Year: 2025
Type: article
Study design: Systematic Review
Abstract: Graph theory, a robust mathematical framework, has emerged as a cornerstone for modeling intricate relationships and patterns inherent in team sports dynamics. This review illustrates the outcomes of a comprehensive Systematic Mapping Study (SMS) conducted to investigate the adoption of graph-based representations, models, and approaches that research groups employ to handle data and information in major team sports analytics. We systematically categorize and map the outlook of diverse graph-based approaches and models, shedding light on their applications, methodologies, and contributions to the ever-evolving field of sports analytics. The results of our study provide a comprehensive overview of the maturation and diversification of methodologies, providing insights into emerging trends. As well we also identify and thoroughly discuss potential research gaps. The present work aims to serve as a valuable reference resource for researchers, practitioners, and enthusiasts seeking to navigate the rich tapestry of graph-based knowledge representation in major team sports analytics. The code to execute the SMS is available at https://github.com/crusso7/systematicmappingstudy
Source: ACM Computing Surveys
DOI: 10.1145/3773024
Institution: University of Naples Federico II
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4415505967