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Physical Size Associations to Offensive Performance Among Major League Leaders

Crotin, Ryan L.1; Forsythe, Charles M.2; Karakolis, Thomas3; Bhan, Shivam3

The Journal of Strength & Conditioning Research: September 2014 - Volume 28 - Issue 9 - p 2391–2396
doi: 10.1519/JSC.0000000000000551
Original Research

Crotin, RL, Forsythe, CM, Karakolis, T, and Bhan, S. Physical size associations to offensive performance among Major League leaders. J Strength Cond Res 28(9): 2391–2396, 2014—Minimal work has studied physical size effects on statistical performance among Major League players. In this study, longitudinal, bivariate, and regression analyses studied the impact of physical size on offensive baseball statistics within a homogeneous talent sample of Major League batting leaders. Body mass index (BMI) was calculated from heights and weights that were publicly available to form a statistical database of 4,360 offense leaders from 1950 to 2010. Repeated-measures analysis of variances examined differences in anthropometrics and baseball statistics between each decade from 1950 to 2010. Bivariate correlation and linear regression analyses evaluated BMI as an independent variable of influence, where all tests applied an a priori significance level (p ≤ 0.05). After 1980, offensive performance increased (p ≤ 0.05) concurrent to body mass and BMI growth (p < 0.001). During the 1960s, only batting average and on-base plus slugging percentages were found statistically decreased (p ≤ 0.05). All baseball statistics were positively correlated and predicted by BMI (p < 0.001). Consideration to covariant factors is required in data interpretation, yet nonetheless, our results showed physical size (BMI) to positively influence Major League offensive statistics. Over the 60-year period, greater body weight-to-height proportions owed to improved competitive performance, which suggests greater emphasis on hypertrophic stimuli in training and nutrition, as well as selection of larger professional baseball prospects.

1Baltimore Orioles, Major League Baseball Club, Baltimore, Maryland;

2Department of Kinesiology and Health Education, The College of Education, The University of Texas at Austin, Austin, Texas; and

3Department of Kinesiology, Faculty of Applied Health Sciences, University of Waterloo, Waterloo, Ontario, Canada

Address correspondence to Dr. Ryan L. Crotin,

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Major League organizations have recently inspired investigation into how body composition affects athletic and baseball performance (2,5,6). In 2010, physical size had peaked among position players, with athletes typically weighing more than 93 kg, standing taller than 1.85 m, and having a body mass index (BMI) greater than 27 kg·m−2 (4). Physical size seems to be a distinguishing factor between talent pools in baseball, where offensive leaders were found larger than the reference cohort, demonstrating greater height, mass, and BMI by at least 2 cm, 5 kg, and 0.8 kg·m−2, respectively for each year studied (4). Advances in hypertrophic stimuli, such as improved strength and conditioning practices among baseball populations (youth, high school, and collegiate), emergence of sport nutrition, and global advances in nutrition may have facilitated the availability of larger players for professional drafts. Therefore, throughout the modern era of baseball, athletes of greater mass relative height seem to have greater advantages at the professional level (2,4,6).

Effects of body composition and physiological performance on baseball statistics had been described among a heterogeneous participant pool, which included widespread skill classifications of various ages in professional baseball (Rookie, A, AA, AAA, and ML) (2,5,6). Skill heterogeneity involving disparity in talent may been most influential on the results, and therefore, the strength of association of lean body mass, grip strength, 10-yard sprint, pro-agility, and vertical jump peak power to common offensive statistics (homeruns [HR], slugging percentage [SLG], and total bases) remains in question (5). Rather than baseball statistics, body composition seems to better describe physiological outcomes, where body fat percentages and lean mass proportions show strong evidence in explaining effects on running speed (2), linear acceleration, agility, and grip strength (5,6), among professional baseball players.

