AI and Data Science in Sports Analytics
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: 30 June 2026 | Viewed by 128
Special Issue Editors
Interests: sports analytics; data mining; data science; machine learning; artificial intelligence
Special Issue Information
Dear Colleagues,
(1) Introduction
Sports analytics has transformed the way athletes train, compete, and recover. The integration of data science, machine learning, and artificial intelligence (AI) in sports provides valuable insights into performance optimization, injury prevention, and tactical decision-making. With the increasing availability of advanced performance metrics, sensor data, wearable technology, and video analysis, the application of big data analytics in sports has gained significant traction. These advancements contribute to more precise performance assessment, personalized training programs, and enhanced forecasting models for game outcomes and player evaluation.
The importance of this research area is underscored by the growing demand for data-driven methodologies in professional and amateur sports. Teams, coaches, and medical professionals now rely on predictive analytics to optimize training loads, reduce injury risks, and refine in-game strategies. Despite these developments, challenges remain in data collection, interpretation, and ethical considerations. This Special Issue seeks to address these challenges by exploring cutting-edge methodologies and applications in sports analytics.
(2) Aim of the Special Issue
This Special Issue aims to gather innovative research that leverages data science techniques to advance sports analytics. By focusing on big data, AI, and machine learning applications, this Special Issue aligns with the broader scope of Big Data and Cognitive Computing (BDCC), which emphasizes computational intelligence, cognitive computing, and data-driven decision-making.
Contributions to this Special Issue will not only enhance scientific knowledge in sports analytics, but also bridge the gap between academia and industry, offering real-world applications for performance enhancement, forecasting, and injury prevention. We welcome original research and review articles that explore novel data-driven approaches, predictive modeling techniques, and the ethical implications of AI in sports.
(3) Suggested Themes
We invite contributions covering a wide range of topics, including but not limited to the following:
- Performance Analytics: Data-driven performance evaluation, real-time monitoring, and optimization strategies.
- Injury Prevention and Rehabilitation: Predictive modeling for injury risk assessment, recovery tracking, and return-to-play protocols.
- Game Strategy and Tactical Analysis: AI-powered decision-making, opponent scouting, and play pattern recognition.
- Wearable Technology and Sensor Data: The role of IoT devices and biometric data in athlete monitoring.
- Big Data and Machine Learning in Sports: Applications of deep learning, reinforcement learning, and advanced analytics.
- Sports Forecasting and Betting Analytics: Predictive modeling for game outcomes, player performance, and market trends.
- Ethical and Privacy Considerations in Sports Analytics: Responsible AI usage, data privacy, and athlete consent.
We look forward to receiving your contributions.
Dr. Vangelis Sarlis
Prof. Dr. Christos Tjortjis
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- sports analytics
- big data in sports
- machine learning
- performance optimization
- injury prevention
- predictive modeling
- wearable technology
- game strategy analysis
- AI in sports
- sports forecasting
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