Background/Objectives: Eye-tracking technology has gained increasing attention in sports science, as it provides valuable insights into visual attention, decision-making, and motor planning. This systematic review examines the application of eye-tracking technology in basketball, highlighting its role in analyzing cognitive and perceptual strategies in players, referees, and coaches. Methods: A systematic search was conducted following PRISMA guidelines. Studies published up until December 2024 were retrieved from PubMed and Web of Science using keywords related to basketball, eye tracking, and visual search. The inclusion criteria focused on studies using eye-tracking technology to assess athletes, referees, and coaches. A total of 1706 articles were screened, of which 19 met the eligibility criteria. Results: Eye-tracking studies have shown that expert basketball players exhibit longer quiet eye (QE) durations and more efficient gaze behaviors compared to novices. In high-pressure situations, skilled players maintain more stable QE characteristics, leading to better shot accuracy. Referees rely on efficient gaze strategies to make split-second decisions, although less experienced referees tend to neglect key visual cues. In coaching, eye-tracking studies suggest that guided gaze techniques improve tactical understanding in novice players but have limited effects on experienced athletes. Conclusions: Eye tracking is a powerful tool for studying cognitive and behavioral functioning in basketball, offering valuable insights for performance enhancement and training strategies. Future research should explore real-game settings using mobile eye trackers and integrate artificial intelligence to further refine gaze-based training methods.

This paper outlines a new system for processing of eye-tracking data in basketball live games with two pre-trained Artificial Intelligence (AI) models. blueThe system is designed to process and extract features from data of basketball coaches and referees, recorded with the Pupil Labs Neon Eye Tracker, a device that is specifically optimized for video analysis. The research aims to present a tool useful for understanding their visual attention patterns during the game, what they are attending to, for how long, and their physiological responses, blueas is evidenced through pupil size changes. AI models are used to monitor events and actions within the game and correlate these with eye-tracking data to provide understanding into referees’ and coaches’ cognitive processes and decision-making. This research contributes to the knowledge of sport psychology and performance analysis by introducing the potential of Artificial Intelligence (AI)-based eye-tracking analysis in sport with wearable technology and light neural networks that are capable of running in real time.

Background/Objectives: Eye tracking technology has gained increasing attention in sports science as it provides valuable insights into visual attention, decision-making, and motor planning. This systematic review examines the application of eye-tracking technology in basketball, highlighting its role in analyzing cognitive and perceptual strategies in players, referees and coaches. Methods: A systematic search was conducted following PRISMA guidelines. Studies published up December 2024 were retrieved from PubMed and Web of Science using keywords related to basketball, eye tracking and visual search. Inclusion criteria focused on studies using eye-tracking technology to assess athletes, referees, and coaches. A total of 1706 articles were screened, of which 19 met the eligibility criteria. Results: Eye-tracking studies have shown that expert basketball players exhibit longer quiet eye (QE) durations and more efficient gaze behaviors compared to novices. In high-pressure situations, skilled players maintain more stable QE characteristics, leading to better shot accuracy. Referees rely on efficient gaze strategies to make split-second decisions, although less experienced referees tend to neglect key visual cues. In coaching, eye-tracking studies suggest that guided gaze techniques improve tactical understanding in novice players, but have limited effects on experienced athletes. Conclusions: Eye tracking is a powerful tool for studying cognitive and behavioral functioning in basketball, offering valuable insights for performance enhancement and training strategies. Future research should explore real-game settings using mobile eye trackers and integrate artificial intelligence to further refine gaze-based training methods.

Eye tracking is a tool that is widely used in scientific research, enabling the acquisition of precise and detailed data on an individual’s eye movements during interaction with visual stimuli, thus offering a rich source of information on visual perception and associated cognitive processes. In this work, a new software called SPEED (labScoc Processing and Extraction of Eye tracking Data) is presented to process data acquired by Pupil Lab Neon (Pupil Labs, Berlin, Germany). The software is written in Python which helps researchers with the feature extraction step without any coding skills. This work also presents a pilot study in which five healthy subjects were included in research investigating oculomotor correlates during MDMT (Moral Decision-Making Task) and testing possible autonomic predictors of participants’ performance. A statistically significant difference was observed in reaction times and in the number of blinks made during the choice between the conditions of the personal and impersonal dilemma.

Circadian rhythms, sleep homeostasis, and chronotype interact to modulate cognitive processes such as attention and executive functions, leading to fluctuations in performance throughout the day and significant impairments under conditions of misalignment or sleep deprivation. The study was conducted in two phases and included the assessment of subjective measures of sleepiness, vigor, affect, sleep quality, and individual chronotype. In the first phase, 32 healthy participants (19 females; mean age = 24.9 ± 3.14) were tested at four different times of the day to examine diurnal variations in attentional performance. In the second phase, a subsample of 8 participants (4 females; mean age = 24.4 ± 2.20) underwent a total sleep-deprivation protocol and completed the AD-Task over two consecutive days to evaluate the impact of prolonged wakefulness on attentional and executive functioning. In the first phase, results revealed a progressive decline in selective attention across the day (F_(3.93) = 3.188; p = 0.027; η²p = 0.093) and significantly slower reaction times in divided attention during the morning (F_(3.93) = 7.3134; p < 0.001; η²p = 0.191), indicating a time-of-day modulation of attentional resources. In the second phase, total sleep deprivation led to a marked impairment in performance, reflected by slower reaction times (F_(11.77) = 1.948; p = 0.046; η²p = 0.218) and reduced discriminative ability (d′; F_(11.77) = 13.438; p < 0.001; η²p = 0.657), particularly in task-switching conditions. These findings suggest increased vulnerability of executive functions under sleep deprivation, likely associated with reduced efficiency of prefrontal cortical processes. The results confirm that time of the day and pressure of sleep significantly affect attention and cognitive flexibility and further affirm the validity of the AD-Task as a reliable instrument for detecting these variations under ecologically relevant conditions.