Exploration of the path of digital technology empowering the sustainable development of alumni football—a study based on ordinal logistic regression analysis

Introduction In the digital era, professional sports have rapidly embraced technologies such as big data, AI, and the Internet of Things to optimize performance, strategy, and fan engagement. However, the digital transformation of grassroots and amateur level sports remains significantly underdeveloped, posing a major obstacle to the inclusive and sustainable growth of national sports ecosystems. Alumni football, participated in by a vast and growing population of college graduates in China, emerges as a strategic gateway to bridging this digital divide. Methods This study explores how digital technologies can empower the sustainable development of alumni football from the perspectives of data acquisition, processing, and application, with a focus on seven practical digital implementation scenarios. Using a questionnaire survey of 100 university football alumni and ordinal logistic regression analysis, ten digital factors were examined for their influence on alumni football development. Results The results show that factors such as digital business models and digital team culture significantly contribute to sustainable development, whereas elements like virtual coaching and match data management have relatively limited impact. Discussion This study not only addresses an urgent gap in digital grassroots sports integration but also provides replicable insights for policy makers, educators, and industry stakeholders aiming to promote large scale participation, cultural cohesion, and digital inclusion across broader segments of the sports domain.

• Publication year

  2025

• Venue

  Frontiers in Sports and Active Living

• Publication date

  2025-08-20

• Fields of study

  Medicine, Business, Education, Computer Science

• Identifiers
  DOI 10.3389/fspor.2025.1613339PMID 40909990PMCID 12406710
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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