ArticleSensors (Basel, Switzerland)2025
AI-Powered Analysis of Eye Tracker Data in Basketball Game.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
7 citing papers in PubMed.
- NeuroPlayNet: a multimodal AI framework for real-time cognitive-aware strategy optimization in professional basketball.Scientific reports · 2026Article
- Developmental Differences in Gaze Behaviors and Performance During Basketball Free Throws in Youth Athletes.Sports (Basel, Switzerland) · 2026Article
- Article
- Cognitive processing characteristics of the advantage of assistant referee offside decision-making: evidence from eye movements and ERPs.Frontiers in psychology · 2026Article
- Comparative study on dynamic visual tracking abilities in three-dimensional multi-object tracking tasks among basketball players of different skill levels.Frontiers in psychology · 2025Article
- The impact of time pressure on decision-making and visual search characteristics in basketball players.Frontiers in psychology · 2025Article
- Research on the visual search behavior and decision-making ability of basketball referees.Frontiers in psychology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
This paper outlines a new system for processing of eye-tracking data in basketball live games with two pre-trained Artificial Intelligence (AI) models. The 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, as 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.