The Concurrent Validity of Mobile Application for Tracking Tennis Performance

Abstract

The SwingVision (SV) application represents software for the automatic analysis of movement and specific parameters in tennis, but no study evaluated its applicability so far. Therefore, the aim of this research is to determine the validity of SwingVision for monitoring speed and placement parameters when performing serve and the frequency, type, and rotation of each stroke in the game. The sample of participants (N = 5) consisted of elite male junior tennis players (mean age 15.6 ± 0.35 years, mean height 179.16 ± 5.71 cm, and mean weight 72.62 ± 3.89 kg). Video analyses of closed and open character exercises were used to compare real data and those obtained using SV. The placement results determined good and very good validity (ICC = 0.83–0.87). In terms of speed, the results were found to have good validity (Speed_AD-ICC = 0.76–0.80). SV provided very good validity (ICC = 0.97) in the stroke detection parameter and also presented good validity in recognizing the rotation of shots (ICC = 0.76). SV provides valid objective feedback on tennis performance. Thus, the results justify the use of SV as a helpful tool in the training process, both in training and matches.