The longitudinal value of body composition assessment remains undetermined, as access to such details is limited, making it virtually unknown how baseball performance has been affected by morphological changes in percentage of fat or lean muscle mass. Recently, BMI had been shown to offer historical insight (4), as height and weight measurements are still taken today at the time of player signing. Because of public availability, it is suggested that BMI derivations be used as a simpler method to describe anthropometric proportionality from which longitudinal anthropometric analyses can be performed over a series of decades, including years for which body composition testing and records were unavailable. Therefore, this study features as homogeneous talent sample of offensive leaders in Major League Baseball to examine physical size effects on offensive statistics through BMI calculations. Strength and conditioning coaches working in Major League Baseball will benefit from this study by understanding how an athlete's mass proportion relative to his height can influence on-field batting performance. Within a homogenous talent pool, larger players are expected to associate with greater offensive prowess, while an evolutionary trend revealing increased BMI is anticipated to be concurrent to statistical enhancement from 1950 to 2010.

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Experimental Approach to the Problem

To lower the confounding effect of talent, a homogenous population of top 10 leaders across several offensive categories, including both American and National League players, was selected from 1950 to 2010, and then grouped by decade. Major League leaders whose statistical entries repeated over more than 1 decade were removed from analysis.

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Statistics, body weights, and heights were extracted from a free publicly available source carrying licensed Major League data ( Because no human subjects were involved in the study, all data were performance-based and have been made public since 1950, research ethics were waived for this study. In total, 4,360 players were analyzed (age, 29.1 ± 0.60 years; height, 1.88 ± 0.13 m; mass, 91.0 ± 6.46 kg; BMI, 26.4 ± 1.33 kg·m−2). Homerun totals (HR), SLG, batting averages (BA), on-base percentages (OBP), runs scored (RS), runs batted in (RBI), and on-base plus SLG (OPS) were examined incrementally over 10-year periods and associated to BMI.

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Mathematical descriptions provided below express nondiscrete offensive statistics and the BMI calculation:



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Statistical Analyses

One-way repeated-measures analysis of variances examined changes in player anthropometrics (height, weight, and BMI) and baseball statistics, as the dependent variables, across decades from 1950 to 2010. A Bonferroni's correction factor was applied in post hoc as significant differences in mass relative to height were shown in previous work, with minimal changes seen to player height (4). Pearson's moment correlations evaluated the strength of association between statistical measures and BMI, where linear regression analyses estimated the predictive nature of BMI on offensive performance. Statistical significance determined a priori was set at p ≤ 0.05 for all statistical tests, and all statistical analyses were performed using SPSS 20 (SPSS Inc., Chicago, IL, USA).

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Anthropometric measurements by decade are represented in Table 1, presenting mean heights, weights, and BMIs for league leaders from 1950 to 2010. From the 1980s to 1990s, body weight increased to 8.3 kg (18.3 lbs) (p < 0.001) and then increased again from 2000 through 2010 by 4.3 kg (9.5 lbs) (p < 0.001), for a total of 12.6 kg (27.8 lbs) throughout the 30-year span. Although not statistically significant, mean heights show gradual growth over the 60-year analysis, but more rapid were advances in body mass from the 1980s onward, which led to increased kilogram mass proportionality during the 1990s at 27.6 kg·m−2 to a maximum of 28.6 kg·m−2 found in the last decade (p < 0.001).

Table 1

Table 1

Changes in common statistics were presented in Figure 1, illustrating chronological increases in offensive performance throughout 6 decades. Statistical increases seen from the 1980s through the current decade are aligned with anthropometric changes noted in Table 1. Homerun totals were found decreased from the 1960s to 1970s (p ≤ 0.05), which occurred void of changes in physical size, whereas increases were found between the 1980s and 1990s, and the 1990s to the most recent decade (p < 0.001), which reflects increased body mass proportions. Overall, HR totals were greatest during the most recent decade, approaching an average of 43 HRs per season, where both body mass and BMI reached a maximum. Runs batted in increased similarly, as the 1990s mean was increased from the 1980s (p < 0.001), and again RBIs increased from the 1990s to the current decade (p ≤ 0.05). Slugging percentage increased from the 1980s to the 1990s only (p < 0.001), whereas OPS decreased from the 1950s during the 1960s (p < 0.001), but again increased from the 1980s before the year 2000 (p < 0.001). Runs scored and BA, 2 hallmark statistics denoting scoring capacity, were significantly increased from the 1980s during the 1990s (p < 0.001), where only BA decreased in 1960s from the 1950s (p ≤ 0.05), which reflected OBP results.

