A Neutrosophic Approach for Opponent Analysis and Game Strategy Formulation in College Volleyball

In competitive college volleyball, effective opponent analysis is crucial for strategic decisionmaking, particularly when facing teams with varying performance dynamics. This study introduces a QNeutrosophic Soft Set (QNSS) approach to opponent analysis, enabling multi-context decision evaluation based on a granular assessment of opponent characteristics across different game conditions. Our QNSS proposes a novel Context-wise Aggregation Operator (CWA) that captures the nuanced relationships between contexts and parameters in QNSS, providing a flexible aggregation mechanism that not only accounts for the varying importance of different contexts but also emphasizes the multiplicative relationships between membership values. Our framework presents neutrosophic best-worst method to compute criteria weights by ensuring more diverse and well-distributed criteria values and introduces a regularization-based spread maximization function to prevent weight convergence and ensure proper consistency handling through a nonlinear optimization model. Then, a customized fuzzy ARAS is computed to assess and rank the different playing strategies. Further, we introduce a real case study on European volleyball championship for senior men's national teams in Europe, in which decision-makers. Proof of concept analysis is conducted on real case studies validated to the advantages of the proposed approach, and compared the methods against state-of-the-art studies, implying insightful boosting to the opponent analysis and game planning.