TACDEC: Dataset of Tackle Events in Soccer Game Videos

Abstract

This paper introduces TACDEC, a dataset of tackle events in soccer game videos. Recognizing the gap in existing open datasets that predominantly focus on official soccer events such as goals and cards, TACDEC targets a comprehensive analysis of tackles — a critical aspect of soccer that combines technical skills, tactical decisionmaking, and physical engagement. By leveraging video data from the Norwegian Eliteserien league across multiple seasons, we annotated 425 videos with 4 types of tackle events, categorized into "tackle-live", "tackle-replay", "tackle-live-incomplete", and "tacklereplay-incomplete", yielding a total of 836 event annotations. The dataset offers an unprecedented resource for the development and testing of machine learning models aimed at understanding and analyzing soccer game dynamics. A proof-of-concept classification model demonstrates the dataset’s utility, achieving promising results in automatic tackle detection, thereby validating TACDEC’s potential to support not only advanced game analytics but also to enhance fan engagement and player development initiatives.