” clause). Please rewrite for clarity and confirm whether the 8×8 m vs 9×9 m refers to per-side dimensions (which is standard in volleyball).

 

Sections 2.2 and 2.3 were reviewed and revised according to your suggestions. The parents recorded their height at the same time as their children’s, which helped to ensure the validity of the data

 

Data Interpretation and Analysis, Statistics

Frequentist vs Bayesian contradictions

The manuscript reports p-values, partial η², BF₁₀, and posterior odds but does not reconcile conflicts. Example: 5–8 g impacts show p = .010 but BF₁₀ = 0.124 (evidence for H₀ by Bayesian standards), while average landing (g) shows p = .121 but BF₁₀ = 28.67 (strong evidence for H₁). You must predefine the primary evidential framework and explain decision rules when indices disagree.

 

The section has been modified to highlight the statistical framework.

This study adopted a Bayesian approach as its main evidentiary framework. Inferences were based on model comparison using Bayes factors (BF₁₀) and Bayesian odds ratios, which quantify the relative evidence in favour of the alternative hypothesis (H₁) versus the null hypothesis (H₀). Frequentist analyses are included only as supplementary information on the magnitude and precision of the observed effects.

The normality of the data distribution was assessed. For variables with a normal distribution, a repeated-measures ANOVA was performed; for variables with a non-normal distribution, the Friedman test was applied. Effect size was calculated using partial η². In addition, a Bayesian repeated-measures ANOVA was conducted. For the interpretation of differences, the Bayes Factor (BF₁₀) was used. Bayesian post hoc comparisons between tournaments were conducted to evaluate specific differences, using a Bayesian approach with multiple comparison correction [31]. In the event of discrepancies between Bayesian and frequentist metrics, interpretative priority was given to the Bayesian result. Posterior odds (PO) were used as the main indicator.

 

 

Effect size and practical significance

Some statistically “significant” findings have very small partial η² (e.g., .006 for 5–8 g impacts), which undermines practical significance. Include confidence intervals and standardized mean differences with interpretive thresholds to aid applied readers.

Confidence intervals have been added. Furthermore, we clarified previously that Bayesian analysis should be taken into account in the event of a dispute.

 

 

Moderation analysis

The Johnson–Neyman ranges are often narrow and near the upper %PAH spectrum (e.g., many effects >~88–90% PAH). Provide raw-data visualizations (scatter/violin by %PAH deciles or bins) and robustness checks (e.g., excluding extremes, robust regression). Current figures lack individual data overlays and clear axis units/labels.

The distribution places most players in the upper maturity stage. However, this procedure performs a percentile bootstrap IQ procedure.

 

 

 

Results: results, Figures and tables

Internal inconsistencies exist between table labels and the narrative. Table 2 lists “< 8 g impacts”, yet the text interprets “higher than 8G” among the significant variables; please harmonize the label, threshold direction, and narrative claims.

Done, thanks for your appreciation.

 

Several post hoc summaries (e.g., “T1 < T3; T2 < T3”) lack exact contrasts with CIs and sometimes conflict with Bayesian evidence gradations (anecdotal vs strong) for the same rows; include the actual contrast estimates (mean differences, CI/HDI) next to each symbol code.

For the post hoc, the POs were taken into account.

 

Define the operational cut-offs for “high accelerations/decelerations” and g-bands within Methods once, with a brief rationale and source.

The values that appear in other academic studies have been used.

Pawlik, D., & Mroczek, D. (2022). Fatigue and training load factors in volleyball. International Journal of Environmental Research and Public Health, 19(18), 11149.

Akyildiz, Z., de Oliveira Castro, H., Çene, E., Laporta, L., Parim, C., Altundag, E., & Clemente, F. M. (2022). Within-week differences in external training load demands in elite volleyball players. BMC Sports Science, Medicine and Rehabilitation, 14(1), 188.

 

 

Discussion: Conclusion

Assertions that MD2 promotes “more frequent but less intense actions” and a “safer environment” are not directly supported without injury, soreness, or wellness indices; they should be toned down or explicitly couched as hypotheses for future work.

We have considered for future studies.

The Discussion should acknowledge design limitations (non-randomized order, contextual variability, unmeasured technical–tactical factors) and the frequentist–Bayesian conflicts noted above, which are currently underplayed.

Limitations paragraphs are added.

Bring the moderation takeaway into sharper focus: specify which maturity bands benefit most and for which variables, and avoid broad generalizations (e.g., “above ~90% PAH”) without consistent evidence across outcomes.

