Simpson Marni J, Jenkins David G, Connick Mark, Kelly Vincent G
School of Human Movement and Nutrition Sciences, University of Queensland, St Lucia, QLD,Australia.
Queensland Firebirds, Netball Queensland, Nathan, QLD,Australia.
Int J Sports Physiol Perform. 2022 Sep 12;17(11):1599-1605. doi: 10.1123/ijspp.2021-0441. Print 2022 Nov 1.
This study examined the relationships between training workloads, game workloads, and match performance in an elite netball team.
Ten elite female netball athletes were monitored over a complete season. Training and game external workloads were determined through inertial movement units and expressed as absolute PlayerLoad (PL) and change of direction (COD). Monthly workload and training efficiency index were also calculated, which used internal workloads (session rating of perceived exertion and summated heart-rate zones). Game performance was assessed through a performance analysis statistic algorithm called NetPoints. To account for the influence of team game workloads on each other, the average workload for midcourt positions (avgMC) was calculated for each game. Data for each athlete were transformed into z scores, and linear mixed modeling was used to build models to examine the relationships between workloads and game performance.
Monthly PL, training efficiency index PL, and avgMC PL were statistically significant (P < .05) and positively related to game PL (z = 0.20-0.35, P < .001-.02). For game COD, statistically significant positive relationships were found between monthly COD (z = 0.29 [0.11], P = .01) and avgMC COD (z = 0.21 [0.09], P = .03). The models for NetPoints found significant negative relationships with monthly PL (z = 0.46 [0.12], P < .001) and COD (z = -0.36 [0.11], P = .01).
Higher monthly workloads are related to higher game workload; however, they are also related to decreases in match performance. Therefore, netball practitioners should consider that increases to training workload in a 4-week period prior to a game can influence game workloads and performance.
本研究探讨了一支精英无挡板篮球队的训练负荷、比赛负荷与比赛表现之间的关系。
对10名精英女子无挡板篮球运动员进行了一个完整赛季的监测。通过惯性运动单位确定训练和比赛的外部负荷，并以绝对球员负荷（PL）和变向（COD）表示。还计算了月度负荷和训练效率指数，其中使用了内部负荷（主观用力程度评分和累计心率区间）。通过一种名为NetPoints的表现分析统计算法评估比赛表现。为了考虑团队比赛负荷之间的相互影响，计算了每场比赛中场位置的平均负荷（avgMC）。将每位运动员的数据转换为z分数，并使用线性混合模型构建模型，以研究负荷与比赛表现之间的关系。
月度PL、训练效率指数PL和avgMC PL具有统计学意义（P <.05），且与比赛PL呈正相关（z = 0.20 - 0.35，P <.001 -.02）。对于比赛COD，在月度COD（z = 0.29 [0.11]，P =.01）和avgMC COD（z = 0.21 [0.09]，P =.03）之间发现了具有统计学意义的正相关关系。NetPoints模型发现与月度PL（z = 0.46 [0.12]，P <.001）和COD（z = -0.36 [0.11]，P =.01）存在显著负相关关系。
较高的月度负荷与较高的比赛负荷相关；然而，它们也与比赛表现的下降有关。因此，无挡板篮球从业者应考虑到，在比赛前4周内增加训练负荷可能会影响比赛负荷和表现。
