Load monitoring in basketball is fundamental to develop training programs, maximizing performance while reducing injury risk. However, information regarding the load associated with specific activity patterns during competition is limited. This study aimed at assessing the external load associated with high-intensity activities recorded during official basketball games, with respect to different (1) activity patterns, (2) playing positions, and (3) activities performed with or without ball. Eleven male basketball players (six backcourt, five frontcourt, age: 20.5 ± 1.1 years, stature: 191.5 ± 8.7 cm, body mass: 86.5 ± 11.3 kg; experience: 8.5 ± 2.4 years) competing in the Lithuanian third division were recruited for this study. Three in-season games were assessed via time-motion analysis and microsensors. Specifically, the high-intensity activities including sprints, high-intensity specific movements (HSM) and jumps were identified and subsequently the external load [PlayerLoad™ (PL) and PlayerLoad™/min (PL/min)] of each activity was determined. Linear mixed models were used to examine differences in PL, PL/min and mean duration between activity pattern, playing positions and activities performed with or without ball. Results revealed PL was lower in jumps compared to sprints [p < 0.001, effect size (ES) = 0.68] and HSMs (p < 0.001, ES = 0.58), while PL/min was greater in sprints compared to jumps (p = 0.023, ES = 0.22). Jumps displayed shorter duration compared to sprints (p < 0.001, ES = 1.10) and HSMs (p < 0.001, ES = 0.81), with HSMs lasting longer than sprints (p = 0.002, ES = 0.17). Jumps duration was longer in backcourt than frontcourt players (p < 0.001, ES = 0.33). When considering activity patterns combined, PL (p < 0.001, ES = 0.28) and duration (p < 0.001, ES = 0.43) were greater without ball. Regarding HSMs, PL/min was higher with ball (p = 0.036, ES = 0.14), while duration was longer without ball (p < 0.001, ES = 0.34). The current findings suggest that external load differences in high-intensity activities exist among activity patterns and between activities performed with and without ball, while no differences were found between playing positions. Practitioners should consider these differences when designing training sessions.

篮球中的负荷监控是制定训练计划的基础，该训练计划可以在降低受伤风险的同时最大化性能。但是，关于与比赛期间特定活动模式相关的负荷的信息是有限的。这项研究旨在评估与正式篮球比赛期间记录的高强度活动相关的外部负荷，涉及不同的（1）活动模式，（2）比赛位置以及（3）有球或无球活动。为此招募了十一名参加立陶宛三级赛的男篮球运动员（六个后场，五个前场，年龄：20.5±1.1岁，身高：191.5±8.7 cm，体重：86.5±11.3 kg；经验：8.5±2.4岁）。学习。评估了三场季后赛通过时间运动分析和微传感器。具体来说，确定包括冲刺，高强度特定运动（HSM）和跳跃的高强度活动，然后确定每个活动的外部负荷[PlayerLoad™（PL）和PlayerLoad™/ min（PL / min）]。线性混合模型用于检查PL，PL / min和活动模式，比赛位置和有无球活动之间的平均持续时间之间的差异。结果显示，与短跑相比，PL的跳动作要低[p <0.001，效果大小（ES）= 0.68]和HSM （p <0.001，ES = 0.58），而与跳跃相比，短跑的PL / min更大（p= 0.023，ES = 0.22）。与短跑相比，跳跃显示的持续时间短（p <0.001，ES = 1.10）和HSM（p <0.001，ES = 0.81），HSM持续时间比冲刺更长（p= 0.002，ES = 0.17）。后场的跳跃时间长于前场的运动员（p<0.001，ES = 0.33）。当考虑活动模式组合时，PL（p <0.001，ES = 0.28）和持续时间（p<0.001，ES = 0.43）无球时更大。对于HSM，带球的PL / min更高（p = 0.036，ES = 0.14），而没有球的持续时间更长（p<0.001，ES = 0.34）。目前的发现表明，在高强度活动中，外部负荷差异存在于活动模式之间以及在有球和无球情况下进行的活动之间，而在演奏位置之间没有发现差异。从业人员在设计培训课程时应考虑这些差异。