Impact of Specific Periodization and Foster’s Scale on Technical and Emotional Development of Young Volleyball Athletes (13 - 16 Years Old) ()
1. Introduction
Volleyball is among the most practiced team sports worldwide and plays a central role in adolescents’ motor, cognitive, and psychosocial development. In Brazil and the United States, it functions not only as a competitive sport but also as a pedagogical tool that fosters teamwork, discipline, and resilience. Training athletes aged 13 - 16, however, presents distinctive challenges. This developmental stage is characterized by rapid growth, hormonal variability, evolving executive functions, and heightened emotional reactivity. These characteristics influence how adolescents perceive effort, tolerate fatigue, and connect practice content to long-term skill acquisition. Recent studies (e.g., Saw et al., 2016; Montull et al., 2022; Sondt et al., 2024) highlight the importance of integrating subjective monitoring tools with training load management to enhance performance and psychological well-being in youth athletes. A physically demanding drill that combines repeated jumps with ball control, for example, may be misinterpreted as simple conditioning, when the intent is to accelerate technical execution and decision-making. Bridging this perception-intention gap requires structured, scientifically grounded methodologies that integrate conditioning and skill development.
1.1. Specific Demands of Adolescence in Sport
Adolescence is more than a transitional stage; it is a unique biopsychosocial period. Academic pressure, social identity formation, and peer dynamics interact with growth and neural maturation to influence motivation and stress management. Many adolescents report fluctuations in self-esteem, difficulties in self-regulation, and mood variability that may undermine consistent training. Thus, programs for this age group should go beyond physical conditioning to cultivate emotional engagement and metacognitive awareness. Designing constraints that clarify the technical purpose of conditioning—such as embedding jump work within attack-timing drills or coupling defensive footwork with live ball recovery—helps adolescents connect exertion to tactical and technical goals.
1.2. Periodization in Volleyball
Traditional models of periodization, developed for individual sports, often fail to account for the dynamics of team sports. In response, volleyball-specific periodization frameworks have been proposed, integrating physical, technical, and tactical components into coherent training structures. These frameworks emphasize careful manipulation of load variables—volume, intensity, and complexity—aligned with competition calendars. Monitoring such variables is essential, as poor control may result in overtraining or injury. For adolescents, who are particularly vulnerable to fatigue and emotional stress, this monitoring is even more critical.
1.3. Monitoring Training Load with Foster’s Scale
The introduction of Foster’s Session Rating of Perceived Exertion (sRPE) provided a simple, low-cost way to monitor internal training load. Calculated by multiplying perceived effort by session duration, sRPE correlates well with physiological markers and is widely validated. In adolescent volleyball, sRPE offers two benefits. First, it allows coaches to adjust volume and intensity based on how athletes are actually responding, complementing metrics such as monotony (mean/SD across a week) and strain (mean × monotony). Second, it promotes cognitive awareness: athletes reflect on their fatigue and readiness when asked to report effort and soreness. This strengthens self-regulation and reinforces the technical purpose of drills, linking “how it feels” with “what we are training”.
1.4. Emotional Impact of Training Load
Beyond physical adaptation, systematic monitoring influences emotional development. Structured training combined with reflective tools has been shown to improve motivation, reduce anxiety, and reinforce athletes’ sense of purpose. In volleyball, performance depends on coordination, timing, anticipation, and team cohesion. When adolescents understand why a drill is demanding, they are more likely to stay engaged and sustain quality effort. Thus, combining volleyball-specific periodization with sRPE provides a dual pathway: optimizing physical performance and enhancing psychosocial development.
1.5. Rationale of the Present Study
Despite the validation of sRPE and volleyball-specific periodization in adult and professional contexts, little evidence addresses youth cohorts that consider load, technical outcomes, defined here as measurable changes in enjoyment, motivation, and self-regulation of effort, and emotional responses simultaneously. Adolescent programs often lack access to sophisticated technology, making low-burden, athlete-centered monitoring particularly relevant. Building on practical applications, this study addresses this gap by documenting the seasonal pattern of internal load (including monotony and strain), weekly enjoyment, motivation, and soreness, and changes in technical performance (serve accuracy, attack efficiency, average jumps per set) in adolescent female volleyball players.
