Sports Management
The Emergence of Big Data in Sports Performance Management
Introduction
In the past twenty-five years, the amount of data available in this world has grown exponentially. In Western society in particular, we have become obsessed with the quantification of just about everything. One of the reasons is simple – there’s a lot more data out there, it’s relatively cheap to acquire, and there are just enough statisticians who know how to get value from data to make sense of it all. Some sports have always loved data – baseball, especially. The large data sets from playing 160 game seasons, and the way that each play occurs in isolation makes it easy for casual fans to understand baseball’s class stats. When people started digging deeper into baseball’s numbers, they came up with the ideas in Moneyball, rooted in the idea that there is a sufficient amount of granular data available that is not being used by everybody, and therefore can serve as a source of competitive advantage. Sports management has run with this concept, and now advanced quantitative analysis has become a core component of the management not just of entire sports, but individual athletes as well. This paper will explore the emergence of Big Data in sports performance management.
The Trend Towards Big Data
The trend towards Big Data in sport mirrors the trend in many other industries as well. The term Big Data appears to have originated in the late 1990s in Silicon Valley (Lohr, 2013), used to describe vast sets of data, newly available types of data, and the means to parse this data to derive meaningful results. The Internet was one of the key technologies in this trend, because it allowed for companies – such as Amazon – to collect data on consumer shopping and purchasing, and do so at scale. Businesses have always like information, but the cost of acquiring useful sets of quantitative data has often been prohibitively high, but when the cost of acquiring useful data in quantity began to drop, rapidly, in the late 90s and early 00s., Big Data became a trend that every industry wanted to get in on.
Sports has actually been one of the slower industries to adopt Big Data, but it is here now. Millington and Millington (2015) draw the pathway as to how Big Data arrives in the sports industry. Before Big Data, statistics were relatively simple – how many touchdowns, how many goals, what’s the shooting percentage. These easy-to-collect stats were used in contract negotiations, so it is a natural extension that if there are better numbers to support a position in a negotiation, those numbers will be entered into the negotiation.
In that sense, the use of...
References
Baerg, A. (2017) Big data, sport and the digital divide: Theorizing how athletes might respond to big data monitoring. Journal of Sports and Social Issues. Vol. 41 (1) 3-20.
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Hutchins, B. (2015) Tales of the digital sublime: Tracing the relationship between big data and professional sport. Convergence: The International Journal of Research into New Media Technologies. Vol. 22 (5) 494-509.
Lohr, S. (2013) The origins of Big Data: An etymological detective story. New York Times. Retrieved April 14, 2019 from https://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/
Millington, B. & Millington, R. (2015) The datafication of everything: Toward a sociology of sport and big data. Sociology of Sport Journal. Vol. 32 (2) 140-160.
Zuccolotto, P., Manisera, M. & Sandri, M. (2017) Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions. International Journal of Sports Sciences and Coaching. Vol. 13 (4) 569-589.
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