The aim was to assess factor structure of player-reported fatigue and quantify within-subjects association between changes in training load measures and next day player-reported fatigue at different time points of an elite football season. Using longitudinal research design, twenty-four professional footballers, mean (SD) age of 25.7 (3.4) years, were monitored during their competitive season, including pre-season. Player-reported fatigue data and session ratings of perceived exertion (session-RPE) were collected via a mobile application. Player’s Heart rate (HR) and global positioning system (GPS) data were collected daily for each player in field sessions. Principal component analysis (PCA) indicated three components with Eigenvalues above 1.0; “soreness”, “mood, and “hydration”. Within-player correlations between training load values and next day player-reported fatigue values were trivial to moderate (r ≈ −0.42 to −0.04). In-season we observed large correlations between Total Distance (TD) and PlayerLoad with Soreness (r = −0.55, 95% CI: −0.62 to −0.46; r = −.054, 95% CI: −0.62 to −0.46), but during pre-season, correlations were small (r = −0.15, 95% CI: −0.28 to −0.01; r = −0.13, 95% CI: −0.26 to 0.01). The HR TRIMP, TD and session-RPE measures each showed trivial to moderate correlations (r ≈ −0.41 to −0.08) with next day “mood”. Our in-house player-reported fatigue questionnaire was sensitive to the multi-dimensional nature of fatigue, identifying physiological (soreness), psychological (mood and stress) and nutritional (hydration and nutrition) components. We found the in-season correlations with training load to be greater than previously reported in the literature, specifically with next day player-reported “soreness”. Nevertheless, the correlations between the items of our scale and pre-season training load were small.

目的是评估运动员报告的疲劳的因素结构，并量化训练负荷量度的变化与第二天运动员报告的疲劳在精英足球赛季的不同时间点之间的受试者内部关联。使用纵向研究设计，在包括赛季前在内的整个比赛赛季中，对24名平均（SD）年龄为25.7（3.4）岁的职业足球运动员进行了监测。玩家报告的疲劳数据和感知劳累的会话等级（session-RPE）是通过移动应用程序收集的。每天在野外训练中为每个玩家收集玩家的心率（HR）和全球定位系统（GPS）数据。主成分分析（PCA）表明特征值大于1.0的三个成分；“酸痛”，“情绪和水分”。训练负荷值与第二天运动员报告的疲劳值之间的运动员内部相关性从微不足道到中等（r≈-0.42至-0.04）。在赛季中，我们观察到总距离（TD）和带有荷重的PlayerLoad之间存在很大的相关性（r = -0.55，95％CI：-0.62至-0.46； r = -.054，95％CI：-0.62至-0.46），但在季前赛期间，相关性很小（r = -0.15，95％CI：-0.28至-0.01； r ​​= -0.13，95％CI：-0.26至0.01）。HR TRIMP，TD和会话RPE度量均显示与第二天的“情绪”无关紧要（r≈-0.41至-0.08）。我们内部玩家报告的疲劳调查表对疲劳的多维性质敏感，可以识别生理（酸痛），心理（情绪和压力）和营养（水分和营养）成分。我们发现与训练负荷的季节内相关性要比文献中先前报道的要大，尤其是第二天玩家报告的“痛感”。然而，我们的量表项目与季前训练负荷之间的相关性很小。