Int J Sports Physiol Perform. 2021 Jun 1;16(6):772-778. doi: 10.1123/ijspp.2020-0457. Epub 2021 Feb 4.
To compare weekly training and game demands according to playing position in basketball players.
A longitudinal, observational study was adopted. Semiprofessional, male basketball players categorized as backcourt (guards; n = 4) and frontcourt players (forwards/centers; n = 4) had their weekly workloads monitored across an entire season. External workload was determined using microsensors and included PlayerLoad™ (PL) and inertial movement analysis variables. Internal workload was determined using heart rate to calculate absolute and relative summated-heart-rate-zones workload and rating of perceived exertion (RPE) to calculate session-RPE workload. Comparisons between weekly training and game demands were made using linear mixed models and effect sizes in each positional group.
In backcourt players, higher relative PL (P = .04, very large) and relative summated-heart-rate-zones workload (P = .007, very large) were evident during training, while greater session-RPE workload (P = .001, very large) was apparent during games. In frontcourt players, greater PL (P < .001, very large), relative PL (P = .019, very large), peak PL intensities (P < .001, moderate), high-intensity inertial movement analysis events (P = .002, very large), total inertial movement analysis events (P < .001, very large), summated-heart-rate-zones workload (P < .001, very large), RPE (P < .001, very large), and session-RPE workload (P < .001, very large) were evident during games.
Backcourt players experienced similar demands between training and games across several variables, with higher average workload intensities during training. Frontcourt players experienced greater demands across all variables during games than training. These findings emphasize the need for position-specific preparation strategies leading into games in basketball teams.
根据篮球运动员的场上位置比较周训练和比赛的需求。
本研究采用纵向观察性研究。将半职业男性篮球运动员分为后卫（后卫；n = 4）和前场球员（前锋/中锋；n = 4），整个赛季对他们的每周工作量进行监测。使用微传感器确定外部工作量，包括 PlayerLoad™（PL）和惯性运动分析变量。使用心率确定内部工作量，以计算绝对和相对总和心率区工作量和感知用力等级（RPE）以计算会话-RPE 工作量。使用线性混合模型和每个位置组的效应量比较每周训练和比赛需求。
在后卫中，训练时相对 PL（P =.04，非常大）和相对总和心率区工作量（P =.007，非常大）较高，而比赛时会话-RPE 工作量（P =.001，非常大）较高。在前锋中，PL（P <.001，非常大）、相对 PL（P =.019，非常大）、峰值 PL 强度（P <.001，中等）、高强度惯性运动分析事件（P =.002，非常大）、总惯性运动分析事件（P <.001，非常大）、总和心率区工作量（P <.001，非常大）、RPE（P <.001，非常大）和会话-RPE 工作量（P <.001，非常大）在比赛中更为明显。
后卫在几个变量之间的训练和比赛中经历了相似的需求，训练时平均工作量强度更高。前锋在比赛中经历了所有变量的需求都比训练时更高。这些发现强调了在篮球比赛中，球队需要制定针对特定位置的准备策略。
