AI in sports is transforming how athletes train, coaches prepare, and teams scout talent, redefining what counts as evidence and turning once-inferential decisions into data-informed practices that scale from youth academies to major league programs, while aligning performance incentives with verifiable metrics rather than intuition alone, and inviting players, clinicians, and analysts to collaborate in a shared, technology-enabled playbook that emphasizes consistency, safety, and measurable improvement.As data streams from wearables, video analysis, in-game sensors, and environmental trackers multiply, AI-driven insights—from machine learning for athlete performance to data-driven decision making in sports—are replacing guesswork with evidence, enabling near real-time optimization, personalized coaching, sequential trial-and-error testing, and the ability to simulate thousands of practice and competition scenarios before a single rep or game.