@misc{17716,
  keywords = {Information retrieval},
  author = {Evan Kassab and H{\r a}kon Solberg and Sushant Gautam and Saeed Sabet and Thomas Torjusen and Michael Riegler and P{\r a}l Halvorsen and Cise Midoglu},
  title = {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 decision-making, 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 "tackle-replay-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{\textquoteright}s utility, achieving promising results in automatic tackle detection, thereby validating TACDEC{\textquoteright}s potential to support not only advanced game analytics but also to enhance fan engagement and player development initiatives.},
  year = {2024},
  journal = {MMSys {\textquoteright}24: Proceedings of the 15th ACM Multimedia Systems Conference},
  publisher = {Association for Computing Machinery},
  doi = {10.1145/3625468.3652166},
}