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Journal . 2025
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2025
License: CC BY
Data sources: Datacite
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AI IN SPORTS: AN EXTENSIVE REVIEW

Authors: Ms. Sawant S.A.;

AI IN SPORTS: AN EXTENSIVE REVIEW

Abstract

Artificial intelligence (AI) has become an important part of modern sports and is changing the way athletes train, recover, and perform in competitions. In earlier years, coaches relied mainly on their personal experience, visual observation, and manual methods to evaluate athletes. Today, AI allows coaches and players to use scientific data to measure movement patterns, body stress, fatigue levels, and technique with high accuracy. AI tools such as video analysis, wearable sensors, biomechanics software, tracking cameras, and machine learning systems help athletes improve skills, avoid injuries, and receive personalized training programs. Many studies report that AI reduces injury risk, improves decision-making, increases training efficiency, and enhances overall performance by 20–25 percent. This paper reviews the role of AI in sports, explains examples from football, cricket, and American sports, and discusses its impact on training, safety, and the future of sports science. The paper also explores limitations, ethical challenges, and future possibilities such as AI coaches, digital twin athletes, VR-based training, and genetic prediction models. The purpose is to present a simple and clear understanding of how AI supports athletes and transforms sports at all levels.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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