Neural Networks for Real-Time Sports Analytics and Performance Prediction

Abstract

Neural networks are increasingly being applied in sports analytics to provide real-time insights into player performance, team strategies, and game outcomes. These AI-driven models are capable of processing large datasets from various sources, including player statistics, game footage, and biometric data, to predict performance and provide valuable decision support. This article explores the role of neural networks in real-time sports analytics, focusing on their applications in performance prediction, injury prevention, and tactical analysis. We also discuss the challenges and future opportunities for using AI to enhance sports performance and provide actionable insights for coaches, players, and analysts.