Manzi Vincenzo, Savoia Cristian, Padua Elvira, Edriss Saeid, Iellamo Ferdinando, Caminiti Giuseppe, Annino Giuseppe
Department of Humanities Science, Pegaso Open University, Naples, Italy.
The Research Institute for Sport and Exercise Sciences, The Tom Reilly Building, Liverpool John Moores University, Liverpool, England, United Kingdom.
Front Physiol. 2023 Oct 24;14:1230912. doi: 10.3389/fphys.2023.1230912. eCollection 2023.
This study aimed to explore the interplay between metabolic power (MP) and equivalent distance (ED) and their respective roles in training games (TGs) and official soccer matches. Furthermore, the secondary objective was to investigate the connection between external training load (ETL), determined by the interplay of metabolic power and equivalent distance, and internal training load (ITL) assessed through HR-based methods, serving as a measure of criterion validity. Twenty-one elite professional male soccer players participated in the study. Players were monitored during 11 months of full training and overall official matches. The study used a dataset of 4269 training games and 380 official matches split into training and test sets. In terms of machine learning methods, the study applied several techniques, including K-Nearest Neighbors, Decision Tree, Random Forest, and Support-Vector Machine classifiers. The dataset was divided into two subsets: a training set used for model training and a test set used for evaluation. Based on metabolic power and equivalent distance, the study successfully employed four machine learning methods to accurately distinguish between the two types of soccer activities: TGs and official matches. The area under the curve (AUC) values ranged from 0.90 to 0.96, demonstrating high discriminatory power, with accuracy levels ranging from 0.89 to 0.98. Furthermore, the significant correlations observed between Edwards' training load (TL) and TL calculated from metabolic power metrics confirm the validity of these variables in assessing external training load in soccer. The correlation coefficients (r values) ranged from 0.59 to 0.87, all reaching statistical significance at < 0.001. These results underscore the critical importance of investigating the interaction between metabolic power and equivalent distance in soccer. While the overall intensity may appear similar between TGs and official matches, it is evident that underlying factors contributing to this intensity differ significantly. This highlights the necessity for more comprehensive analyses of the specific elements influencing physical effort during these activities. By addressing this fundamental aspect, this study contributes valuable insights to the field of sports science, aiding in the development of tailored training programs and strategies that can optimize player performance and reduce the risk of injuries in elite soccer.
本研究旨在探讨代谢功率（MP）与等效距离（ED）之间的相互作用及其在训练赛（TGs）和正式足球比赛中的各自作用。此外，次要目标是研究由代谢功率和等效距离的相互作用所确定的外部训练负荷（ETL）与通过基于心率的方法评估的内部训练负荷（ITL）之间的联系，以此作为标准效度的一种衡量。21名精英职业男性足球运动员参与了该研究。在11个月的全面训练和所有正式比赛期间对球员进行了监测。该研究使用了一个包含4269场训练赛和380场正式比赛的数据集，这些数据被分为训练集和测试集。在机器学习方法方面，该研究应用了多种技术，包括K近邻、决策树、随机森林和支持向量机分类器。数据集被分为两个子集：一个用于模型训练的训练集和一个用于评估的测试集。基于代谢功率和等效距离，该研究成功地运用了四种机器学习方法来准确区分两种足球活动类型：训练赛和正式比赛。曲线下面积（AUC）值在0.90至0.96之间，显示出高辨别力，准确率在0.89至0.98之间。此外，观察到的爱德华兹训练负荷（TL）与根据代谢功率指标计算得出的TL之间的显著相关性证实了这些变量在评估足球外部训练负荷方面的有效性。相关系数（r值）在0.59至0.87之间，均在<0.001时达到统计学显著性。这些结果强调了研究足球中代谢功率与等效距离之间相互作用的至关重要性。虽然训练赛和正式比赛之间的总体强度可能看起来相似，但显然导致这种强度的潜在因素有显著差异。这凸显了对影响这些活动中体力消耗的具体因素进行更全面分析的必要性。通过解决这一基本问题，本研究为体育科学领域提供了有价值的见解，有助于制定可优化精英足球运动员表现并降低受伤风险的定制训练计划和策略。
