In the realm of soccer, a substantial amount of data analysis has been undertaken. Although analyses using tracking data are prevalent, those involving gaze information have not progressed as much due to the challenges associated with measuring gaze. However, in soccer, gaze and visual information are critical features for players when making situational judgments. Concurrently, gaze tracking technology utilizing virtual reality (VR) has been advancing.In this study, we recreated logs of soccer simulation 2D games by converting into 3D models for more realistic visualization. We not only reproduced the positional information available from simple logs into the 3D model but also created cameras representing each player's viewpoint and performed Z-axis interpolation to replicate an environment that closely resembles real-world soccer. Subsequently, we conducted a survey with participants, comparing 2D and 3D models. Although the survey revealed numerous challenges, the 3D model developed was a step closer to acquiring the field of view information of experts, akin to a real soccer environment.The paper also describes some directions of future research which may include data augmentation with actual soccer data and extending this 3D model to VR, enabling gaze measurement. Ultimately, it is conceivable that analyzing the gaze movements as perceived by experts and implementing them into the player model of robot soccer could become feasible.
