Atmospheric Science Program, Department of Mathematical Science, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, United States of America.
PLoS One. 2019 Jul 31;14(7):e0220630. doi: 10.1371/journal.pone.0220630. eCollection 2019.
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.
是什么决定了一个球队的主场优势，以及为什么它会随着时间的推移而变化？是主场观众的喧闹声吗？是球队的位置吗？还是球队自身，球队的实力或可能的打法风格？为了回答这些问题，我们下载了 NBA 球队在 32 个赛季（83-84 赛季至 17-18 赛季）中的赛季表现统计数据。我们还获得了文献中确定的其他潜在影响因素的数据，包括：体育场上座率、海拔和球队市场规模。使用人工神经网络，仅使用球队表现统计数据来诊断球队的主场优势。上座率、海拔和市场规模并不能改善这种诊断。打法风格是主场优势的关键因素。更多地投中两分球和罚球的球队在主场会有更大的优势。考虑到近年来三分球的兴起，这一发现部分解释了近年来整个联盟主场优势逐渐下降的现象。
