How valid is the commercially available tennis match analysis mobile application? Is it good enough?

IF 1.9 4区 教育学 Q2 SPORT SCIENCES
Ju-Pil Choe, In-Whi Hwang, Jeong-Hui Park, Christina Amo, Jung-Min Lee
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引用次数: 0

Abstract

ABSTRACTThe present study examines the validity of the SwingVision application by comparing SwingVision’s data to criterion data. Also, we investigated the difference in recording angles of SwingVision (optimal and suboptimal). Six college students played four matches, and every match was recorded from two different angles. After the data collection, recorded videos were analysed by SwingVision and human analysts (criterion). A total of 1065 strokes were analysed in the agreement of SwingVision and human analysts. Cross-tabulation with a column proportion test, Cochran’s Q test, and Kappa statistics were utilised to demonstrate the association of categorical variables (stroke, hit depth, hit zone, bounce depth, bounce zone, spin, result) between the three data (i.e. optimal, suboptimal, and criterion). Repeated measures analysis of variance (ANOVA) and Pearson correlation were used to compare speed data. SwingVision data in most variables showed high proportional similarity and percent agreement with criterion data. Additionally, the optimal angle data had much more similar results to the criterion data than the suboptimal data. Therefore, this present study documented that SwingVision is trustworthy, and users should be aware of possible errors derived from angle differences.KEYWORDS: Measurementsport analyticssmartphone applicationtennisvalidity AcknowledgementsWe want to thank for participants who took part in our experiments.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Korea Creative Content Agency [SR202107001].
商业上可用的网球比赛分析移动应用程序的有效性如何?它够好吗?
摘要本研究通过比较SwingVision的数据和标准数据来检验SwingVision应用程序的有效性。此外,我们还研究了SwingVision记录角度的差异(最优和次优)。六名大学生进行了四场比赛,每场比赛都从两个不同的角度进行了记录。数据收集完成后,使用SwingVision和人工分析(标准)分析录制的视频。在SwingVision和人类分析师的一致意见下,共分析了1065个笔画。交叉表与列比例检验,科克伦的Q检验和Kappa统计被用来证明三个数据(即最优,次优和标准)之间的分类变量(笔画,击球深度,击球区,弹跳深度,弹跳区,旋转,结果)的关联。使用重复测量方差分析(ANOVA)和Pearson相关来比较速度数据。SwingVision数据在大多数变量中与标准数据显示出较高的比例相似性和百分比一致性。此外,与次优数据相比,最佳角度数据与标准数据具有更相似的结果。因此,本研究证明SwingVision是值得信赖的,用户应该意识到由于角度差异可能产生的错误。关键词:测量、运动分析、智能手机应用、网球效度感谢参与我们实验的参与者。披露声明作者未报告潜在的利益冲突。本研究得到了韩国创意内容振兴院[SR202107001]的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Performance Analysis in Sport
International Journal of Performance Analysis in Sport Health Professions-Physical Therapy, Sports Therapy and Rehabilitation
CiteScore
4.40
自引率
4.80%
发文量
38
期刊介绍: The International Journal of Performance Analysis in Sport aims to present current original research into sports performance. In so doing, the journal contributes to our general knowledge of sports performance making findings available to a wide audience of academics and practitioners.
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