We modified the conclusion according your suggestions.

 

Minor Points

Language and Clarity

Numerous typos/formatting issues interrupt readability (e.g., duplicated/garbled MD1/MD2 rule sentence; spacing around units; mixed capitalization)—please copy-edit thoroughly.

Ensure consistent units and symbols (g, m/s²) and correct anomalies in descriptives (height SD).

The authors have reviewed the minor aspects. Thank you for your comments.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Please see attached

Comments for author File: Comments.pdf

Author Response

REVIEWERS LETTER

 

Dear reviewer, thank you very much for your comments.  We will answer all your suggestions point by point in the following paragraphs. All changes will be right in red letters in the manuscript.

 

 

Reviewer 2:

The abstract is well-structured, with the aim, methods, results and conclusions presented.

The introduction provides a comprehensive background on volleyball adaptations and biological maturity. The experimental work in this area is indeed limited, leading to the purpose of the study. The flow of the paragraphs is not very good, and it could be improved. For example, the discussion of net height in line 57 should include all relevant information in one place, rather than introducing another separate paragraph on net height at line 87. I would revisit the introduction and separate the paragraphs into sections that deal with biological maturity as well as competition models. In this way, the authors will be able to support the need for the study. If you have a specific research hypothesis that needs to be added.

 

We restructured the introduction according your suggestions . Thank you.

 

The methodology is described in detail so that someone can replicate the study. The participant’s characteristics are presented. Protocols and procedures are also described in detail. Evidence for ethical approval is provided. Were there any exclusion criteria? Is there any justification for the sample size? Based on what I understood, all the players followed the same competition order. Do you think the order might have influenced the results (fatigue effects, etc)?

 

The participants played the same set of games and competed against the same opponents to maintain the study’s statistical power and to control the rest intervals between sets and across days.

 

The results section is clearly presented. The figures are not very clear, but it may be the version that I have.

 

The authors have attached the highest quality graphics along with the other files.

 

 

The discussion connects findings to previous research, and the study is certainly novel in its assessment of biological maturity. However, the first and second paragraphs could be better connected. It is generally more effective to begin the discussion by summarizing the key findings. In this case, the authors start by presenting the study’s purpose and noting that their results align with previous work, but they do so without first outlining their own results. Furthermore, the discussion lacks critical thinking, and the study limitations are missing. I would focus on interpreting the results rather than presenting them.

Overall, I find the topic very important, particularly with the inclusion of biological maturity. However, I believe certain sections of the manuscript would benefit from revision or rewriting (incorporating more critical thinking).

 

Limitations have been added, and the discussion has been restructured following your suggestions.

 

Kind Regards

The authors

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript titled “Impact of Modified Competition Formats on Physical Performance in Under-14 Female Volleyball Players: The Role of Biological Maturity” explores the effects of adapted competition formats—such as changes in net height, court dimensions, and serve rules—on physical performance, while also examining the moderating role of biological maturity (assessed via % predicted adult height, PAH).

Using a quasi-experimental design, the study evaluates accelerations, decelerations, impacts, and jump-related metrics across three tournament types (ST, MD1, MD2). The authors apply a Bayesian inferential framework supplemented by frequentist statistics.

The study is timely and relevant, contributing to an under-explored area in youth volleyball and providing practical implications for rule modifications and bio-banding practices in youth sport.

Major Recommendations

Significance and Novelty

The authors have strengthened the theoretical framework with additional citations and further justified the importance of contextual modeling and biobanding in volleyball. The paper now clearly contributes novel empirical data in a real competitive setting—rare in volleyball rule adaptation literature.

Structure and Content of Introduction

The introduction now integrates ecological dynamics and contextual modeling frameworks more explicitly. It also clearly articulates the research gap—limited empirical data in youth volleyball under real-match conditions—and how this study fills it. The background is well-structured and logically leads into the study's aims.

Methods: Quality of Used Methods, Methodological Limitations

• Sequential design concern: Acknowledged in the limitations section (p. 13, lines 342–346), with a reasonable reflection.

• Instrumentation details: The manuscript now includes improved implementation details regarding the WIMU PRO system (anchor placement, sampling rate, etc.) in section 2.3.

• Stadiometer/device error: Corrected (Tanita BF-522W clarified and actual m

  easurements specified).

• Typographical data error (height SD = 0.96 m): Still present (p. 2, line 110). This SD is implausibly high (96 cm). The authors claim it's been reviewed, but the value remains incorrect. This must be corrected before acceptance.

