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NBA team home advantage: Identifying key factors using an artificial neural network

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  • Austin R Harris
  • Paul J Roebber

Abstract

What determines a team’s home advantage, and why does it change with time? Is it something about the rowdiness of the hometown crowd? Is it something about the location of the team? Or is it something about the team itself, the quality of the team or the styles it may or may not play? To answer these questions, season performance statistics were downloaded for all NBA teams across 32 seasons (83–84 to 17–18). Data were also obtained for other potential influences identified in the literature including: stadium attendance, altitude, and team market size. Using an artificial neural network, a team’s home advantage was diagnosed using team performance statistics only. Attendance, altitude, and market size were unsuccessful at improving this diagnosis. The style of play is a key factor in the home advantage. Teams that make more two point and free-throw shots see larger advantages at home. Given the rise in three-point shooting in recent years, this finding partially explains the gradual decline in home advantage observed across the league over time.

Suggested Citation

  • Austin R Harris & Paul J Roebber, 2019. "NBA team home advantage: Identifying key factors using an artificial neural network," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-9, July.
    • Handle: RePEc:plo:pone00:0220630
    DOI: 10.1371/journal.pone.0220630
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    References listed on IDEAS

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    1. Yung-Chin Chiu & Chen-Kang Chang, 2022. "Major League Baseball during the COVID-19 pandemic: does a lack of spectators affect home advantage?," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-6, December.

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