AI and analytics in sports: Leveraging BERTopic to map the past and chart the future
- URL: http://arxiv.org/abs/2510.15487v1
- Date: Fri, 17 Oct 2025 09:57:42 GMT
- Title: AI and analytics in sports: Leveraging BERTopic to map the past and chart the future
- Authors: Manit Mishra,
- Abstract summary: We identify 204 journal articles pertaining to utilization of AI and analytics in sports published during 2002 to 2024.<n>We follow it up with extraction of the latent topics by leveraging the topic modelling technique of BERTopic.<n>The study offers insights to academicians and sports administrators on transformational impact of AI and analytics in sports.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Purpose: The purpose of this study is to map the body of scholarly literature at the intersection of artificial intelligence (AI), analytics and sports and thereafter, leverage the insights generated to chart guideposts for future research. Design/methodology/approach: The study carries out systematic literature review (SLR). Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol is leveraged to identify 204 journal articles pertaining to utilization of AI and analytics in sports published during 2002 to 2024. We follow it up with extraction of the latent topics from sampled articles by leveraging the topic modelling technique of BERTopic. Findings: The study identifies the following as predominant areas of extant research on usage of AI and analytics in sports: performance modelling, physical and mental health, social media sentiment analysis, and tactical tracking. Each extracted topic is further examined in terms of its relative prominence, representative studies, and key term associations. Drawing on these insights, the study delineates promising avenues for future inquiry. Research limitations/implications: The study offers insights to academicians and sports administrators on transformational impact of AI and analytics in sports. Originality/value: The study introduces BERTopic as a novel approach for extracting latent structures in sports research, thereby advancing both scholarly understanding and the methodological toolkit of the field.
Related papers
- A Data-Driven Analysis for Engineering Conferences: The Institute of Industrial and Systems Engineering (IISE) Annual Conference Proceedings (2002-2025) [0.0]
This paper presents a computational analysis of IISE proceedings from 2002 to 2025.<n>We map thematic evolution to identify dominant, emerging, and receding research topics.<n>The findings illuminate the field's intellectual assets and provide a data-informed map to guide the future of ISE.
arXiv Detail & Related papers (2026-02-28T01:10:46Z) - Large-Scale Multidimensional Knowledge Profiling of Scientific Literature [46.15403461273178]
We compile a unified corpus of more than 100,000 papers from 22 major conferences between 2020 and 2025.<n>Our analysis highlights several notable shifts, including the growth of safety, multimodal reasoning, and agent-oriented studies.<n>These findings provide an evidence-based view of how AI research is evolving and offer a resource for understanding broader trends and identifying emerging directions.
arXiv Detail & Related papers (2026-01-21T16:47:05Z) - Artificial Intelligence and Journalism: A Systematic Bibliometric and Thematic Analysis of Global Research [0.51795041186793]
This study presents a comprehensive systematic review of published articles on AI in journalism from 2010 to 2025.<n>The findings show a sharp increase in research activity after 2020, with prominent focus areas including automation, misinformation, and ethical governance.<n>The review also highlights regional disparities in scholarly contributions, with limited representation from the Global South.
arXiv Detail & Related papers (2025-07-15T01:11:39Z) - Trends and Challenges in Authorship Analysis: A Review of ML, DL, and LLM Approaches [1.8686807993563161]
Authorship analysis plays an important role in diverse domains, including forensic linguistics, academia, cybersecurity, and digital content authentication.<n>This paper presents a systematic literature review on two key sub-tasks of authorship analysis; Author Attribution and Author Verification.
arXiv Detail & Related papers (2025-05-21T12:06:08Z) - VizCV: AI-assisted visualization of researchers' publications tracks [7.233541652625401]
VizCV is a novel web-based end-to-end visual analytics framework.<n>It incorporates AI-assisted analysis and supports automated reporting of career evolution.
arXiv Detail & Related papers (2025-05-13T15:47:59Z) - Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation [58.064940977804596]
A plethora of new AI models and tools has been proposed, promising to empower researchers and academics worldwide to conduct their research more effectively and efficiently.<n>Ethical concerns regarding shortcomings of these tools and potential for misuse take a particularly prominent place in our discussion.
arXiv Detail & Related papers (2025-02-07T18:26:45Z) - Ontology Embedding: A Survey of Methods, Applications and Resources [54.3453925775069]
Onologies are widely used for representing domain knowledge and meta data.<n> logical reasoning that can directly support are quite limited in learning, approximation and prediction.<n>One straightforward solution is to integrate statistical analysis and machine learning.
arXiv Detail & Related papers (2024-06-16T14:49:19Z) - Unleashing the Power of AI. A Systematic Review of Cutting-Edge Techniques in AI-Enhanced Scientometrics, Webometrics, and Bibliometrics [1.2374541748245838]
The study aims to analyze the synergy of Artificial Intelligence (AI) with scientometrics, webometrics, and bibliometrics.
Our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication.
arXiv Detail & Related papers (2024-02-22T15:10:02Z) - A Literature Review of Literature Reviews in Pattern Analysis and Machine Intelligence [51.26815896167173]
We present a comprehensive tertiary analysis of PAMI reviews along three complementary dimensions.<n>Our analyses reveal distinctive organizational patterns as well as persistent gaps in current review practices.<n>Finally, our evaluation of state-of-the-art AI-generated reviews indicates encouraging advances in coherence and organization.
arXiv Detail & Related papers (2024-02-20T11:28:50Z) - Textual Analysis of ICALEPCS and IPAC Conference Proceedings: Revealing
Research Trends, Topics, and Collaborations for Future Insights and Advanced
Search [2.1792283995628465]
We use natural language processing techniques to extract meaningful information from the abstracts and papers of past conference proceedings.
We extract topics to visualize and identify trends, analyze their evolution to identify emerging research directions, and highlight interesting publications.
arXiv Detail & Related papers (2023-10-13T08:55:19Z) - Artificial Intelligence in Concrete Materials: A Scientometric View [77.34726150561087]
This chapter aims to uncover the main research interests and knowledge structure of the existing literature on AI for concrete materials.
To begin with, a total of 389 journal articles published from 1990 to 2020 were retrieved from the Web of Science.
Scientometric tools such as keyword co-occurrence analysis and documentation co-citation analysis were adopted to quantify features and characteristics of the research field.
arXiv Detail & Related papers (2022-09-17T18:24:56Z) - Characterising Research Areas in the field of AI [68.8204255655161]
We identified the main conceptual themes by performing clustering analysis on the co-occurrence network of topics.
The results highlight the growing academic interest in research themes like deep learning, machine learning, and internet of things.
arXiv Detail & Related papers (2022-05-26T16:30:30Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.