Sports Coaching College, Beijing Sport University, Beijing 100084, China.
School of Physical Education, Qingdao University, Qingdao 266071, China.
Int J Environ Res Public Health. 2022 Oct 14;19(20):13237. doi: 10.3390/ijerph192013237.
The number of studies on the relationship between training and competition load and injury has increased exponentially in recent years, and it is also widely studied by researchers in the field of professional soccer. In order to provide practical guidance for workload management and injury prevention in professional athletes, this study provides a review of the literature on the effect of load on injury risk, injury prediction, and interpretation mechanisms. The results of the research show that: (1) It appears that short-term fixture congestion may increase the match injury incidence, while long-term fixture congestion may have no effect on both the overall injury incidence and the match injury incidence. (2) It is impossible to determine conclusively whether any global positioning system (GPS)-derived metrics (total distance, high-speed running distance, and acceleration) are associated with an increased risk of injury. (3) The acute:chronic workload ratio (ACWR) of the session rating of perceived exertion (s-RPE) may be significantly associated with the risk of non-contact injuries, but an ACWR threshold with a minimum risk of injury could not be obtained. (4) Based on the workload and fatigue recovery factors, artificial intelligence technology may possess good predictive power regarding injury risk.
近年来,关于训练和比赛负荷与损伤之间关系的研究数量呈指数级增长,这也是职业足球领域研究人员广泛研究的课题。为了为职业运动员的工作量管理和损伤预防提供实际指导,本研究对负荷对损伤风险、损伤预测和解释机制的影响进行了文献回顾。研究结果表明:(1)短期赛程密集可能会增加比赛受伤的发生率,而长期赛程密集对总受伤发生率和比赛受伤发生率均无影响。(2)无法确定任何基于全球定位系统(GPS)的衍生指标(总距离、高速跑动距离和加速度)是否与受伤风险增加有关。(3)感知用力的会话等级评分(s-RPE)的急性:慢性工作量比(ACWR)可能与非接触性损伤的风险显著相关,但无法获得具有最小损伤风险的 ACWR 阈值。(4)基于工作量和疲劳恢复因素,人工智能技术可能对损伤风险具有良好的预测能力。
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