1.6. Objective of the Study
To evaluate the impact of volleyball-specific periodization on physical performance and emotional development in athletes aged 13 - 16 years, with emphasis on Foster’s Scale as a tool to align training load with technical aims and to support adaptive psychosocial outcomes. (defined here as measurable changes in enjoyment, motivation, and self-regulation of effort).
2. Methods
2.1. Study Design
This research is characterized as a longitudinal, descriptive, observational study, developed according to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines, ensuring methodological transparency and reproducibility. The study aimed to investigate the impact of applying specific periodization for volleyball combined with Foster’s Scale of Perceived Exertion (PSE) on both technical and emotional development of female athletes aged 13 - 16 years. Technical skills were assessed by two independent volleyball coaches using standardized criteria (serve accuracy %, attack efficiency %, jump counts). Inter-rater reliability was high (Cohen’s κ = 0.85). Non-parametric tests were applied despite normality checks due to small and heterogeneous samples. A formal power analysis was not conducted, which is acknowledged as a limitation.
2.2. Population and Sample
The population consisted of adolescent female volleyball athletes competing at the regional level, with the possibility of qualifying for national tournaments. Three independent cohorts were included, representing different years and contexts:
Cohort 1: 25 athletes, aged 13 - 16 years, belonging to a competitive club team. Training frequency was three sessions per week, over a total of 30 weeks (≈ one competitive season).
Cohort 2: 23 athletes divided into two subgroups: 13 athletes (Sub-15) and 10 athletes (Sub-13). Training frequency was two sessions per week, over 26 weeks.
Cohort 3: 10 athletes (Sub-15), followed over 26 weeks, with two sessions per week.
Across all cohorts, the training context was structured and supervised by qualified coaches, with athletes regularly participating in official competitions.
2.3. Selection Process and Inclusion Criteria
Athletes were recruited based on their active enrollment in competitive volleyball programs. Inclusion criteria were: a) female sex, b) age between 13 and 16 years at the start of data collection, c) participation in at least 80% of scheduled training sessions, and d) signed informed consent by parents/guardians, along with athlete assent. Exclusion criteria included: a) athletes with musculoskeletal injuries at the start of monitoring, b) those who did not complete at least 70% of the monitoring period, and c) athletes diagnosed with chronic illnesses that could interfere with training load tolerance.
2.4. Ethical Considerations
All stages of the research respected the principles of the Declaration of Helsinki (2013 revision) regarding ethical procedures with human participants. Athletes and guardians received detailed information about the study objectives, voluntary participation, and confidentiality of individual results. For the 2018 Brazilian cohort, approval was obtained from the Institutional Ethics Committee linked to the academic environment in which the intervention was carried out. For the 2023 and 2025 cohorts in the United States, activities were conducted under institutional supervision, following local regulations on research involving minors.
2.5. Intervention and Training Structure
Training followed the model of specific periodization for volleyball proposed by Marques Junior (2017), The core principles of the Marques Junior model include the integration of physical and technical-tactical tasks, progressive overload through volleyball-specific actions such as jumps and defensive displacements, and tapering in the weeks preceding competition. Each season was divided into three main phases:
Preparatory period: Initial 6 - 8 weeks with low-to-moderate load, combining general conditioning and technical fundamentals.
Pre-competitive period: Progressive increase in load, reaching medium-to-high intensity approximately one month before the first competition. Sessions emphasized tactical drills, high-intensity rallies, and complex motor tasks.
Competitive period: Maintenance of medium loads, reduction of training volume in the week preceding official competitions, and emphasis on ball control and tactical positioning.
At all times, conditioning was integrated with volleyball-specific movements (e.g., jump training combined with ball recovery, defensive displacements with situational drills) rather than isolated physical exercises.
2.6. Monitoring Tools
Foster’s Scale of Perceived Exertion (sRPE): Administered at the end of each training session to record perceived effort. Internal training load (UA) was calculated by multiplying intensity (sRPE score) by session duration in minutes.
Muscle soreness scale (PS): Administered post-training to assess fatigue and delayed onset muscle soreness (DOMS).