Figure 1

Figure 1

Pearson's moment correlations identified an association of BMI on all statistical expressions among league leaders from 1950 to 2010 (p < 0.001). Presented in Table 2, OPS showed the greatest bivariate association nearing R = 0.37, whereas BA was weakest in association to BMI at R = 0.20. Significant linear regression estimates (p < 0.001) showed reasonable predictability of offensive performance from BMI.

Table 2

Table 2

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Correlation coefficients were found to be on the lower spectrum of associative strength, yet nonetheless, physical size was positively correlated with statistical performance. Similarly, advancement in offensive performance was seen in parallel to increased mass proportion to height, perhaps owing to larger and more productive offensive players from 1980 onward. These findings aligned with our initial hypotheses, as larger athletes among a homogenous talent population were expected to show greater offensive prowess. Because mass proportions were shown greater amid minimal changes in body height, we interpret Major League leaders to have greater BMIs over time, and especially in relation to other affiliated cohorts (Rookie level, A, AA, AAA) (2,5,6). Slowed progression in height with respect to mass gains had been described previously (4,8), as greater Latin presence was seen among league leaders, who stood shorter in stature than the average American athlete (1,8).

Given an inability to assess body composition in this study, nor having access to such information in public records, we were unable to define BMI as proportion of lean mass relative to height. If made possible, stronger correlation coefficients could be expected, as previous lean body mass associations to HRs (R = 0.478) and SLG (R = 0.474) were greater than what was discovered by our results (HRs, R = 0.29; SLG, R = 0.34) (5). Collective anthropometric research demonstrating greater body weight relative to body fat percentage represented greater lean mass and increased BMI ratings among professional baseball players (2,5,6), where hitting power was found greatest for athletes of larger anthropometrics (4–6). With respect to BMI only, OPS, a hybrid statistic combining OBP and SLG, showed the greatest association (R = 0.37), demonstrating a similar anthropometric influence on combined power and scoring potential performance.

Linear regression analyses supported the estimation of traditional offensive statistics from BMI, yet many associative biologic factors must be considered in conjunction with predicted baseball statistics from anthropometry. For example, a 1.68 increase in HRs is suggested as a predicted increase for a league leading power hitter who augments his mass relative to height from 28 to 30 kg·m−2, where the current calculations cannot explain body composition or improvement in physiological function. If lean mass gains resulted in an increase in BMI, a constitutive effect on strength physiology may be much more explanatory for improved offensive performance. This has been evidenced by previous work, where professional baseball players reporting greater lean body mass similarly had advanced neuromuscular function, whereby offering greater linear speed (2), agility, and grip strength (2,5,6) tests improved statistical prowess. Physiological gains owed to strength training are speculated to increase BMI after 1980, where concurrent improvement in offensive prowess could be explained by hypertrophic factors, offering greater cross-sectional area (force production) and neural recruitment of muscle fibers (contractile speed). The combined product of force and contractile velocity increases muscular power, which can result in greater sprint and swing acceleration capacity and has the potential to improve one's chance of hitting an extra-base hit, and ultimately scoring (2–4). Age is a secondary biologic covariant to influence greater lean mass gains, which has been shown in older professional baseball players, and likely their BMI records therein (6). In contrast, age also poses a nonbiologic influence, which may be more impactful to statistical presence, as older players intuitively gain greater competitive experience, which allows for better understanding of their approach to hitting, which is a considerable factor void of improved neuromuscular function.

Because heights and weights are registered at the time an athlete signs his professional contract, the anthropometric connection seen with offensive prowess validates scouting selection of larger athletes. This has been described previously among a heterogeneous population of Major League athletes, where the sport has transcended their scouting rubrics to forecast anthropometrics (4). It has also been noted that anthropometric changes in the mainstream or secular population has occurred with improved nutrition and greater dedication to strength training, where BMI growth would be evident in younger male populations (4,8).

