Next-Gen Coaching: IoT and Linear Regression for Adaptive Training Load Management

With the growth of data analytics and Internet of Things (IoT) devices, the world of sports coaching is also transforming due to the continuous evolution of technology. This paper shows how athletes might benefit from adaptive training load management using IoT sensors and linear regression (LR) analysis. Athletes' performance, physiology, and environmental variables may be studied in detail with the help of IoT devices like smart gear and wearable sensors. Coaches may create individualized training plans for their athletes by combining this data with advanced analytics tools like linear regression. LR models will examine how different training parameters relate to performance results. Coaches may dynamically alter training loads in real time by creating prediction models based on past data to improve performance, reduce injuries, and promote overall athlete well-being. In addition, with the help of IoT technology, coaches can monitor their players' physical health and recuperation status in real-time, whether exercising or going about their everyday lives. The efficacy of training programs may be maximized by coaches making informed decisions about training intensity, volume, and recuperation procedures using this real-time feedback loop. It allows unprecedented personalization and flexibility in training load management, making it a potential approach to next-generation coaching. With data-driven insights, coaches can help their athletes perform at their best without putting them in danger of injury or overtraining.