Background. Kinanthropometric and Kinematic variable are important in the understanding of performance in various sports. These variables have not been explored among Tennis players in Nigeria. Objectives. An exploration to establish a regression model for kinanthropometric and kinematic variables in relation to ball velocity of Nigerian Female Tennis Players. Methods. Data were collected through direct standard anthropometric protocol and kinematic videographic technique with four Vicon MX 13 cameras. Subjects for the study were drawn from Nigerian female tennis players who participated in the 14th West African University Games and 19th National Sports Festival. Fortysix (46) of the athletes gave their consent to participate in the study, which took place between October to December, 2018. Data were analyzed using SPSS version 23 to obtain mean, standard deviation, range, Pearson correlation Moment Coefficients and Regression linear analysis which was used to test the hypotheses at 0.05 significant levels. Results. Results from this study revealed that there was 60% prediction of interactions of the kinanthropometric and kinematic variables to ball velocity. The results further revealed statistically significant difference in the predicted variables (kinanthropometric and kinematic) to ball velocity at p<0.05. The study recommends that during selection processes, coaches should strictly ensure that only athletes with suitable anthropometric features specific for each sport are recruited. Also, the relevant outcome of the analysis should be employed in developing tennis sports as it will contribute to improving performance and increasing accuracy. Conclusion. Using standard anthropometric protocols and videographic techniques to establish typical performance profile for Nigerian players would ensure a more reasonable assessment of match performances and assist to set practical training and match targets for coaches and

中文翻译：

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人体力学的人体运动学和运动学变量的回归模型

背景。人体测量学和运动学变量对于理解各种运动中的表现很重要。这些变量尚未在尼日利亚的网球运动员中进行探讨。目标。探索建立相对于尼日利亚女网球运动员球速的人体力学和运动学变量回归模型的方法。方法。通过直接的标准人体测量学方案和运动学的摄像技术，使用四个Vicon MX 13摄像机收集数据。该研究的受试者来自参加第14届西非大学运动会和第19届全国体育节的尼日利亚女网球选手。四十六岁（46）的运动员表示同意参加这项研究，该研究于2018年10月至12月进行。使用SPSS 23版对数据进行分析以获得均值，标准偏差，范围，Pearson相关矩系数和回归线性分析，用于检验0.05个显着水平的假设。结果。这项研究的结果表明，有60％的人体力学和运动学变量与球速度的相互作用预测。结果进一步表明，预测变量（人体测量学和运动学）与球速度的统计差异显着，p <0.05。研究建议在选拔过程中，教练应严格确保仅招募具有针对每种运动的人体特征的运动员。同样，分析的相关结果应用于发展网球运动，因为它将有助于提高性能和提高准确性。结论。