Rampant steroid usage tainted Major League Baseball (MLB) in the late 1980s, and decades later, steroid usage is still a serious issue. Steroids, along with other illegal substances, have heavily impacted various statistics in professional baseball (Petersen, Jung, & Eugene Stanley, 2008). Many records—a more notable one being Barry Bond’s 73 homerun season—have been broken during this timeframe, which has been coined as the “Steroid Era” of baseball (Rymer, 2012). In a sport with more statistics than any other, the impact steroid usage has on baseball statistics becomes fascinating, and this impact can be mapped in a variety of ways. In fact, there is an entire branch of statistical modeling specifically for baseball formally known as “sabermetrics”(SABR). The core of this thesis is an attempt to analyze the statistical impact steroids have on baseball statistics at a professional level. By utilizing various baseball sabermetrics to collect data, this study examines how steroids have a careerewide impact on the statistical distribution of a MLB player who used steroids with respect to a player who refrained from usage of such illegal substances. By applying various analyses on said data, potential differences can be made quantifiable.These results could be telling enough to portray suggestive anomalies in a MLB player’s statistics. On a larger level, these results could be telling enough to discourage steroid usage among professional baseball players entirely
