Introduction

Our topic involves MLB (baseball) statistics. We are both athletes at St. Olaf, and love watching/playing baseball. In today’s game, payroll is becoming and more and more important factor in terms of a team’s success. Last MLB season, the World Series was between the Los Angeles Dodgers and the New York Yankees, who were 5th and 2nd in total payroll allocations with 241 million USD and 309 USD respectively. Additionally, the New York Mets, the team with the highest total payroll allocations in the MLB last season with $317 million, lost to the Dodgers in the National League Championship Series1. As high payrolls are seemingly becoming essential for team’s to perform well in the MLB today, we were interested in the actual correlation between payroll and success. We found a dataset that looks at various statistics for each team by year from 2011 to 2024, focusing primarily on payroll allocations. Through this dataset, we can measure success through both win rate (a column we created by dividing wins by total games) and regular season results (the standings before postseason: no playoffs, wildcard, or division winner).

This topic is especially important in the game of baseball today, because of its growing importance and disparity among teams. Some team’s have an abundance of wealth, while others are already at their cap. Team’s with minimal payroll are scrambling to match bigger teams like the New York Yankees, who have seen large amounts of success in the recent past. But is payroll really what creates this success? This leads to our research question: “How does a team’s total payroll allocations in a given year affect success in that year?” On a simpler level, is success directly correlated with payroll? Or are there other, more important ways to win in the MLB? One example of a team whose low payroll didn’t limit their success is the “Moneyball” Oakland Athletics. In 2002, the Athletics had the third-lowest payroll in Major League Baseball of only 41 million USD. However, by using advanced analytics to construct their roster, the Athletics were able to win 103 games that year, and advance to the American League Divisional Series in the playoffs2. Was this case an outlier, or is payroll not as much of an indicator of success as we are made to believe?

There is prior research on the correlation between payroll and success, but there are minimal definite conclusions. In fact, there are multiple sources that found conflicting results about the impact of a higher payroll on wins. On the one hand, payroll may lead to more capital freedom, but not necessarily success3. On the other hand, payroll can help gather better, more skilled players who in turn help a team win more games4. So which one is more apparent? Our study aims to fill the general uncertainty and knowledge gap of the importance of payroll in the MLB today. As MLB fans, this is extremely interesting and can have a lot of significance in better informing underlying causes of a franchise’s success, not only in baseball, but in any professional sport (assuming that findings can be generalized).

The dataset5 we will be diving into comes from kaggle.com, with statistics gathered directly from Spotrac, which is a company that provides detailed information on player contracts, salaries, and other financial data for professional sports. This is an observational study, with each row representing a given team in a given year. The data includes variables such as average age, payroll allocations, and wins/losses measured for each team from 2011-2024. Data comes from end-of-year statistics for each of these 14 years. For this project, we will primarily analyze team name, year, total payroll allocations, active 26-man payroll allocations, win rate, and regular season result. Team name is a nominal categorical variable with 30 levels, one for each team in the MLB. Year is also a nominal categorical variable with 14 levels, 2011 through 2024. All playoff allocations are discrete numeric variables measured in dollars. Win rate is a continuous numeric variable measured in terms of proportion of wins in a given year. Regular season result (pre-playoff standing) is an ordinal categorical variable broken down into “no playoffs”, “wild card”, and “division winner”. The purpose of this dataset is to give ability for analysis of various metrics in relation to each team and for a certain year. We will utilize this data to help conclude the importance of payroll for a team’s success/failure, by using data science and data visualization between the variables described above.

Analysis

How do total payroll allocations impact a team’s win rate?

To start, we want to explore how payroll allocations impact a team’s win rate. In other words, how does having more money to spend on players impact success in a given season?

This is a scatter plot that shows the relationship between total payroll allocations and win rate for all 30 Major League Baseball teams by year (from 2011-2024). The x-axis represents total payroll allocations in increments of 100 million USD, ranging from 0 to 3.5 (350 million). The y-axis represents win rate, as a proportion of games won out of total games, ranging from 0.25 to 0.75. Each point represents a given team in a certain year, with 420 total. A blue fitted trend line runs through the data points, indicating a clear positive correlation (positive slope) between payroll allocations and win rates, with teams with larger payrolls generally achieving higher win rates.

Figure 1: Higher total payroll allocations are associated with higher win rates for MLB teams. Data are based on and derived from official MLB statistics via Kaggle.com, on each of the 30 MLB teams from 2011-2024 (420 total observations). Payroll allocations represent the amount of money used on a given team, measured in hundreds of millions of US dollars. Win rate is calculated as total wins divided by total games, measured as a proportion between 0 and 1. A test of slope (p-value < 0.001) shows a statistically significant correlation between payroll allocations and MLB team’s success in that given year.

