Professional sports lend themselves really well to economic calculations – players, coaches, and agents act similarly to the hypothetical, rational decision-makers in economic models. While this data may seem complex or hard to obtain, it’s actually all readily available online – you just need to know where to look, how to gather it and how to use it and draw your insights based on it.
Data is at the heart of every professional sports decision – especially when it comes to player contracts. A player like Patrick Mahomes, who was just awarded a monster $500 million contract extension by the Kansas City Chiefs, is a prime example of how economic data is at play in these negotiations.
While it’s easy to think that Mahomes’ extension was solely the result of his on-field performance, the reality is that there are plenty of other data sources that came into play.
And this data goes far beyond sports. It includes alternative or external sources of online data like merchandise sales, local real estate prices and game-day tourism spikes.
The Mahomes’ example
The Mahomes’ deal is again an excellent recent example of this concept. The Chiefs greatly relied on predictive data to look at how the deal would affect ticket pricing, merchandise sales and even things that seem trivial like how much they could increase hot dog prices at the stadium just because Mahomes is on the team.
Using the aforementioned data, they were able to make the calculation that ticket prices would increase by $40 each – meaning the investment would become well worth it long before 2031, when this specific contract expires.
In fact, the increased ticket price alone, without accounting for merchandise and vending sales, would easily return the initial amount paid to Mahomes. So yes, while Mahomes was awarded such a big contract because of his talent and Super Bowl win, the team came to the actual figure that was offered to him thanks to a more complex and data-based calculation than his talent alone might suggest.
The rise of alternative data in sports
For professional teams and leagues, the incentive to utilize economic data in their decision-making is undoubtedly financial. But data economists are often driven by something else – analyzing whether sports have a direct impact on local real estate, education, the overall labor market, and more.
For example, during “King James” (Lebron James) time at the Cleveland Cavaliers and Miami Heat, the total number of bars and restaurants within a mile of those stadiums rose by an aggregate 13 percent, while total employment rose about 23.5 percent, a Harvard Kennedy School study found.
Every single decision in professional sports ultimately comes down to a data check. Contracts like Mahomes’ aren’t decided arbitrarily. They’re based on a carefully calculated on historical and current cost-benefit analysis driven by external online data sources.
Within this decision-making process, the specific amount of money offered comes down not only to considerations like the previously mentioned effect on ticket prices but also how much merchandise the player’s name will sell and even the player’s impact on broadcasting rights negotiations.
Domestic tourism is another important data point that professional sports teams consider when making their personnel decisions. Teams have a massive impact on their local economies, with some bringing in millions of dollars to their respective cities’ economies on the day of home games.
This reverberates far beyond ticket prices and impacts things like the jobs provided to local residents that work in the stadium. How the team drives the local economy is always a consideration when it comes to salary negotiations.
Everything from stadium food to the price of parking, to the prices of real estate as well as the impact on the area’s education system, will be directly affected by who’s on the roster.
The source of the data
With all of this considered, the next logical question is – where does this data actually come from?
The majority of this data is based on publicly available online. Teams can source data from local city economic reports, analysis of the change in local real estate prices over a period of time, and looking at how similar personnel decisions impacted other teams and their local economies. In addition, monitoring social media reviews and posts plays a part in gathering real-time insights on a possible new contract.
The challenging part is weaving through the masses of available data, gathering the precise required online data, and leveraging it in a way that provides real-live insights that can be practically used in negotiations.
This is where the art of using alternative or external data comes in and is the reason why most professional teams work with data scientists that are skilled in these calculations.
With sports contract numbers only increasing with each new major deal, onlookers can become suspicious about how these offers are arrived at. The truth is, every major sports contract is based on well-calculated data. Every professional sports deal is a comprehensive business decision, one that relies on well-orchestrated, comprehensive data.
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