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This collegiate essay explores how modern baseball is utilizing sabermetrics in player development and how it is continuously expanding alongside the game we all know and love.

Written By: AJ Stone (9/14/24)

Sabermetrics in Sports

A.J. Stone

Ottawa University, Department of Humanities

English 155, College Writing

Dr. Austin Newport

September 16, 2024

Abstract

This essay will analyze how statistical analysis, specifically sabermetrics, is essential to modern baseball. Sabermetrics, though recognized only recently, have influenced the game for decades and continue to evolve. Using team and player data, I will demonstrate how sabermetric approaches have reshaped baseball strategies and performance. The use of advanced metrics such as bat speed, exit velocity, and expected statistics has driven teams and players to improve on-field results by targeting controllable factors. This essay argues that understanding and applying sabermetric data is now critical for success in baseball, and the math supporting this will be discussed throughout.

Introduction

Numbers do not lie. As our society evolves, numbers remain a constant metric. Bill James, known as the “father of sabermetrics,” championed detailed statistical analysis in modern baseball. Sabermetrics is the study of analytical data within baseball, helping teams assess a player’s true value. As a cornerstone of the sport, sabermetrics is growing more influential each year. This data contributes to team and player success, shaping how the game is understood. Eventually, sabermetrics may define how baseball is perceived.

Using sabermetrics can be complex, but I would implore you not to ignore its strengths. Actively instituting sabermetrics into how a player or a team functions can allow for a better understanding of the game. Within the confines of sabermetrics, there is room for growth and continued development. The math stands as is, but it will continue to expand. New formulas and ideologies are regularly surfacing and creating a lane for new ways of exploration in relation to talent. Baseball has always been a numbers game. Sabermetrics takes it one step further and lets the numbers have the final say. Older generations fear that this may diminish the “human” aspect of the game. Whether that is true or not is a moot point due to the success that the new wave of sabermetrics has rolled in with. At the end of the day, winning is all that matters. Sabermetrics is a winning formula.

Method

Sabermetrics have revolutionized the way baseball is perceived. The beginning of sabermetric analysis started with a movement known as “Moneyball. Moneyball encompasses the mindset of value per dollar that small-market MLB teams use to maximize their spending. Teams such as the Athletics, Rays, and Brewers have employed this strategy, and it has worked to a tee. The movie “Moneyball” was famously written about the Oakland Athletics, as they were the first team to really employ the sabermetrics in the Moneyball mindset. Sabermetrics and the value they can bring to any size market team far outweigh the cost it takes to employ the strategy.

Sabermetrics tend to refer to the use of critical data analysis within the game of baseball. According to The Sabermetric Revolution (2014), “Baseball, much more than other team sports, lends itself to measurement.” This highlights how much emphasis is put on the mathematics behind a team and players’ performance. These measurements allow for the randomness of baseball, which can sometimes be a player’s demise, to be accurately depicted. When a team can measure “luck,” it becomes much easier to predict success. Time after time, players have random spurts of success; sabermetrics allow for the randomness to be measurable.

According to an article titled The Current State of Data and Analytics Research in Baseball (2022), “Since the 1920s, people have been trying to utilize baseball data to their advantage to predict outcomes and develop winning teams.” This demonstrates the longevity that data analysis possesses within the game of baseball. A winning team’s success derives from its ability to realize its own potential. This can be done through a multitude of practices. Understanding your own output as a player should be a cornerstone in player development and predicting future success. When a team pairs a good understanding of data with talent, the sky’s the limit. Current State of Data and Analytics Research in Baseball (2022) also states, “Today, sabermetrics has led baseball to become one of the biggest data-driven sports worldwide. At the fan level, websites like FanGraphs, Baseballsavant, Baseball Prospectus, and Pybaseball [7] have become increasingly popular…” The data is becoming increasingly more accessible. This means anyone can take it upon themselves to learn. With teams being put in a “ball in your court” scenario, it is now up to the head officials of these organizations to take affirmative action.

According to a study done by Syracuse University called Sabermetrics: Baseball analytics and the science of winning (2024), “Sabermetrics is a science of sport. It is the empirical analysis of baseball through statistics, used to predict the performance of players, giving teams a winning edge.” This definition points towards the beneficial tendencies sabermetrics have. Employing sabermetrics can allow for sustained success.

In their entirety, sabermetrics advance a team and players’ ability to enhance their own success. The math demonstrates growth in measurable ways and shows positive and negative tendencies. Teams that have moved towards the sabermetric approach have seen the positive effects through the on-field results. As sabermetrics continue to grow and change, it is important to understand how they can be used for the better.