From the 1960s onward, newer stadiums were being built and roster expansion took place (9). With smaller dimensions and increased team expansion, the potential to increase power numbers could be intuitive, as baseballs had to travel shorter distances over fences to record HRs, and having more substitutes, had the ability to rest league leaders to be more effective in subsequent games and to avoid injury, which would decrease opportunities to augment power statistics. However, it is believed that smaller playing field surfaces were responsible for the decline in BA and OBP seen at this time, for the opportunity to record a fair ball in play for a hit was diminished. Statistical augmentation could also be owed to expansion of the regular season, where games were increased from 154 to 162 during this time frame (9), which again allowed for greater data accumulation but would lower the probability for safely recorded hits (9), where more outs were able to be recorded because of reduced outfield dimensions. This era of baseball was also noted as the “Pitchers Era,” where the strike zone had been expanded to include the top of the shoulders and the bottom of the knees, where batters had to adjust to the new dimensions set forth by the umpire (9). Secondly, the slider was introduced to competition, adding to pitch deception and improving the opportunity for recorded outs (9). Evidenced by the 1968 season, pitchers were dominant in baseball, recording the highest number of shutouts in a single season (9), where in the 1969, the strike zone was again set back to its previous dimensions to improve offensive performance (9), which our data lend credence toward the resurgence in power and scoring potential in the decades that followed the 1970s.

During the 1990s, offensive power (HR, SLG, RBIs, and OPS) had surged, which led to the belief that baseball manufacturers were creating a “Juiced Ball” (9). Although, not scientifically confirmed, baseballs used from 1990 to the early 2000s were believed to increase impact recoil and exit speeds after contact to increase distance traveled. When cross-sected, the core of the baseball was found to be rubber, instead of traditional cork, which may have been attributed to environmental conservation, and not a business ploy, but may have contributed to the slant in impact ratings (9). Therefore, statistical advancement presented from 1990 to 2010 may have been influenced by changes in baseball materials in addition to anthropometric gains.

Ted Williams was a top 10 performer, and in most cases, a Major League leader, in at least 1 offensive category over 3 decades with the exception of 1942–1945, where he performed military service for the U.S. Army (1952 and 1953), as he served in the Korean War (1959 and 1960), and as he approached retirement (7). Because his data records stemmed over 4 decades, he posed a statistical bias to this study, and therefore, Williams was omitted from analyses because of repeat influences on anthropometric measurements. Williams had a lifetime BA of 0.344, where his record of the highest BA in a single season still stands, and is the all-time Major League leader in OBP with a career mark at 0.482, where decreased performance seen in BA and OPS from the 1950s to 1960s may have been even greater had he been included. Williams played his last game September 28th, 1960, at the start of the decade, otherwise known as, the Pitchers Era (7,9).

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Practical Applications

Undeniably, Major League leaders transformed body mass-to-height proportions from 1980 onward, for which a rise in both physical size and offensive performance was concurrently seen among baseball's most talented hitters and that BMI positively associated to statistical performance over the 60-year analysis. Although BMI provides strong longitudinal evidence to determine changes in anthropometrics among professional athletes, homogeneity is required among the samples studied to reduce the cofounding effect of talent on statistical associations that link physical size to offensive performance. Both biologic and nonbiologic influences must be considered as covariant factors to impact on-field performance, which may be directly or indirectly attributed to increased BMI. Strength and conditioning coaches are important personnel to help maximize biologic factors through improved quality of hypertrophic stimuli (strength training and sports nutrition consumption) without the use of illicit performance enhancing drugs. The scope of strength and conditioning practice in Major League Baseball is one that meets many challenges, as front office, medical, and field staff can at times attempt to downplay its importance and voice unsupported concerns that athletes will become “too big,” “too tight,” or will lose athleticism if they participate in regular strength training. Further research is required to understand the role of strength and conditioning owed to statistical performance, where at present, the emphasis of strength and conditioning programs can only be implied through BMI determinations. Furthermore, nonbiologic factors, such as selection criteria for prospect drafts, competitive rule restructuring, altered park dimensions, improved pitching performance, and changes in equipment design must also not be ignored in understanding statistical enhancement amid increased physical size.

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strength and conditioning; batting; hitting; BMI; mass

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