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The use of GPS data has become an integral part of the work of strength and conditioning coaches as well as data analysts in professional women's and men's football. Coaches should rely on GPS systems with a comparatively high sampling frequency (18 Hz) in order to validly capture short sprint distances with rapid changes of direction. GPS parameters such as total running distance, number of maximal sprints, accelerations, decelerations, and distance covered in speed and high-speed zones are of high practical relevance for athletic performance and injury prevention. Based on these practically relevant GPS parameters, the central challenge lies in capturing the complex interaction between training load and exertion, and in deriving suitable implications for short- (microcycle), medium- (mesocycle), and long-term (macrocycle) training programming. In the future, AI methods may support this process by efficiently analyzing large datasets and identifying patterns in load management. Initial studies provide promising evidence. However, particularly in the highly individualized context of professional football, it remains to be determined whether existing learning algorithms developed from one team's data can be transferred to other teams. In general, the use of GPS data should be contextualized in order to provide coaches with guidance, rather than serving as rigid target parameters for training prescription and load management in football. This article presents literature-based recommendations on the use of GPS data (e.g., acceleration-based parameters) for the design of macro-, meso-, and microcycles, which can guide coaches in football-specific load management. Of additional practical importance is the further development of models capable of predicting increased injury risk during specific phases of the season. While existing approaches such as the Acute:Chronic Workload Ratio (ACWR) provide initial guidance, their methodological limitations are evident. Further research is needed to provide reliable and applicable tools for training management in professional football. In addition, individualized training programming should incorporate not only objective GPS data but also subjective ratings of perceived exertion.