Data science

Why Alternative Data is a Slam Dunk for Professional Sports Teams

Omri Orgad, Managing Director for North America at Bright Data, explains how ‘big money’ sports teams are leading the way in web data collection and analysis.
For years now, “big money” sports teams have analyzed all aspects of players’ in-game performance, generating extensive datasets to inform recruitment and transfer decisions. However, given that teams worldwide are now managing historically high levels of debt – in part due to unexpected expenses and revenue drops caused by the pandemic – many are now turning to web-based alternative data to sharpen the speed and accuracy of their commercial decision-making.

 

So, what is alternative data?
A near-endless supply of alternative data (also known as alt-data) is publicly available on the world’s largest database – the open internet. Sports teams can collect it in bulk from all corners of the web, using automated web data collection platforms and tools. How they then apply it is limited only by the creativity of the teams’ data scientists.

Alt-data encompasses public information gathered from social media, forums, media reports, local city and state economic databases, and more. When analyzed, it can provide teams with an understanding of fan sentiment, the potential impact of signing new players, and even competing teams’ strategies. The most important thing to remember is that, unlike traditional sources, this web-based alt-data generates insights in near real-time.

 

How can alt-data inform teams’ decision-making?
Teams in “big money” sports leagues – like the NBA, NFL, Premier League, and Bundesliga– increasingly benefit from the star power of players to boost global viewership. The reality is that top teams no longer rely on selling tickets to diehard fans to stay afloat. Deloitte’s 2021 Football Money League Report demonstrates this, finding that the world’s top 20 highest-revenue-generating soccer clubs depend on matchday returns for anywhere between just 6% to 22% of their total revenue. Instead, teams across all sports – soccer, basketball, football, etc. – are increasingly reliant on advertising dollars, endorsements, and merchandise sales.

And there’s no better way of generating global buzz – and revenue – than big-name signings. Consider the recent return of global soccer icon Ronaldo to Manchester United, whose signing smashed the club’s shirt sale record in under four hours. Ronaldo’s ability to generate revenue is a major asset for the team, and public online alt-data can go a long way towards helping predict how much value he will bring.

In the NFL, Tom Brady’s 2020 move to the Tampa Bay Buccaneers had a similar effect. His debut performance drew the most viewers for a Week 1 NFL game in four years and was one of the year’s most-watched television broadcasts.

The eye-watering fees paid to players in some leagues – Brady will earn $50 million in his first two years with the Buccaneers – often lead to disbelief from fans. However, the reality is that teams use hundreds of predictive datasets, some of which are gathered from publicly available alt-data, to carefully analyze the value of each deal. From ticket pricing to merchandise sales, and even the price of concession stand hotdogs, signing a big name can easily be offset by price increases across the board. Whether fans think a player brings in-game value is another matter!

 

The LeBron James Effect
Decisions taken by major sports teams often have a ripple effect on their local area. Economic growth, property prices and the regional job market can all be impacted. A fascinating Harvard Kennedy School study found that during Lebron James’ stints with the Cleveland Cavaliers and Miami Heat, total employment in the areas rose by around 23.5%, and the number of bars in the arenas’ direct vicinities rose by 13%.

In this regard, business leaders and investors – restauranteurs and property developers, for example – can also use alt-data to identify sports trends, in turn informing their investment decisions in a particular geography. The potential for this is huge, and in many cases is still going untapped.

Looking forward, we can expect to see the use of alt-data in professional sports continuing to expand. Teams are fast realizing that – to stay relevant and therefore profitable – they must embrace new and creative public web data sources. Those that don’t, and continue to stick to past practices, will soon find that their calculations don’t add up.

 

Author
Omri Orgad, Managing Director for North America at Bright Data

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