Discussion

This discussion will reference sources and use data to point towards the beneficiaries of sabermetrics in baseball. Data within sabermetrics gives coaches and teams the ability to find “hidden” talent. Although the talent was never really hidden at all, it just required a bit of digging. Complex formulas found within the mathematics behind sabermetrics interpret and break down a player brick by brick. This allows for the minute details provided through a player’s on-field performance to be interpreted and reassessed by whoever is in charge of the organization.

The evidence for why sabermetrics are optimal is compelling: teams repeatedly see that data-driven analyses identify clear paths for improvement and often lead to tangible gains in performance.

A classic player-to-player example that can be used to portray how useful sabermetric data can be is comparing Kolten Wong and Dante Bichette. Dante Bichette was an outfielder for the Colorado Rockies in the 1999 season. He had a batting average of .298 and hit 34 home runs with 133 RBIs. Kolten Wong, in comparison, had a 2019 season where he hit .285 with 11 home runs and 59 RBIs. These surface-level numbers would point towards Bichette being the more valuable player by a landslide. However, this is nowhere near the case. Using the stat WAR (Wins Above Replacement), we can determine a player’s true value on a per-game basis. According to Fangraphs (2010), “This value is expressed in a wins format, so we could say that Player X is worth +6.3 wins to their team while Player Y is only worth +3.5 wins, which means it is highly likely that Player X has been more valuable than Player Y.” Although his batting statistics were much lower in all facets, Kolten Wong amounted to 5.1 WAR. Dante Bichette, on the other hand, was a -3.9 WAR. A negative value points towards him being a detriment to his team’s success despite his good season at the plate. This is because WAR takes the entire game into account. Hitting, baserunning, and fielding are all inserted into the calculations. Bichette was one of the worst fielders in major league baseball and was a far below-average base runner who had the benefit of playing in Colorado, where it is much easier to hit. Wong was a league-average hitter who was a plus baserunner and one of the better fielders at his position in the entire league. Having a stat that takes all of this into account is very useful to a front office. Knowing a player like Wong will be much more valuable than a player like Bichette, even when he might cost less money, is one way to stay ahead of the competitive curve.

The strides taken by teams and players to get ahead in sabermetrics show how important they really are. Teams and players have one job at the end of the day: to win. Seeing so many of them opt for the sabermetric route again and again shows exactly why it is important to embrace the math. The results speak for themselves, and the people in charge shout over said results, raving about these new advancements. All in all, it should be easy to see from any perspective that baseline stats are a thing of the past and that analytical data has taken the driver’s seat in the game we love.

The results of this study clearly show and back up why sabermetrics should be fully embraced in the modern game of baseball. Teams and players alike have seen exponential growth in their on-field results after embracing the sabermetric ways. There is nothing wrong with how we used to do things, but there is something right about finding a better way to go about it. Sabermetrics are simply an enhanced version of the game we love.

My conclusion is slightly limited in the sense that I could not create my own control group, but I still believe the research backs my theory. For future research, I would propose data-driven studies done on younger and professional players on a year-to-year basis.

Conclusion

Sabermetrics have continued to mature with the game of baseball as time passes. Mathematics is important when making team and player-based decisions regularly. Front offices have noticed this new wave of math and the effect it has had on the game around them. Front offices and players will go along with the newest form of sabermetrics that becomes available to them.

References

A guide to Sabermetric research. (n.d.). Society for American Baseball Research. https://sabr.org/sabermetrics

Baumer, B., & Zimbalist, A. S. (2014). The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball. University of Pennsylvania Press. https://books.google.com/books?hl=en&lr=&id=ckMYAgAAQBAJ&oi=fnd&pg=PP1&dq=sabermetrics+in+baseball+journal+article&ots=i9h6A-KqjF&sig=-JyPhImoK4Rig37g9qxEvI4ST7Y#v=onepage&q=sabermetrics%20in%20 baseball%20journal%20article &f=false

Burroughs, B. (2020). Statistics and baseball fandom: Sabermetric infrastructure of expertise. Games and Culture, 15(3), 248-265. https://doi.org/10.1177/1555412018783319

Koseler, K., & Stephan, M. (2017). Machine Learning Applications in Baseball: A Systematic Literature Review. Applied Artificial Intelligence, 31(9–10), 745–763. https://doi.org/10.1080/08839514.2018.1442991

