The Price of Glory: Exploring MLB Salaries’ Impact on Team Success in the AL and NL
In the realm of Major League Baseball (MLB), astronomical salaries and blockbuster signings are as much a part of the game as home runs and strikeouts. The recent contract extension of a star pitcher, Shoei Ohtani, eclipsing $700 million, has reignited the debate: does throwing money at talent guarantee a team’s success? This piece explores thirty years worth of data (1986–2016) on which active franchises have had the highest total salaries in one season, in both the American League and National League and how those financial statements translated into wins for that season. This study specifically focuses on differences between the American League and National League as well as challenging the prevailing wisdom that more dollars always lead to more wins.
The stereotypical narrative is quite simple: more money means better players and better players ultimately means more wins. Yet as we dive into three decades of data, the story that unfolds is full of complexity and exploration. This investigation pierces through this assumption and reveals a world where the correlation between financial expenditure through salaries and on field success which result in wins, is anything but straightforward. Not only is data analytics becoming a popular tool when fans are interested in the business and strategic aspects of the sport but also for the sports business and front office of these teams themselves. This information could be used for future predictions as well as discovering upcoming trends.
While trying to narrow down some of the research to find the best trends, I started off by looking at the top fifteen highest salaried franchises in one year for each league. I began by filtering the data based on franchises that are active in the MLB right now along with using a specific range of years which was from 1986 to 2016. This range was strategically put in placer due to the salary data only dating back to 1985. The salaries were calculated by grouping all of the players who were on payroll that season for any active franchise and adding them all up.
In the American League (AL), the average number of wins per season, just including regular season, was 81 games. The average total salary per franchise, per year, was $127,815,592.67. The New York Yankees franchise had a combined total salary of $223, 978, 886 in 2013 which was the highest recorded total salary in the AL. That year the New York Yankees recorded a regular season record of 85–77. The overall correlation coefficient between win loss ratio and salary was 0.02205.
On the other hand, in the National League (NL), the average number of wins per season was 80 and the average total salary per franchise was 133,321,959.20. The Dodgers franchise had the highest combined salary in the NL with $223,362,196, in 2013 recording a record of 92–70. The overall correlation coefficient between win loss ratio of all the franchises and salary was 0.05332.
As you can see, both leagues had a relatively non linear relationship between the highest salaries and win loss ratio. This ultimately means that there was no direct correlation between spending a significant amount of money for salaries and putting more ‘W’s’ in the win column. Although there was no major difference in the average number of wins in the regular season between the AL and NL, there was a significant increase of approximately $5,500,000 in average total salary per franchise in the NL compared to the AL. That is an extraordinary amount of money!
Now you might be wondering, how about the other side? How about the lowest spending franchises in each league and how does that compare to the highest spending franchise, in terms of putting wins in the win column. Well, in the AL, from the fifteen lowest spending franchises, the average combined salary in one given year was $9,367,419.87. In the NL, the average salary was $11,392,546.67. Here comes the crazy part. The average wins for the AL was 83 and the average wins for the NL was 81. The average wins for both the AL and the NL was higher in the lowest salary group compared to the highest salary group, yet the average salaries were tremendously lower. Additionally, the correlation coefficient for the AL was 0.00675 and for the NL, it was -0.431.
The extensive analysis of MLB salary data and team performance over three decades decisively challenges the notion that higher spending equates to more victories. In both the American and National Leagues, the minimal correlation between team payrolls and win-loss records shows a complex reality: success in baseball isn’t bought, but built. This discovery underscores the significance of strategic planning, analytics, and efficient resource allocation over just financial power.
Looking into the data, it’s pretty clear that just throwing money at players isn’t the golden ticket to winning games. The correlation between how much teams spent and their win-loss records was surprisingly weak. This was a real eye-opener because it shows that there’s a lot more to winning games than just having deep pockets. It makes you wonder if teams that spend less but win more have figured out something special.
So, what does all this mean for MLB teams moving forward? Teams are going to have to get more bang for their buck by leaning into analytics and getting creative with how they build their rosters. This could totally change the game, making it more about brain power and less about who has the biggest wallet. It’s kind of exciting to think about a future where MLB teams win by being clever and making smart, data-driven decisions, instead of just outspending everyone else. This study really drives home the point that in baseball, the best team might not be the one that spends the most, but the one that spends the wisest.
