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

(Eine datengetriebene Methode zum Verständnis und Steigerung des Prozentsatzes von 3-Punkte-Würfen)

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. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:Spielsportarten Naturwissenschaften und Technik
Veröffentlicht in:MIT Sloan Sports Analytics Conference 2017
Sprache:Englisch
Veröffentlicht: 2017
Online-Zugang:http://www.sloansportsconference.com/wp-content/uploads/2017/02/1505.pdf
Seiten:1-14
Dokumentenarten:Kongressband, Tagungsbericht
Level:hoch