Sport Analytics in Tactical Decision-Making: Integration of GPS Data, Player Tracking, and Artificial Intelligence in Football

Abstract

The rapid development of sports technology has fundamentally transformed how football clubs analyze performance and make tactical decisions. This study investigates the integration of Global Positioning System (GPS) data, player tracking technology, and artificial intelligence (AI) in supporting tactical decision-making in professional football. Conducted at the Faculty of Sports and Health Sciences, Universitas Negeri Makassar, this research employed a mixed-method approach involving quantitative analysis of player movement data and qualitative examination of coaches' tactical interpretations. Data were collected from 22 active football players monitored across 12 competitive matches using GPS wearable devices and optical tracking cameras, supplemented by semi-structured interviews with five certified football coaches. The findings reveal that the implementation of integrated sport analytics significantly improved tactical decision-making accuracy by 34.7%, increased player high-intensity distance coverage by an average of 18.3% across measured sessions, and reduced coach decision-making time by approximately 27.5% during halftime intervals. The AI-powered predictive models demonstrated 82.4% accuracy in anticipating opposing team formations. These results confirm that the convergence of GPS technology, player tracking systems, and machine learning algorithms provides a powerful analytical framework that enhances both individual player assessment and team tactical management in football. The study concludes that sport analytics represents an indispensable component of modern football management and provides evidence-based recommendations for Indonesian football institutions seeking to adopt data-driven approaches