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 data in sports management echoes the use of data in other forms of management. If a manager sees data as an asset, then the next natural question is what to do with that asset (Dhar, et al, 2014). Management teams in sports use data routinely in contract negotiations, to help make their marketing decisions, and increasingly as a means of governing the performance of individual athletes.

In sports, one of the new common uses of data is to provide more context and granularity to evaluations of individual athletes. Sports teams gather and use data in-house for this purpose. Fan blogs focused on data are prevalent now across many sports. An academic example of this phenomenon is a paper from 2017 on modeling scoring probability in basketball (Zuccolotto et al, 2017). We have arrived at the point where the day-to-day management of athletic performance is...…used in contract negotiations.

The downside, for some at least, is that the purity of athletic completion may be eroded. Data-poor sports are likely to receive less attention in the Big Data world, to the detriment of creating opportunities for the athletes who participate in those sports. Furthermore, the increasing quantification of sports is seen by some as reducing the emphasis on the physical elements of sport – the faster, higher, stronger parts of human achievement. The advances in athletics in the past 150 years have been the result of the application of different sciences – biology, chemistry and design have all transformed different sports. Now, data is the technology that is changing the way that sports are played, and managed.

From the perspective of somebody with an interest in sports management, Big Data is part of the process of professionalizing this business. Managers on the talent side of sports are achieving parity with their marketing and finance departments, for example, but also with other data-rich entertainment competitors. All told, the use of Big Data will be a positive in sports management, one that allows sport to receive a greater share of attention, ideally a greater share of revenue, and by way of that to allow sports to continue to thrive.

Conclusions

Over the past twenty years, Big Data has entered most business realms, and the business of sport is no exception. Yet, sport has been relatively slow to adapt to Big Data, despite the obvious opportunities it presents to make sporting organizations more efficient and effective. Big Data’s impact on sport is just starting to be known, and going forward there should be substantial influences on things like individual athlete performance that are relatively unexplored areas thus far.