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Moneyball: Analyzing ROI in Major League Baseball

Moneyball: Analyzing ROI in Major League Baseball

Ever since Michael Lewis published his book Moneyball: The Art of Winning an Unfair Game, franchises and front offices have taken a new approach to running their organization, especially when assembling a roster.

In the National Football League, all teams are allowed to spend the same amount of money each season, with a slight increase each year. This is known as the salary cap and it allows for a relatively level playing field, seems like a no brainer, right?

Despite this, the MLB has yet to adopt a salary cap, which is why we see historic franchises build super teams while newer teams are stuck struggling. With this in mind, I set out to answer a very important question: Are teams with a higher payroll finding more success than teams with a lower payroll?

Using statistics from Baseball Reference and payroll data pulled from Kaggle’s MLB salary dataset, I created a comprehensive view of team efficiency, allowing me to calculate team ROI.

The project involved scraping, joining, and cleaning data using Python, loading it into a Postgres database on AWS, and building visualizations in Looker. The key metric? Payroll-Per-Win, a simple but revealing ratio that exposes which teams are underperforming (or overachieving) relative to their budgets.

Beginning with one of the most overachieving teams I evaluated, the 2022 Tampa Bay Rays had one of the lowest payrolls in the league, yet they managed to finish with 86 wins and a playoff berth. Their cost per win was among the lowest in baseball, making them arguably the most efficient franchise in MLB that year.

But what set them apart? Smart scouting, elite player development, and avoiding overpriced free-agent deals

On the other hand, we often see high payroll teams underperform, for example; the 2023 New York Mets. That season, the Mets spent a record-setting $350 million on payroll, yet managed to miss the playoffs. According to the data, their salary-per-win ratio was one of the worst in MLB history.

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This is indicates two things: first, assembling a winning roster on a budget is possible, given the right approach. Second, a higher payroll doesn’t directly lead to more, as we see big name teams fall short year after year.

In a league with no salary cap and widening payroll gaps, data has become crucial in assembling a roster. Yet even with more emphasis being placed on analytics departments and performance metrics, one of baseball’s biggest questions remains largely unanswered: Are teams getting what they pay for?

One thing is for sure: The smartest franchises aren’t just the ones with the biggest checkbooks, but the ones that spend with strategic intent. As the 2022 Rays proved, a low budget doesn’t need to keep you out of the playoffs.

You can explore the full data and interactive visuals from this project here:
👉 MLB Payroll Efficiency Dashboard

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