kinematics of upper limbs and the spin effectivity of table tennis ball during a serve with backspin - Muhammad Zaki Hawaari; Khairuddin Khairuddin; Masrun Masrun; Fahd Mukhtarsyaf (JRTI (Jurnal Riset Tindakan Indonesia), 2026)
Among all table tennis strokes, the backspin serve is a critical technical skill because it enables the server to initiate play without direct opposition and create tactical advantages through ball spin. Despite its importance, the biomechanics of upper limb movements during the backspin serve remain less understood than those of topspin strokes. This systematic review aimed to synthesize and critically evaluate the existing evidence on upper limb biomechanics during table tennis serves and strokes, with particular emphasis on the backspin serve. The review followed the PRISMA 2020 guidelines and searched the Scopus database using structured Boolean keywords related to table tennis, biomechanics, upper limb kinematics, and serve actions. Of 479 identified records, 50 studies met the inclusion criteria and were included in the qualitative synthesis. The findings consistently demonstrated that effective spin generation relies on a proximal-to-distal kinetic sequence involving shoulder internal rotation, forearm pronation, and wrist flexion, with wrist motion playing a particularly important role in backspin and short serves. Kinematic patterns also varied according to sex, playing level, and grip style, highlighting the need for individualized technical models. In addition, wearable inertial sensors and statistical mapping emerged as promising alternatives to laboratory-based motion capture systems, although markerless motion analysis requires further validation. However, direct evidence linking upper limb biomechanics to ball spin and serve effectiveness remains limited, particularly for backspin serves. Overall, this review highlights current evidence, identifies important methodological gaps, and provides practical implications for coaching and future research on serve-specific biomechanics, longitudinal designs, and AI-assisted motion analysis in table tennis.