Estimating individual contributions to team success in women’s college volleyball

Powers Scott (), Stancil Luke and Consiglio Naomi
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Powers Scott: 3990 Department of Sport Management , Rice University, Houston, TX, USA
Stancil Luke: Department of Computational Applied Mathematics and Operations Research, Rice University, Houston, TX, USA
Consiglio Naomi: 3990 Department of Sport Management , Rice University, Houston, TX, USA

Journal of Quantitative Analysis in Sports, 2025, vol. 21, issue 2, 117-135

Abstract: The progression of a single point in volleyball starts with a serve and then alternates between teams, each team allowed up to three contacts with the ball. Using charted data from the 2022 NCAA Division I women’s volleyball season (4,147 matches, 600,000+ points, more than 5 million recorded contacts), we model the progression of a point as a Markov chain with the state space defined by the sequence of contacts in the current possession. We estimate the probability of each team winning the point, which changes on each contact. We attribute changes in point probability to the player(s) responsible for each contact, facilitating measurement of performance on the same point scale for different skills. Traditional volleyball statistics do not allow apples-to-apples comparisons across skills, and they do not measure the impact of the performances on team success. For adversarial contact groups (serve/reception and set/attack/block/dig), we estimate a hierarchical linear model for the outcome, with random effects for the players involved; and we adjust performance for strength of schedule not only on the conference/team level but on the individual player level. We can use the results to answer practical questions for volleyball coaches.

Keywords: Markov chain; random-effect linear model; player evaluation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1515/jqas-2024-0038

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