The Impact of Data Analytics in Basketball: a case study from the national basketball association

Abstract

The trends towards Big Data have influenced many business sectors of the economy. Data Analytics were introduced in sports in the early 2000’s to improve efficiency, track players performance and give organizations, general managers, and coaches raw statistical data to analyse for improved decision making. Most professional sports clubs use data analytics to make informed decisions in some capacity. The NBA (National Basketball Association) also use analytics to answer questions about its players, team, and organizational needs. There is an ongoing debate about how data analytics has changed the game of basketball. The purpose of this research is to investigate the overall impact of data analytics and its current use. Optical tracking technology like SportsVU cameras have opened new possibilities to gain insight in a competitive sporting landscape. This paper will highlight how analytics have altered the shot selection of players in the National Basketball Association using play-by-play data along with visualization tools. This research provides a fundamental understanding of data analytics in basketball for spectator, organization, and athletes. Furthermore, it will highlight the practical uses, its impact, and limitations by reviewing literature of past studies. This study provides a statistical analysis of 30 NBA seasons from 1993 using team and player statistics. The results illustrate the trends of 3P and 2P shot attempt before and after the inception of analytics in the sport. To emphasize the modern-day impact of analytics in the NBA the paper examines over 427,737 shot attempts from the 2021-2023 NBA seasons. Using Pearson’s correlation coefficient, the paper investigates which statistical categories have a strong relationship with wins for NBA teams.