Data Interpretation and Analysis, Statistics

• Bayesian vs frequentist conflict: Resolved. The authors now state that Bayesian inference is the primary evidentiary framework, with frequentist results included for context only (section 2.4).

• Effect size interpretation and CIs: Confidence intervals and posterior odds are now consistently reported in tables.

• Moderation analysis robustness: Additional individual plots (Figures 1–3, pages 6, 8, 11) with Johnson–Neyman regions are included, showing the relationship between PAH and each variable. These figures now clearly illustrate maturity-based moderation. However, while scatterplots were shown in the rebuttal letter, these were not retained in the final manuscript. Including one in the main paper (as supplementary or in Results) would further aid interpretation.

Results: Results, Figures, and Tables

• Label inconsistency (e.g., “<8g” vs “>8g” impacts): Corrected in Table 2 and narrative.
• Missing post hoc CIs and PO values: These are now provided (Tables 1–3), with clear interpretation of posterior odds and Bayes Factors.
• Definition of g-bands and thresholds: Operational definitions and references are now provided in section 2.3, citing relevant literature (Pawlik & Mroczek, 2022; Akyildiz et al., 2022).

Discussion: Conclusion

• Claims about “safer environment”: Now more cautiously phrased (p. 12, lines 309–311 and p. 13, lines 357–359), highlighting the lack of direct injury or wellness data.
• Design limitations: Explicitly acknowledged (p. 13, lines 342–346).
• Moderation results contextualized: Clarified ranges of %PAH for significant moderation effects across variables (e.g., >88–99%) and aligned conclusions accordingly.

Minor Points

Language and Clarity

• Many previously identified typos, formatting inconsistencies, and clarity issues have been corrected.

• Units are now more consistently presented (e.g., m/s², g).
• However, the following minor issues remain:
  • The SD of height (0.96 m) is still implausible and needs correction.
  • check: “the %PAH moderates de intervention” (p. 9, line 263).
  • Punctuation and spacing can be improved further in the reference list and figure legends.

Recommendation

Rationale: The authors have addressed nearly all reviewer suggestions comprehensively. The manuscript demonstrates clear improvements in statistical reporting, methodological transparency, and the depth of discussion. Only a few minor issues remain, such as:

1. Correction of the anthropometric descriptive error (implausible SD for height).
2. Optional: Including at least one scatterplot of raw acceleration/impact values by %PAH, as initially shown in the rebuttal, would enhance transparency.

Once these are resolved, the paper is suitable for publication.

Thank you for the opportunity to review this revised manuscript.

Author Response

• Typographical data error (height SD = 0.96 m): Still present (p. 2, line 110). This SD is implausibly high (96 cm). The authors claim it's been reviewed, but the value remains incorrect. This must be corrected before acceptance.

The authors have checked the SD. We appreciate one observation: where a 9 should have been a 0. Thus, the SD is 0.06.

height 1.63 ± 0.06 meters;

 

• Moderation analysis robustness: Additional individual plots (Figures 1–3, pages 6, 8, 11) with Johnson–Neyman regions are included, showing the relationship between PAH and each variable. These figures now clearly illustrate maturity-based moderation. However, while scatterplots were shown in the rebuttal letter, these were not retained in the final manuscript. Including one in the main paper (as supplementary or in Results) would further aid interpretation.

The authors have included Figure 1 to correct this error in section of methods. Thank you for pointing it out.

 

The distribution of the %PAH data can be seen in Figure 1.

Figure 1. Distribution of the %PAH variable.

 

• The SD of height (0.96 m) is still implausible and needs correction.

 

The error has been revised, replacing the 9 with a 0.

 

• check: “the %PAH moderates de intervention” (p. 9, line 263).

The %PAH has been checked and the error has been resolved. The error was in the graphs, and the errors in the figure corresponding to 3-5g IMAPCTS, ST-MD, and >8g IMPACTS ST-MD2 have been corrected. The remaining figures have also been revised.

 

• Punctuation and spacing can be improved further in the reference list and figure legends.

This has been reviewed and resolved. Thank you.

 

Once these are resolved, the paper is suitable for publication.

The authors have addressed the reviewer's comments. Thank you for your comments.

ps: the authors include the new figures in the attached documents.

 

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

I have no further recommendations! Well-done!

Author Response

Comments and Suggestions for Authors

I have no further recommendations! Well-done!

The authors welcome your comments. Thank you for reviewing our manuscript.