Training diary: Each session was documented with load values, muscle soreness scores, and qualitative notes about athlete engagement.
2.7. Variables Measured
Physical variables: Internal training load (UA), session monotony, training strain, jump frequency, training volume.
Emotional variables: Anxiety was assessed weekly using a 5-point Likert self-report scale, and self-awareness of fatigue was monitored through short post-session reflective diaries. These were exploratory variables and not consistently reported in the Results.
Performance variables: Technical execution of serves, attacks, blocks, and overall game performance during competitions.
2.8. Statistical Analysis
Data were processed using GraphPad Prism (version 5.0) and SPSS (version 26.0). Descriptive statistics (mean, standard deviation, minimum, maximum) were used to summarize data across microcycles and mesocycles. The Shapiro-Wilk test verified data normality. For inferential analysis, the Kruskal-Wallis ANOVA with Dunn’s post-hoc test was applied to compare differences between microcycles and mesocycles regarding internal training load, intensity, volume, and muscle soreness. Pearson’s correlation coefficient was used to test associations between training load (UA) and emotional indicators (motivation, enjoyment). A significance level of p ≤ 0.05 was adopted.
2.9. Quality Assurance
To ensure reliability, all scales (sRPE and PS) were explained to athletes using simple visual aids (faces and descriptors), and weekly meetings reinforced correct interpretation. Intra-rater consistency was verified by repeating assessments in a subsample of athletes, confirming reproducibility. Data collection followed a standardized protocol across all cohorts.
3. Results
This section reports outcomes objectively, without interpretation. Results are organized by cohort, training period, and variable category (physical, emotional, technical). Descriptive statistics are given as mean, median, and standard deviation (SD). Comparative analyses include p-values, in bold when significant at α = 0.05.
3.1. Training Exposure and Adherence
Cohort 1 (Brazil, 2018) completed 30 microcycles with three sessions/week; Cohorts 2 and 3 (USA, 2023 and 2025) completed 26 microcycles with two sessions/week. Sessions lasted 90 - 120 minutes. Attendance exceeded 85% and no season-long interruptions occurred. Minor schedule adjustments were made around competitions (Table 1).
Table 1. End-of-Season technical outcomes (pooled).
Description |
Mean |
Median |
SD |
p |
Serve accuracy (%) |
71.5 |
71.5 |
6.2 |
<0.001 |
Attack efficiency (%) |
34.5 |
34.5 |
4.1 |
<0.001 |
Average jumps per set |
27.8 |
27.8 |
3.2 |
<0.001 |
SD: standard deviation; p: p-value from paired comparisons versus baseline (normal approximation). Statistically significant p-values should appear in bold.
3.2. Internal Training Load (UA)
Pooled data show rising load from the Preparatory to Pre-competitive phase, followed by controlled reduction in the Competitive phase. Table 2 summarizes period-level means for internal load (UA_mean), monotony, and strain with weeks observed. Figure 1 (left) shows weekly median UA across 26 weeks, illustrating progressive overload and taper.
3.3. Muscle Soreness and Perceived Exertion
Soreness scores mirrored UA patterns, peaking near pre-competitive weeks and stabilizing during competition. Session-based sRPE-derived loads remained within the intended range for adolescent volleyball training.
Table 2. Internal load (UA), monotony and strain by training period (Pooled across cohorts).
Period |
UA_mean |
Monotony |
Strain |
n_weeks |
Competitive |
292.5 |
8.08 |
2360.6 |
28 |
Pre-competitive |
355.9 |
10.86 |
3856.5 |
28 |
Preparatory |
242.0 |
6.46 |
1576.5 |
26 |
UA: internal training load derived from sRPE; Monotony = period mean (UA)/SD(UA); Strain = period mean (UA) × Monotony; n_weeks: number of observed weeks per period.
3.4. Emotional Indicators
Motivation scores increased from 3.2 ± 0.5 to 3.5 ± 0.4, and enjoyment from 3.4 ± 0.6 to 3.6 ± 0.5 across the season. Weekly descriptive statistics showed soreness peaking between weeks 8 - 10 (mean 3.8 ± 0.7) and stabilizing at moderate values during the competitive period. Table 3 reports correlations between weekly median UA and enjoyment, motivation, and soreness. Figure 1 (right) shows weekly enjoyment and motivation. No extreme outliers (>3 SD) were detected.
