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Abstract
The purpose of this capstone project was to employ optimization tools and techniques to improve basketball jump shot mechanics, resulting in an increased basketball shooting percentage. The capstone project is being submitted to meet the requirements for the Milwaukee School of Engineering’s Master of Science in Engineering program. Six factors that affect basketball shooting ability have been identified in the literature, including shot release time, shot release angle, leg angle, vertical jump, rotational speed on the ball, and ball speed immediately upon release. A Design of Experiments [DOE] approach, featuring factor brainstorming, factor sorting, and a fishbone diagram, has been developed and implemented to examine the factors and the combination of factors that are statistically significant in increasing shot percentage. In this investigation, the author served as the lone study participant. This project employed the mobile artificial intelligence [AI] basketball feedback app, Homecourt [https://homecourt.ai], to record and track a large number of free throw line jump shots associated with the six factors. These collected data were then assessed in Minitab statistical analysis software. These data were employed to develop a MATLAB/Simulink model and simulation of the author’s jump shot, which can be used to evaluate factor changes and determine statistical improvement for optimum factor values.
From the results of the analysis, it is seen that main factors - release angle, release speed, and backspin, as well as the combination factors, including release angle/vertical, leg angle/vertical, vertical/release speed, release time/vertical/backspin, and release angle/leg angle/backspin -- were found to be statistically significant in determining the corresponding response variable, the make percentage. There exist opportunities to improve the analysis of significant factors, including the evidence that the introduction of further study factors may add additional significant factors to determine make percentage. In addition, an increase in number of data points and the ability to track response variable as a continuous response variable would help with the accuracy and applicability of the data found in this experimentation and used within the simulation.