Philipp Nicolas M, McKay Ben, Martin Ethan, Cabarkapa Dimitrije, Fry Andrew C, Troester Jordan
Jayhawk Athletic Performance Laboratory-Wu Tsai Human Performance Alliance, University of Kansas, Lawrence, KS, United States.
Centre for Medical and Exercise Physiology, School of Medicine, University of Wollongong, Wollongong, NSW, Australia.
Front Sports Act Living. 2024 Jul 1;6:1384476. doi: 10.3389/fspor.2024.1384476. eCollection 2024.
With recent increases in the popularity of studying the physical construct of horizontal deceleration performance in team-sport athletes, the aim of the present study was to assess the inter-rater and intra-rater reliability of processing and quantifying horizontal deceleration ability using radar technology.
Data from 92 NCAA Division 1 athletes from two different athletic teams (American football and Lacrosse) were used for the present investigation. All athletes performed two trials of the modified acceleration to deceleration assessment (ADA), which consisted of a maximal 10 m sprint acceleration, followed by a rapid deceleration. Four individual raters manually processed raw, radar-derived instantaneous velocity data for the ADA, and an automated script was used to calculate metrics of interest.
Primary study findings suggest moderate to excellent levels of agreement (ICC = 0.56-0.91) for maximal horizontal deceleration metrics between the four individual raters. The intra-rater analyses revealed poor to excellent consistency (ICC = 0.31-0.94) between ADA trials, with CV%'s ranging from 3.1% to 13.2%, depending on the respective metric and rater.
Our data suggests that if a foundational understanding and agreement of manual data processing procedures for radar-derived data is given between raters, metrics may be interpreted with moderate to excellent levels of confidence. However, when possible, and when using the Stalker ATS radar technology, authors recommend that practitioners use one trained individual to manually process raw data. Ideally, this process should become fully automated, based on selected filters or algorithms, rather than the subjectivity of the rater.
随着近期对团队运动运动员水平减速性能物理结构研究的热度增加，本研究的目的是评估使用雷达技术处理和量化水平减速能力时评分者间和评分者内的可靠性。
本调查使用了来自两个不同运动队（美式橄榄球和长曲棍球）的92名美国大学体育协会（NCAA）一级运动员的数据。所有运动员都进行了两次改良的加速到减速评估（ADA）试验，该试验包括一次最大10米的短跑加速，然后是快速减速。四名个体评分者手动处理ADA试验中雷达获取的原始瞬时速度数据，并使用一个自动化脚本计算感兴趣的指标。
主要研究结果表明，四名个体评分者之间在最大水平减速指标上的一致性水平为中等至优秀（组内相关系数ICC = 0.56 - 0.91）。评分者内分析显示，ADA试验之间的一致性从差到优秀（ICC = 0.31 - 0.94），变异系数（CV%）范围为3.1%至13.2%，具体取决于各自的指标和评分者。
我们的数据表明，如果评分者之间对雷达衍生数据的手动数据处理程序有基本的理解和共识，那么对指标的解释可能具有中等至优秀程度的可信度。然而，在可能的时候，以及在使用跟踪者ATS雷达技术时，作者建议从业者使用一名经过培训的个体来手动处理原始数据。理想情况下，这个过程应该基于选定的过滤器或算法实现完全自动化，而不是依赖评分者的主观性。