(a) (b)
Figure 1. Joint display: Weekly internal training load (UA) (left) and weekly emotional indicators (right).
3.5. Technical Performance
End-of-season metrics were higher than baseline. By cohort: Brazil 2018 (n = 25)—serve accuracy +11%, attack efficiency +8%; USA 2023 (n = 13)—serve +12%, attack +9%; USA 2025 (n = 10)—serve +14%, attack +10%. These mirrored pooled improvements. Table 1 presents descriptive statistics and p-values from paired comparisons. Median and mean values moved in the same direction. Figure 1 (left) (when included) shows baseline vs. end-of-season values for serve accuracy, attack efficiency, and jumps per set.
3.6. Data Quality
Analyses were conducted at the microcycle level with distributional checks for extremes. Missing data were <5% and not imputed. Weekly reminders reinforced sRPE anchors. Figure 1 combines two charts (UA load; enjoyment/motivation) into a single image as per journal instructions.
Table 3. Correlations between weekly median UA and emotional variables.
Pair |
r |
p |
UA vs Enjoyment |
0.05 |
0.809 |
UA vs Motivation |
0.238 |
0.244 |
UA vs Soreness |
0.493 |
0.01 |
Pearson correlation coefficients between weekly median UA and enjoyment, motivation, and muscle soreness; approximate p-values via Fisher z transform.
4. Discussion
This study evaluated the impact of a volleyball-specific periodization model, monitored with Foster’s Session Rating of Perceived Exertion (sRPE), on physical load (UA, monotony, strain, soreness), emotional state (enjoyment, motivation), and technical performance (serve accuracy, attack efficiency, jumps per set) in adolescent female athletes. The main findings were: 1) progressive load increase from preparatory to pre-competitive phases, followed by controlled reduction during competition; 2) soreness rising with higher loads, stabilizing later; 3) small positive trends in enjoyment and motivation, weakly correlated with load; and 4) end-of-season technical improvements.
These results indicate that combining volleyball-specific periodization with sRPE is compatible with the dual aim of youth training: structured physiological stimulus and preserved emotional engagement. The observed trajectory of overload and taper matches best practice in team-sport mesocycles. Soreness trends reflected expected neuromuscular demands, providing a useful control against overreaching.
Compared with existing literature, the findings support sRPE as a valid, low-cost measure of internal load. Its routine use helps coaches tailor intensity while accommodating individual variability. Volleyball-specific periodization emphasizes integrating conditioning with technical-tactical demands; our structure followed this principle and likely supported the observed gains in serve and attack. Patterns of monotony and strain echoed prior reports in team sports, with peaks during pre-competitive loading.
The emotional results complement physical indicators. Adolescents often struggle to connect discomfort with technical goals; systematic monitoring invites reflection and fosters self-regulation. Weekly reporting of effort and soreness may have improved athletes’ understanding of training purpose, reinforcing motivation. Developmentally, such awareness supports engagement and resilience in this age group.
Technical outcomes strengthen the case for this approach. Improvements in accuracy, efficiency, and jump frequency align with the principle that conditioning embedded in sport-specific drills facilitates skill consolidation. The taper before competition may have optimized technical expression by reducing fatigue while maintaining readiness.
Safety is also highlighted. The coherence between load, monotony, and soreness shows that progressive overload was accompanied by expected adaptations and moderated during competition. For adolescents—vulnerable to fatigue, sleep loss, and school stress—these indicators are valuable. Monitoring load and soreness jointly provides better insight than either metric alone.
Limitations must be acknowledged. The design was descriptive and lacked a control group; improvements cannot be attributed solely to the model. Emotional data relied on brief scales, which capture trends but not full affective profiles. Self-reported measures remain vulnerable to bias despite anchor reinforcement. Cohorts differed in context (Brazil vs. USA). Differences in training frequency (Brazil: 3 sessions/week vs USA: 2 sessions/week) may partly explain variations, with higher frequency likely supporting faster technical consolidation, schedule, and competition structure, limiting generalizability. Objective markers (e.g., heart rate, jump counts, inertial sensors) were not included. Technical results, while positive, should be confirmed with athlete-level paired analyses using robust statistics. Additional limitations include small sample sizes per cohort and cultural/contextual differences between Brazil and the USA, which may affect generalizability.
