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Abstract

The regulation of training loads, particularly for speed endurance, is crucial for optimizing physical fitness in football players. This is achieved by balancing external load components such as intensity, volume, and rest with internal load, as measured by heart rate. Such regulation has a precise impact on the level of specific physical fitness. This study focuses on the regulation of speed endurance training during the specialized preparation period, using artificial intelligence to assess its effects on selected physical fitness components and tactical behaviour in football players. The study utilizes Polar H10 sensors, which function effectively under various environmental conditions and interface with an iPad 8 device to measure heart rate, distance, energy, and power during performance and training. These sensors contribute to making the training process highly regulated and well-documented, providing an objective evaluation of physical load. By inputting player data into a pre-designed difficulty formula, the training load can be determined instantly, without the need to rely on time-consuming manual calculations that may be prone to human error, especially under fatigue or high-pressure conditions. In contrast, these AI-generated metrics are consistently reliable and free from human error. The researchers concluded that developing training programs based on modern technological devices equipped with artificial intelligence is essential, given their capacity to improve physical fitness parameters accurately-particularly speed endurance. The study further examines the influence of these technologies on the targeted physical fitness elements and tactical behaviour of players from Al-Qasim Sports Club in the Iraqi Professional League. and this achieves one of the sustainable development goals of the United Nations in Iraq which is (Quality Education).

First Page

265

Last Page

274

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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