Mizels, J., Erickson, B., & Chalmers, P. (2022). Current state of data and analytics research in baseball. Current Reviews in Musculoskeletal Medicine, 15(4), 283-290. https://doi.org/10.1007/s12178-022-09763-6

Syracuse University. (2024). Sabermetrics: Baseball analytics and the science of winning. Syracuse University / Blog. Retrieved September 28, 2024, from https://onlinegrad.syracuse.edu/blog/sabermetrics-baseball-analytics-the-science-of-winning/#:~:text=Sabermetrics%20is%20a%20science%20of,predictions%20based%20on%20previous%20data

What is WAR? (2024, November 3). Sabermetrics Library. https://library.fangraphs.com/misc/war/

(n.d.). Baseball-Reference.com. https://www.baseball-reference.com/

Annotated Biography

A guide to Sabermetric research. (n.d.). Society for American Baseball Research. https://sabr.org/sabermetrics

This is the official website for sabermetric research. The information published on this site is

straight from the source. These people are the brains behind the bronze of sabermetric data analysis. This information is backed up by mathematical research and formulas used to predict steady ascension or decline in performance.

Baumer, B., & Zimbalist, A. S. (2014). The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball. University of Pennsylvania Press. https://books.google.com/books?hl=en&lr=&id=ckMYAgAAQBAJ&oi=fnd&pg=PP1&dq=sabermetrics+in+baseball+journal+article&ots=i9h6A-KqjF&sig=-JyPhImoK4Rig37g9qxEvI4ST7Y#v=onepage&q=sabermetrics%20in%20 baseball%20journal%20article &f=false

This source takes a deep dive into the development and growth of sabermetric analysis within

modern baseball. It uses the “Moneyball” movement from the early 2000s as a prime example of the “jumping off point” for sabermetric analysis. This analysis has numbers backing up its points and uses the statistic WAR as a prime calibrator.

Burroughs, B. (2020). Statistics and baseball fandom: Sabermetric infrastructure of expertise. Games and Culture, 15(3), 248-265. https://doi.org/10.1177/1555412018783319

This scholarly source examines the infrastructure associated with sabermetric analysis in

reference to baseball. It theorizes that sabermetrics serve as a platform for a more in-depth analysis of the game as it is played. They also provide a new market for study and reporting. Sabermetrics provide a new microcosm for interpretation within the game we know and love.

Koseler, K., & Stephan, M. (2017). Machine Learning Applications in Baseball: A Systematic Literature Review. Applied Artificial Intelligence, 31(9–10), 745–763. https://doi.org/10.1080/08839514.2018.1442991

This source examines how machine learning can be applicable to the current state and use of sabermetrics. This source demonstrates key points through data and formulas while describing how these can be applied to baseball today.

Mizels, J., Erickson, B., & Chalmers, P. (2022). Current state of data and analytics research in baseball. Current Reviews in Musculoskeletal Medicine, 15(4), 283-290. https://doi.org/10.1007/s12178-022-09763-6

This article highlights the transformation within the game of baseball that was signaled by the

development of sabermetrics. It uses context from before sabermetric analysis to portray the changes.

within the game. It also demonstrates and develops how sabermetric analysis is used in the present.

Syracuse University. (2024). Sabermetrics: Baseball analytics and the science of winning. Syracuse University / Blog. Retrieved September 28, 2024, from https://onlinegrad.syracuse.edu/blog/sabermetrics-baseball-analytics-the-science-of-winning/#:~:text=Sabermetrics%20is%20a%20science%20of,predictions%20based%20on%20previous%20data

This article is derived from Syracuse University. Sabermetrics is referred to as the “science of

winning.” This conveys the argument that they are necessary in the modern game of baseball. This article provides a brief history of sabermetric analysis, along with the definition of what it is. It uses numbers and statistics to present valid arguments that convey the overall point of the article.

What is WAR? (2024, November 3). Sabermetrics Library. https://library.fangraphs.com/misc/war/

Fangraphs is a website used by baseball fans to decipher between statistics and look through small details in a player’s biography. Fangraphs defines all statistics and allows for further exploration of a player’s career.

(n.d.). Baseball-Reference.com. https://www.baseball-reference.com/

Baseball Reference is a website containing all the career achievements of teams and players. It has specific stats and awards for different careers. Baseball Reference is often used to double-check stats and different career years players may have had. It is constantly being updated and observes up-to-date statistics and achievements for players and teams alike.