Reliability and validity of the fulltrack AI application to determine cricket bowling line and length compared to 3D motion capture

Abstract

<p>This study examined reliability and validity of the <i>Fulltrack</i> AI applica-tion to identify cricket ball landing position (line, length). Nine hundred and thirty-two deliveries were compared to 3D motion capture,the criterion measure, with 836 included in analysis (516 bowled (pace = 420, spin = 96), 320 Sidearm^TM" 301 facing a batter). Agreement analysis indicated an intraclass correlation coefficient of >0.96 for raw and filter 3D line and length data, compared to <i>Fulltrack</i> AI. The coefficient of variation was acceptable for length(<10%) and larger for line (23.82%), albeit with a smaller standard error of measurement (SEM = 0.05 m), improving with outliers removed. Bland−Altman plots confirmed good statistical agreement between devices, with limits of agreement largely within maximal allowable difference values. There are potential practical application considerations, given SEM = 0.47 m for length (diameter of seven cricket balls)" with greater variability detecting length closer to the batters-end, and line closer to the bowlers-end. Validity, using a generalised additive model, showed no significant differences between devices (p > 0.05), with no condition-based interaction effects. The <i>Fulltrack</i> AI application enables ecologically valid assessment of bowling performance. Considering the trade-off between this and the accuracy of information is warranted when deciding how best to apply it to coaching environments to support augmented feedback.</p>