Open Access
ARTICLE
Research on the Best Shooting State Based on the “Three Forces” Model
Xuguang Liu1, Ruqing Zhao2, Qifei Chen2, Ming Shi3, Ziling Xing2, Yanan Zhang4,*
1 Department of Physical Education, Nanjing University of Information Science & Technology, Nanjing, 210044, China
2 Changwang School of Honors, Nanjing University of Information Science & Technology, Nanjing, 210044, China
3 School of Automation, Nanjing University of Information Science & Technology, Nanjing, 210044, China
4 Engineering Training Center, Nanjing University of Information Science & Technology, Nanjing, 210044, China
* Corresponding Author: Yanan Zhang. Email:
Journal on Big Data 2020, 2(2), 85-93. https://doi.org/10.32604/jbd.2020.013845
Received 15 June 2020; Accepted 15 August 2020; Issue published 18 September 2020
Abstract
The shooting state during shooting refers to the basketball’s shooting
speed, shooting angle and the ball’s rotation speed. The basketball flight path is
also related to these factors. In this paper, based on the three forces of Gravity,
Air Resistance and Magnus Force, the “Three Forces” model is established, the
Kinetic equations are derived, the basketball flight trajectory is solved by
simulation, and the best shot state when shooting is obtained through the
shooting percentage. Compared with the “Single Force” model that only
considers Gravity, the shooting percentage of the “Three Forces” model is
higher. The reason is that the Magnus Force generated by considering the
basketball rotation speed is considered. Although in the “Three Forces” model,
the shot speed is faster and the shot is harder, the backspin will reduce the angle
of the shot and achieve the goal of saving effort. By calculating the best shot
state and giving the athlete’s usual training state range, you can guide the
training, thereby improving the athlete’s shooting percentage during the game.
Keywords
Cite This Article
X. Liu, R. Zhao, Q. Chen, M. Shi, Z. Xing
et al., "Research on the best shooting state based on the “three forces” model,"
Journal on Big Data, vol. 2, no.2, pp. 85–93, 2020.