Department of Psychology, Sport and Exercise, School of Social Sciences, Humanities and Law, Teesside University, Middlesbrough, UK.
Sport Science and Medical Department, Hartlepool United Football Club, Hartlepool, UK.
Sports Med. 2018 Mar;48(3):641-658. doi: 10.1007/s40279-017-0830-z.
The associations between internal and external measures of training load and intensity are important in understanding the training process and the validity of specific internal measures.
We aimed to provide meta-analytic estimates of the relationships, as determined by a correlation coefficient, between internal and external measures of load and intensity during team-sport training and competition. A further aim was to examine the moderating effects of training mode on these relationships.
We searched six electronic databases (Scopus, Web of Science, PubMed, MEDLINE, SPORTDiscus, CINAHL) for original research articles published up to September 2017. A Boolean search phrase was created to include search terms relevant to team-sport athletes (population; 37 keywords), internal load (dependent variable; 35 keywords), and external load (independent variable; 81 keywords). Articles were considered for meta-analysis when a correlation coefficient describing the association between at least one internal and one external measure of session load or intensity, measured in the time or frequency domain, was obtained from team-sport athletes during normal training or match-play (i.e., unstructured observational study). The final data sample included 122 estimates from 13 independent studies describing 15 unique relationships between three internal and nine external measures of load and intensity. This sample included 295 athletes and 10,418 individual session observations. Internal measures were session ratings of perceived exertion (sRPE), sRPE training load (sRPE-TL), and heart-rate-derived training impulse (TRIMP). External measures were total distance (TD), the distance covered at high and very high speeds (HSRD ≥ 13.1-15.0 km h and VHSRD ≥ 16.9-19.8 km h, respectively), accelerometer load (AL), and the number of sustained impacts (Impacts > 2-5 G). Distinct training modes were identified as either mixed (reference condition), skills, metabolic, or neuromuscular. Separate random effects meta-analyses were conducted for each dataset (n = 15) to determine the pooled relationships between internal and external measures of load and intensity. The moderating effects of training mode were examined using random-effects meta-regression for datasets with at least ten estimates (n = 4). Magnitude-based inferences were used to interpret analyses outcomes.
During all training modes combined, the external load relationships for sRPE-TL were possibly very large with TD [r = 0.79; 90% confidence interval (CI) 0.74 to 0.83], possibly large with AL (r = 0.63; 90% CI 0.54 to 0.70) and Impacts (r = 0.57; 90% CI 0.47 to 0.64), and likely moderate with HSRD (r = 0.47; 90% CI 0.32 to 0.59). The relationship between TRIMP and AL was possibly large (r = 0.54; 90% CI 0.40 to 0.66). All other relationships were unclear or not possible to infer (r range 0.17-0.74, n = 10 datasets). Between-estimate heterogeneity [standard deviations (SDs) representing unexplained variation; τ] in the pooled internal-external relationships were trivial to extremely large for sRPE (τ range = 0.00-0.47), small to large for sRPE-TL (τ range = 0.07-0.31), and trivial to moderate for TRIMP (τ range= 0.00-0.17). The internal-external load relationships during mixed training were possibly very large for sRPE-TL with TD (r = 0.82; 90% CI 0.75 to 0.87) and AL (r = 0.81; 90% CI 0.74 to 0.86), and TRIMP with AL (r = 0.72; 90% CI 0.55 to 0.84), and possibly large for sRPE-TL with HSRD (r = 0.65; 90% CI 0.44 to 0.80). A reduction in these correlation magnitudes was evident for all other training modes (range of the change in r when compared with mixed training - 0.08 to - 0.58), with these differences being unclear to possibly large. Training mode explained 24-100% of the between-estimate variance in the internal-external load relationships.
Measures of internal load derived from perceived exertion and heart rate show consistently positive associations with running- and accelerometer-derived external loads and intensity during team-sport training and competition, but the magnitude and uncertainty of these relationships are measure and training mode dependent.
了解训练过程和特定内部指标的有效性，内部和外部负荷及强度指标之间的关联非常重要。
我们旨在提供元分析估计值，这些估计值由团队运动训练和比赛期间负荷和强度的内部和外部指标之间的相关系数决定。进一步的目的是检查训练模式对这些关系的调节作用。
我们在截至 2017 年 9 月的时间内，通过搜索六个电子数据库（Scopus、Web of Science、PubMed、MEDLINE、SPORTDiscus 和 CINAHL），搜索了有关团队运动运动员的原始研究文章（人群；37 个关键词）、内部负荷（因变量；35 个关键词）和外部负荷（自变量；81 个关键词）。当从正常训练或比赛中（即非结构化观察研究）获得至少一个内部和一个外部的关于会话负荷或强度的指标的关联时，文章被认为可以进行元分析。来自 13 项独立研究的 122 个估计值包含了 3 个内部和 9 个外部负荷和强度指标之间的 15 个独特关系。这个样本包括 295 名运动员和 10418 个个体会话观察。内部指标是自我感觉用力评分（sRPE）、sRPE 训练负荷（sRPE-TL）和心率衍生的训练冲击（TRIMP）。外部指标是总距离（TD）、高速和非常高速（HSRD≥13.1-15.0km/h 和 VHSRD≥16.9-19.8km/h）覆盖的距离、加速度计负荷（AL）和持续冲击的次数（Impacts＞2-5G）。不同的训练模式被确定为混合（参考条件）、技能、代谢或神经肌肉。对每个数据集（n=15）分别进行了随机效应元分析，以确定内部和外部负荷和强度指标之间的综合关系。使用随机效应元回归检查了训练模式对至少有十个估计值的数据集（n=4）的调节作用。基于幅度的推断用于解释分析结果。
在所有训练模式的组合中，sRPE-TL 的外部负荷关系可能是非常大的，与 TD 呈高度相关（r=0.79；90%置信区间[CI]0.74-0.83），可能与 AL（r=0.63；90%CI0.54-0.70）和 Impacts（r=0.57；90%CI0.47-0.64）呈中度相关，可能与 HSRD（r=0.47；90%CI0.32-0.59）呈低度相关。TRIMP 与 AL 的关系可能是中度的（r=0.54；90%CI0.40-0.66）。其他所有关系都不清楚或无法推断（r 范围为 0.17-0.74，n=10 个数据集）。内部-外部关系的组内异质性[表示无法解释的变异的标准差（SD）；τ]对于 sRPE 为微小到非常大（τ 范围=0.00-0.47），对于 sRPE-TL 为小到中（τ 范围=0.07-0.31），对于 TRIMP 为微小到中度（τ 范围=0.00-0.17）。混合训练期间的内部-外部负荷关系对于 sRPE-TL 与 TD（r=0.82；90%CI0.75-0.87）和 AL（r=0.81；90%CI0.74-0.86）以及 TRIMP 与 AL（r=0.72；90%CI0.55-0.84）呈非常大，对于 sRPE-TL 与 HSRD（r=0.65；90%CI0.44-0.80）呈大。与混合训练相比，所有其他训练模式的这些相关性幅度都有所减小（与混合训练相比，r 的变化范围为-0.08 至-0.58），这些差异不太清楚或可能较大。训练模式解释了内部-外部负荷关系中 24%-100%的组内变异。
来自自我感觉用力和心率的内部负荷指标与团队运动训练和比赛期间的跑步和加速度计负荷和强度呈一致的正相关，但这些关系的大小和不确定性取决于指标和训练模式。