The data shown in figure 1 depicts a clear positive relationship between payroll allocations and win rate in Major League Baseball. Teams with higher payrolls tend to achieve higher win rates, as seen in the upward trend of the plotted points and the resulting positive slope of the fitted trend line. A slope of 0.0047 suggests that for every additional 100,000,000 USD, win rate is expected to increase by 0.47%. While there are certainly exceptions–some teams with lower payrolls still manage strong win rates, and vice versa–the general pattern suggests that higher payroll allocations correlates with better performance. This aligns with existing ideas about competitive advantages in baseball, where franchises with higher payroll allocations attract top talent, which results in more wins. In answering the research question, evidence in figure 1 suggests that payroll allocations positively impact a team’s success in the MLB from years over the last 15 years.

Do payroll allocations also affect whether or not a team makes the playoffs?

To say win rate is the only important indicator of success is naive. Truthfully, what matters most is the team’s position in the playoffs. Franchises care about World Series, not just winning 65% of games, right? Thus, we need to examine the payroll allocations of teams that are division winners, wild cards, or did not make the playoffs at all.

This is a bar chart displaying the average team payroll allocations of Major League Baseball teams based on their categorical regular season results from 2011 to 2024. The x-axis categorizes teams into three regular season result groups: No Playoffs, Wildcard, and Division Winner. The y-axis represents total payroll allocations, measured in 100 million USD increments, ranging from 0 to 1.5 (150 million). This chart shows that teams failing to make the playoffs have the lowest payroll allocations on average, followed by teams that qualify as wildcard contenders, while division winners allocate the highest payroll amounts, on average. This trend suggests that higher payroll investments generally correlate with stronger regular-season performance.

Figure 2: Higher average payroll allocations are associated with better regular season results. Data are based on 30 MLB teams from 2011-2024, measured by official MLB statistics. Average payroll allocations are measured in hundreds of millions of US dollars. This is categorized under regular season results, which is broken down into ‘no playoffs’, ‘wildcard’, and ‘division winner’, each of which get progressively better respectively. Visually, we see a strong relationship between payroll and regular season results; payrolls are higher, on average, for teams with more successful regular season results.

Payroll allocations vary significantly by regular season results. In figure 2, we see that teams that fail to make the playoffs tend to have the lowest payrolls on average, while teams that do make the playoffs (wildcard and division winners) tend to have the highest payrolls. More specifically, the increase in payroll for division-winning teams suggests that financial resources contribute to more success in securing postseason berths. This pattern reinforces the notion that payroll allocations are a strong predictor of team success, in that higher payrolls often lead to more success in the MLB, directly answering our overall research question.

Are the very best teams those with the highest payrolls? Are the very worst teams those with the lowest payrolls?

We know that teams with higher payrolls tend to be more successful than teams with lower payrolls. But now we want to know if this is accurate of the best of the best. To do this, we need to analyze the success of teams in the top and bottom 5% of total payroll allocations.

This is a scatter plot displaying the relationship between total payroll allocations of MLB teams and corresponding win rates, for the top and bottom 5% of teams (top and bottom 21 teams). The x-axis displays payroll, which is measured in hundreds of millions of dollars, with the bottom 5% ranging from 0.25 (25,000,000 USD) to 0.52 (52,000,000 USD) and the top 5% ranging from 2.4 (240,000,000 USD) to 3.5 (350,000,000 USD). On the y-axis is win rate, which is measured as a proportion of games won out of total games, and ranges from 0.3 to 0.7. Each point represents an MLB team in a certain year 2011-2024, and is labeled by the team's abbreviation on the graph. To enhance appearance, the points are colored green for the top 5% payroll group, and red for the bottom 5% payroll group. We see that the average win rates for the higher payroll teams are clearly higher than that of the lower payroll teams. Thus, there is visual evidence that higher payrolls lead to more successful seasons for MLB teams, based on win rate.

Figure 3: Teams with higher payroll allocations tend to be more successful (in terms of win rate) than teams with lower payroll allocations in the MLB. Based on teams with the top and bottom 5% of total payrolls, higher teams experience higher win rates in a given season (mean of 0.58 vs 0.46, respectively). Data are based on 30 MLB teams from 2011-2024, measured by official MLB statistics. Average payroll allocations are measured in hundreds of millions of US dollars, while win rate is a measured as a proportion of games won. Visually, we see a strong relationship between payroll and win rate. 

# A tibble: 2 × 2
  Payroll_Group         Avg_Win_Rate
  <chr>                        <dbl>
1 High Payroll (>$240M)         0.58
2 Low Payroll (<$52M)           0.46

Figure 3 shows a strong difference in win rates between the higher and lower payroll clusters. The observations in the top 5% of payroll allocations have an average win rate of 0.58, while the observations in the bottom 5% of payroll allocations have an average win rate of 0.46. This 12 percent difference in significant; it is a difference of nearly 20 wins in a given season (out of 162 total games). Thus, while there are certainly exceptions to this trend outlined in figure 3 (like the Tampa Bay Rays in 2020), there is strong visual evidence that higher payrolls are correlated with more winning seasons. This notion aligns with the general expectation and more money allows for more talent and, in turn, more wins. Overall, this plot provides further evidence that payroll allocations are positively correlated with a team’s success in the MLB.

