Skip to main content

What businesses can learn from how professional sports are using alternative data

(Image credit: Image Credit: Wk1003mike / Shutterstock)

More and more enterprise decisions are being made based on “alternative data.” Data that may initially seem irrelevant such as Twitter posts, product reviews data or even ocean cargo and automobile registrations, are being used to provide critical business insights. Though interest in alternative data is already high and rising, with the whole industry expected to be worth $1.7 billion in 2020, many businesses are only just starting to realize its true potential. However, there is an unlikely leader in the field of alternative data that other businesses can look to as an example - professional sports.

It is common knowledge (at least to anyone who has seen the film Moneyball) that teams in the Premier League and other big money sports leagues like the NFL or NBA employ data scientists to evaluate player performance and make player recruitment decisions based on metrics like passing accuracy. What is lesser known is that they leverage data that goes far beyond game performance to fuel decision-making processes. While it’s easy to think that eye watering contracts such as the £235 million deal Inter Milan are prepared to offer Lionel Messi if he decides to leave Barcelona next year are awarded purely on the basis of on the turf performance, it’s likely that many other data-based considerations came into play.

When millions of pounds of club money are being allocated for a contract, merchandise sales, local property prices, game-day tourism spikes and other sources of information that are often freely available online are looked at to make decisions on contracts. Businesses that are a million miles away from a football pitch have a lot to learn from some of the creative ways sports teams use alternative data to decide how to spend their money, particularly as traditional economic indicators seem more fallible than ever.

How professional sports teams use real-time online data to fuel decision making

Premier league teams look towards predictive data to give a rough estimate of how much a particular deal could affect ticket pricing, merchandise sales and even the price of burgers they can charge at the stadium. The high levels of interest a premium player like Messi brings to a team can reap a lot of benefits for clubs off the field. Using this data, teams can determine that they can increase ticket prices by a certain amount, say £7 each, and easily justify the price of a seemingly eye watering contract offer through the expected returns. So, although talents on the pitch and performance-based statistics undoubtedly play a role in decisions such as these, there are a much wider array of factors that are taken into consideration

While it is obvious that the Premier League’s interest in economic data is mainly profit oriented, there are other social factors which often play into decision making. Team decisions often directly impact property prices in the area and the regional job market. Looking to US Sports, the NBA for example, a Harvard Kennedy school study found that during Lebron James’ stint at the Cleveland Cavaliers and Miami Heat, total employment in the areas rose by around 23.5 percent and the total number of bars in the arenas’ direct vicinities rose by 13 percent.

It would be naive to think that contracts at the scale of Messi and James’ are offered arbitrarily. The money offered instead comes from a precise estimation of expected returns, going beyond ticket prices and into projected kit sales based on the players brand name, their social media following, broadcasting rights negotiations and even the effects on domestic tourism. With the scale of sports contracts only increasing every year, it is only natural that more and more sports fans question whether the value of these deals can ever truly be justified. Fans should realize that these deals are rational data-based decisions informed by comprehensive methodologies.

What businesses can learn from how professional sports use online data

One area in which businesses could learn from professional football is by looking at the sources of data which teams use. Most of the wide variety of data they have drawn from is in fact publicly available online data, rather coming from niche and often expensive proprietary sources. Insights are drawn from local city economic reports, regional employments statistics, or local house prices – all of which can be found for free on the World Wide Web using the power of open data collection platforms. Even the most experienced group of data scientists is useless if they don’t have the raw materials that they need to gather the best insights, and the internet represents an almost infinite source of this data.

Businesses can look to how professional sports are leading the way and putting their money where their mouth is when it comes to data driven decision making. In the current period of record economic volatility, traditional sources of data such as company financial reports, or analyst reports are serving as unreliable markers of the economic trajectory. With the status of the pandemic and government legislation hard to predict, even a few weeks of delay can render a data source inaccurate, hence the growing interest in fast moving up-to-minute online data by enterprises and corporates. When making bold investments with uncertain returns, all potential sources of information should be considered, so more businesses could look to incorporate publicly available online data at every stage of their decision-making process, regardless of the industry.

Omri Orgad, Director of North America, Luminati Networks

Tech-savvy and data-driven business leader Omri Orgad is Luminati Networks’ Managing Director, North America. During the last five years, Orgad has held several senior executive roles at Luminati, an industry leader in the automated data collection space.