Despite these limits, the study has strengths. It tracked real-world training across multiple seasons and countries, enhancing ecological validity. Periodization was explicitly volleyball-specific, with conditioning embedded in technical-tactical contexts. Monitoring burden was minimal, supporting sustainability in youth programs. The alignment of observed load/strain with planned mesocycles confirmed fidelity of implementation. Finally, integrating physical, emotional, and technical outcomes offers a holistic perspective rarely addressed in adolescent sport research.
Weak correlations between training load and motivation likely reflect that psychosocial states are influenced by multiple contextual factors, including academic stress and peer dynamics. Practical recommendations include embedding conditioning into volleyball drills, for example, repeated jumps combined with ball recovery, so that training intensity supports technical improvement while sustaining engagement.
Future studies should adopt stronger designs (e.g., randomized or stepped-wedge), integrate multimodal monitoring (sRPE plus objective metrics), and expand emotional assessment with validated short-form instruments. Mixed-methods approaches could clarify how adolescents interpret monitoring tools and how this shapes motivation. Tracking sleep, academic load, and injuries would give a fuller picture of recovery and adaptation.
Within the limits of an observational design, this study shows that volleyball-specific periodization combined with sRPE monitoring produces coherent load patterns, maintains positive emotional engagement, and coincides with technical gains in adolescent female players. The approach appears feasible, educationally meaningful, and well suited to youth sport, underscoring the value of simple athlete-centered monitoring to balance performance and well-being.
5. Conclusion
Volleyball-specific periodization monitored with sRPE produced coherent training loads, modest emotional benefits, and significant technical improvements in adolescent athletes. The novelty of this study lies in demonstrating an integrated, low-cost model that combines physical, emotional, and technical monitoring in youth volleyball. Across three real-world cohorts, internal load followed the intended arc of progressive overload and taper; soreness rose predictably during higher-load phases and moderated during competition; enjoyment and motivation trended upward across microcycles; and pooled technical indicators (serve accuracy, attack efficiency, average jumps per set) improved from baseline to season end. Together, these patterns show that a simple, athlete-centered monitoring routine can be embedded in a sport-specific plan to guide day-to-day adjustments without undermining developmental quality.
Practically, three implications follow. First, season architecture matters: clearly defined preparatory, pre-competitive, and competitive periods enable load progressions that adolescents tolerate while sustaining motivation. Second, minimal-burden monitoring can be meaningful: sRPE and brief soreness checks, applied consistently, are sufficient to signal peaks and plateaus and to keep workloads within adaptive ranges. Third, technical outcomes benefit when conditioning is delivered through volleyball constraints, for example, jump conditioning drills were executed in combination with ball recovery or defensive repositioning, ensuring that physical loads directly supported technical-tactical objectives, aligning how sessions feel with what they are intended to teach. While observational by design, the convergence of workload, emotion, and skill change points to a feasible, educationally coherent path for youth programs seeking to balance performance and well-being.
Future implementations should preserve low measurement burden and high ecological validity, while progressively adding objective markers (e.g., simple heart-rate indices, jump counts) and brief validated emotional scales suited to adolescents. Designs that incorporate appropriate controls and mixed-methods insights can clarify causal pathways and enrich coach-athlete dialogue. Within these guardrails, volleyball-specific periodization monitored with sRPE appears to be a pragmatic foundation for organizing stimulus, protecting engagement, and cultivating skill during a formative athletic window.
Acknowledgements
The author thanks the athletes and their families for their trust and dedication, as well as the coaches and managers who collaborated in implementing daily monitoring. Special gratitude is extended to the GAB Community Institute (Orlando, Florida, USA) for its financial support, to the Tainas Volleyball Club (Orlando, Florida, USA) for providing facilities and competitive opportunities, and to the Prefeitura Municipal de Diadema (São Paulo, Brazil) for its institutional encouragement of youth sport. Appreciation is also due to colleagues who contributed to data collection and session debriefing procedures.