ReviewSensors (Basel, Switzerland)2024
Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management.
Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Application of Artificial Intelligence for Predicting Sports Injuries and Customizing Personalized Prevention Strategies: A Scoping Review.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial Intelligence is a Useful Tool in Exercise Science and Sports Medicine.Medicine and science in sports and exercise · 2026Article
- Development and validation of an AI use scale for sport and exercise science students.Scientific reports · 2026Article
- Winning beyond scoring: an explainable machine learning framework for identifying key performance indicators in the Chinese Basketball Association.BMC sports science, medicine & rehabilitation · 2026Article
- Wearable Biosensing and Machine Learning for Data-Driven Training and Coaching Support.Biosensors · 2026Review
- Artificial intelligence and wearables in sport: performance, injury risk, and wellbeing.Frontiers in artificial intelligence · 2026Review
- Micro-recovery dosing in elite sport: an initiative-taking, organization-wide recovery framework.Frontiers in physiology · 2026Article
- Special Issue "Applications of Machine Learning in Sports Medicine, Physical Activity, Posture, and Rehabilitation".Journal of functional morphology and kinesiology · 2025Article
- Intelligent strength training for football players using resnext optimized by upgraded chimp optimization algorithm.Scientific reports · 2025Article
- Tracking key metrics: fluctuations in external and internal load across game quarters in collegiate basketball players.BMC sports science, medicine & rehabilitation · 2025Article
- Physical Workload Patterns in U-18 Basketball Using LPS and MEMS Data: A Principal Component Analysis by Quarter and Playing Position.Sensors (Basel, Switzerland) · 2025Article
- Validity and Reliability of a Novel AI-Based System in Athletic Performance Assessment: The Case of DeepSport.Sensors (Basel, Switzerland) · 2025Article
- Understanding Acceleration-Based Load Metrics: From Concepts to Implementation.Sensors (Basel, Switzerland) · 2025Review
- Enhancing table tennis performance and physical fitness through digital technology: a quasi-experimental study based on the TPACK framework.Frontiers in sports and active living · 2025Article
- Sports Industry 5.0: reimagining sport through technology, humanity, and sustainability.Frontiers in sports and active living · 2025Review
- Algorithmic fandom: how generative AI is reshaping sports marketing, fan engagement, and the integrity of sport.Frontiers in sports and active living · 2025Article
- Visio-spatial intelligence skills in non-athletes versus amateur boxers.Medical hypothesis, discovery & innovation ophthalmology journal · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Artificial Intelligence (AI) is transforming the field of sports science by providing unprecedented insights and tools that enhance training, performance, and health management. This work examines how AI is advancing the role of sports scientists, particularly in team sports environments, by improving training load management, sports performance, and player well-being. It explores key dimensions such as load optimization, injury prevention and return-to-play, sports performance, talent identification and scouting, off-training behavior, sleep quality, and menstrual cycle management. Practical examples illustrate how AI applications have significantly advanced each area and how they support and enhance the effectiveness of sports scientists. This manuscript also underscores the importance of ensuring that AI technologies are context-specific and communicated transparently. Additionally, it calls for academic institutions to update their curriculums with AI-focused education, preparing future sports professionals to fully harness its potential. Finally, the manuscript addresses future challenges, such as the unpredictable nature of team sports, emphasizing the need for interdisciplinary collaboration, including clear communication and mutual understanding between sports scientists and AI experts, and the critical balance between AI-driven insights and human expertise.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.