{'fraction_non_alphanumeric': 0.021119324181626188, 'fraction_numerical': 0.0021119324181626186, 'mean_word_length': 5.676056338028169, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A framework for visualization of soccer video using motion trajectories: presenting insights into tactics and performance

Recently, a fast-developing trend has been to enhance the experience of sporting events beyond the scores, player information and statistics associated with the sport. Systems have been designed to provide additional information, especially spatial data for better comprehension of broadcast events. The paper presents a visualization framework designed for deeper analysis of soccer video, providing further insights into tactics and performance. This framework analyzes broadcast soccer video to obtain motion trajectories of ball and players, and offers a rich set of visualization options based on this trajectory data. Our approach can be applied in (1) the goal event, to analyze team collaboration for training support, or (2) the foul event, to verify referee decisions, especially for some controversial situations.