Do these trends apply to allocations on the active 26-man roster as well?

The active 26-man roster is based on the players that are designated to play, or have a chance of playing in a given game. Essentially, it includes the team’s top players. This roster excludes injured, retained, or buried payroll allocations, making it a good representation of a team’s spending on what matters most: the active players.

This is a scatter plot including regression lines for each team (as well as an overall trend line), showing the relationship between Active 26-Man Payroll Allocations and Win Rate in the years: 2012, 2018, and 2024 (6 year intervals). The x-axis displays Active 26-Man Payroll Allocations, measured in hundreds of millions of US dollars, ranging from 0.1 (10 million USD) to about 2.75 (275 million USD). The y-axis displays win rate, which is measured as a proportion of games won out of total games, and ranges from 0.25 to about 0.7. Each line is a linear regression of a given MLB team using data from 2012, 2018, and 2024. Lines with a positive slope are colored green, while lines with a negative slope are colored red. We see that a large majority of lines (26/30) have a positive slope (green), and the overall trend line (black, dashed) is increasing as well.

Figure 4: MLB teams, for the most part, experience more success (in terms of win rate) when more money is allocated to the active 26-man roster. Data are based on all 30 MLB teams in years 2012, 2018, and 2024, and are collected by official MLB statistics on Kaggle.com. This graph shows trends in win rates dependent on active 26-man payroll allocations over time in the MLB. Active roster payroll allocations are measured in hundreds of millions of dollars, while win rate is measured as a proportion of games won in the given season. In the graph, the green lines represent lines with increasing slope, or higher win rate over time when more money is spent. The red lines represent lines with negative slope, or decreasing win rate as more money is spent. We see substantially more green lines (26/30), which suggests that a large majority of teams experience higher win rates as they allocate more money to the active 26-man roster.

Data in figure 4 shows a strong correlation between active roster payroll allocations and win rate, both by team and in general. We see 26 out of 30 teams (colored green) experience higher win rates when their active roster allocations are higher. In addition, the overall slope is increasing, signaling that more money on active players means higher win rate. While there are exceptions to this trend (4 out of 30 teams see the inverse effect), the general trend from figure 4 reveals a high positive correlation between active payroll and win rate. This trend aligns with expectations, and provides further evidence to go with our previous analysis. Overall, as a league, teams win more games when they spend more on the active 26-man roster.

Conclusion

A pressing topic in Major League Baseball is the importance of payroll on success. Can team’s with less money still be equally successful? Are the financial powerhouses always dominant? We wanted to fill a general gap of uncertainty on this topic by analyzing the impact of payroll on success in the MLB

To do this, we used a dataset called “MLB Team Payrolls 2011-2024” from Kaggle.com which extracts data directly from Spotrac on all 30 teams in the MLB. The dataset includes variables like team name, total payroll allocations, active payroll allocations, wins, losses, and post-season standings.

In analyzing this dataset using data science, we found that teams with more money are generally more successful. Specifically, we drew four key conclusions. First, total payroll allocations are positively correlated with win rates in the MLB. Second, teams that do better in the regular season (and thus are seeded better in the post-season) tend to have higher payrolls. Third, the top 5% of payrolls perform significantly better than the bottom 5% of payrolls, in terms of win rate. Fourth, the vast majority of teams experience seasons with higher win rates when they increase active roster payroll allocations.

In conclusion, while there can certainly be outliers, it is a reality that teams with more money tend to be more successful in the MLB. I guess that’s how it works in the real world!

  1. Blasi, Weston (25 October. 2024). “The Yankees-Dodgers World Series Features the Biggest Combined Payroll Ever.” Market Watch. https://www.marketwatch.com/story/the-yankees-dodgers-world-series-features-the-biggest-combined-payroll-ever-316dff5c.↩︎

  2. Popdust (28 Feb. 2025). “How Moneyball Changed the Way We See Sports Forever.” Popdust. https://www.popdust.com/how-moneyball-changed-sports-forever.↩︎

  3. Hall, S., Szymanski, S., & Zimbalist, A. S. (2002). “Testing Causality Between Team Performance and Payroll: The Cases of Major League Baseball and English Soccer.” Journal of Sports Economics. https://doi.org/10.1177/152700250200300204↩︎

  4. Schwartz, Noah L. and Zarrow, Jason M. (2009). “An Analysis of the Impact of Team Payroll on Regular Season and Postseason Success in Major League Baseball.” Undergraduate Economic Review. https://digitalcommons.iwu.edu/uer/vol5/iss1/3↩︎

  5. Treasure, C. (2024). MLB Team Payrolls 2011-2024. Kaggle.com. https://www.kaggle.com/datasets/christophertreasure/mlb-team-payrolls-2011-2024↩︎