Sma×Sna : Basketball Snap Judgements Using a Smartwatch

Abstract

The quantification of sports movements enables performance and skill evaluation to assist players in improving their skills. In the shoot motion of basketball, joint motion is essential, especially elbow, shoulder, and wrist motion. In previous studies, most systems used cameras, and financial and environmental conditions may influence their use. On the other hand, systems using wearable devices evaluate little indicators and provide insufficient information for technical assistance. This study uses a smartwatch to determine whether the user uses a wrist snap when shooting free throws. Preliminary experiments showed that the short-term energy (STE) value of the x-axis acceleration is more prominent when the user snaps the wrist than when he doesn’t. We experimented to verify the accuracy of the wrist snap detection threshold. Twenty-one players (6 experienced and 15 inexperienced) shot ten free throws each. We evaluated the accuracy of wrist snap detection by the rate of agreement with wrist snap judgment based on video images. Detection accuracy reached 78.5% with optimal threshold setting and overcame 75% within a specific threshold range. However, we observed a significant difference between the accuracy for experienced players (62.7%) and inexperienced players (84.7%). One of the reasons for the lower accuracy of the experienced players was that some of them shot without using their knees, which may have caused the STE value to increase and exceed the threshold. A possible cause of the misjudgment of shots by inexperienced players is that the magnitude of the STE value may have changed depending on whether the ball reached the ring. Since there is little difference in overall detection accuracy around the optimal threshold value, it is possible to adapt it according to user characteristics. As prospects, it is necessary to find an index not affected by the use of the knee and to add the arrival position of the ball to the index for judgment to improve the accuracy of the snap use judgment in this study. Besides, we would like to increase the feedback items related to wrist motion and posture at the time of shooting.