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A Multivariate Framework for Position-Specific Performance Analytics in Elite Volleyball: Development, Validation, and Applications for Evidence-Based Coaching

Anin Dita Safitri, Soni Sulistyarto, Irmantara Subagio, Achmad Widodo, Taufiq Hidayat, Muhammad Muhammad · INSPIREE Indonesian Sport Innovation Review · 2026

Researchers analyzed match data from 300 elite volleyball players across five positions in Indonesia's 2025 Proliga Championship, using a position-specific observation tool and multivariate statistics to test whether technical skills differ by role. Position strongly predicted technical performance: setters led in setting quality, opposites in attack effectiveness, middle blockers in blocking, and liberos in serve reception and defense.
Takeaway: Evaluate and train volleyball players against position-specific skill benchmarks rather than one generic performance standard.
Abstract (source)

Background: &

Objective: Position-specific technical demands in elite volleyball require evaluation systems that accurately reflect the tactical responsibilities of each playing role. However, most existing performance assessments rely on generalized indicators that may underestimate positional specialization. This study aimed to develop and validate a multivariate framework for objectively evaluating technical performance across setters, outside hitters, middle blockers, opposites, and liberos.

Materials and methods: This observational quantitative study employed a Research and Development (R&D) framework using official match data from the 2025 Indonesian Proliga Championship. The dataset included 300 elite volleyball players equally distributed across five playing positions. Technical performance was assessed using a validated position-specific observation instrument covering service, serve reception, setting, attack, blocking, and defense. Data were analyzed using descriptive statistics, Shapiro–Wilk, Levene's, and Box's M tests, followed by Multivariate Analysis of Variance (MANOVA), one-way ANOVA, Tukey's Honestly Significant Difference (HSD) post hoc tests, and Estimated Marginal Means (EMMs).

Results: All statistical assumptions were satisfied prior to inferential analysis. MANOVA revealed a significant multivariate effect of playing position on overall technical performance (Wilks' Λ = 0.214, p < .001, Partial η² = 0.46). Significant differences were identified across all technical domains (p < .001). Setters achieved the highest setting quality, opposites demonstrated superior attack effectiveness, middle blockers excelled in blocking, and liberos recorded the strongest serve reception and defensive performance. Position-specific performance profiles generated through EMMs further confirmed clear technical specialization.

Conclusions: The proposed framework provides a valid, reliable, and standardized approach for

objective position-specific performance evaluation. Its application can enhance evidence-based coaching, individualized athlete development, talent identification, and performance monitoring in elite volleyball.

Observational / cohortOpen accessVelocity-Based & Technology
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