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A data­driven method for understanding and increasing 3-point shooting percentage

Although 3-point shooting is an essential aspect of winning games, shooting percentages have remained stagnant for decades. Here, we analyze 6 shooter factors from over 1.1 million 3-point shots captured by the Noah shooting system to quantitatively define high percentage shooting and shooter improvement. We find significant associations between all of these 6 shooter factors and shooting percentage. Furthermore, we use the interaction of these factors to define the region in the hoop where shots are guaranteed to score. Of the 6 factors, 4 are directly actionable using new technologies for instant feedback. We use machine learning to predict shooting percentage within 1.5% using only these 4 factors as input. Finally, we grouped players by their proficiency at these 4 factors and show case studies about the dissimilar training approaches that will lead to optimal improvement for two of these groupsDeskriptoren
© Copyright 2017 MIT Sloan Sports Analytics Conference 2017. All rights reserved.

Bibliographic Details
Subjects:
Notations:sport games technical and natural sciences
Published in:MIT Sloan Sports Analytics Conference 2017
Language:English
Published: 2017
Online Access:http://www.sloansportsconference.com/wp-content/uploads/2017/02/1505.pdf
Pages:1-14
Document types:congress proceedings
Level:advanced