Investigating the Knuckleball Effect in Soccer Using a Smart Ball and Training Machine

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 11; p. 3984
• Main Authors: Eager, David, Ishac, Karlos, Zhou, Shilei, Hossain, Imam
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 24-05-2022; MDPI
• Subjects: Adidas; Applications programs; Athletic Performance; ball sports; Baseball; Dynamic models; Football; knuckleball; Literature reviews; Psychomotor Performance; smart ball; Soccer; Software; Velocity; ball sports; knuckleball; soccer; sports dynamics; sport science; smart ball; football; Adidas
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22113984

The term knuckleball in sporting jargon is used to describe a ball that has been launched with minimal spin, resulting in a trajectory that is erratic and unpredictable. This phenomenon was first observed in baseball (where the term originated) and has since been observed in other sports. While knuckleball has long fascinated the scientific community, the bulk of research has primarily focused on knuckleball as it occurs in baseball. Following the changes in the design of the soccer ball after the 2006 World Cup, knuckleball and ball aerodynamics were exploited by soccer players. This research examined the properties of a knuckleball in the sport of soccer. We designed and evaluated a system that could reproduce the knuckleball effect on soccer balls based on previous theories and characteristics outlined in our literature review. Our system is comprised of the Adidas miCoach Smart Ball, a companion smart phone app for data collection, a ball-launching machine with programmable functions, and a video-based tracking system and Tracker motion analysis software. The results from the testing showed that our system was successfully able to produce knuckleball behaviour on the football in a highly consistent manner. This verified the dynamic models of knuckleball that we outline. While a small portion of the data showed some lateral deviations (zig-zag trajectory), this erratic and unpredictable trajectory was much smaller in magnitude when compared to examples seen in professional games. The sensor data from the miCoach app and trajectory data from the Tracker motion analysis software, showed that the knuckleballs were consistently reproduced in-line with theoretical dynamics.