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The article announces the kickoff of the fifth season of NFL on Prime, featuring the Bills vs. Lions game at Highmark Stadium and highlighting tech advancements like AI insights for enhanced fan viewing.
A basketball AI system that combines local AI with GPT-6 Astra to detect and track players, perform OCR for player numbers, and map trajectories for sports analytics.
NVIDIA announced expansions to NVIDIA AI for Media at IBC 2026, including advanced Synthetic Video Detector and 3D Body Pose technologies to enhance AI applications in broadcast, sports, and streaming.
This paper adapts Expected Threat (xT) and Valuing Actions by Estimating Probabilities (VAEP) frameworks to professional handball, introducing Handball-xT and Handball-VAEP using five seasons of tracking-derived event data from the Handball Bundesliga, and releases the code for clubs.
xPitch is a mobile app offering football match analytics for casual players, akin to Strava for football.
This paper presents FST.ai 2.5, an explainable and uncertainty-aware AI framework for Olympic and Para-Taekwondo that integrates athlete digital twins, competition analytics, and federation-scale decision support.
A data-driven visualization project that reconstructs every match of FIFA World Cup 2026 from recorded events, offering an impression built entirely from data.
This paper uses a Transformer-based model on MLB Statcast data to counterfactually optimize baseball pitch sequences, finding that optimizing both final and setup pitches can improve season-level statistics like K/9 by over 1.0.
TacticAI uses graph neural networks to represent players as nodes and their interactions as connections, allowing data scientists to test defensive setups by dragging and dropping players in real time.
This MIT Technology Review newsletter covers the rise of AI and data analytics in soccer, China's rapid construction of large nuclear reactors, and reports that autonomous drones may have killed soldiers for the first time.
Jesse Davis and his Sports Analytics Lab at KU Leuven use machine learning to analyze soccer data, revealing tactical insights like the value of kicking the ball out of bounds. Their open-source tools are influencing professional clubs.
This paper presents a constraint programming approach to determine NHL playoff clinching scenarios with n-day lookahead, using tree search and preprocessing techniques.