Prediction of Offensive Performance Factors in KOVO

This study aims to analyze the impact of foreign players on team offensive performance in the women’s professional volleyball league by forecasting offensive indicators of both top-ranked and bottom-ranked teams (attack success rate, attack efficiency, average serves per set, and average blocks per set), as well as those of their respective foreign players, including attack success rate, attack efficiency, attack share, average serves per set, and average blocks per set, using the time series analysis model NeuralProphet. The results demonstrate that offensive capability is a decisive factor in determining match outcomes, underscoring the critical role of foreign players’ technical and tactical competencies in enhancing team competitiveness. Furthermore, the findings indicate that bottom-ranked teams exhibit a high dependence on foreign players for offensive performance, suggesting the need to increase domestic player participation and diversify positional strategies to improve overall attack efficiency. By conducting a quantitative predictive study in a relatively underexplored area of volleyball research, this study provides data-driven insights that can serve as a foundation for team management, player recruitment, and tactical planning. Additionally, it contributes to the academic advancement of time series–based performance analysis in sports research.