This article focuses on the NABBP’s initial years during which the principal issue was the “bound game” versus “fly game,” the former being the existing method of play. As Marshall Wright noted in his history of the NABBP, “no rule was more hotly contested than the bound out rule.”2 Robert Tholkes called it “the most contentious rules issue of the [1857–65] period.”3 Richard Hershberger went further, describing it as “the most contentious rules argument in the history of the game [and] the strangest.”4 Not surprisingly, as Warren Goldstein noted, “this issue attracted a huge amount of attention in the sporting press.”5 And yet, oddly, the episode is virtually unknown to the modern baseball community.

Under the bound game, a batter could be put out if his batted ball was caught on the first bound (bounce), as well as being caught on the fly, i.e., before it first struck the ground. Under the fly game, only a fly catch counted as an out. The issue was debated and voted on at most annual NABBP conventions until the bound out (on fair balls only) was finally eliminated in December of 1864. This, of course, was a critical step in the evolution toward modern baseball. This article summarizes that history, then empirically analyzes the difference between the two rules in terms their effect on runs scored. In other words, how important was the change from the bound game to the fly game in terms of game outcomes?

Regarding the NABBP’s name, in 1858 “it went without saying” that the involved players were amateurs and so the word was not needed in the title. After all, professional play had not yet evolved, and the NABBP did not take its first step toward formally “outlawing” compensation for players until its March 1859 convention.6 Also, the NABBP was hardly national in scope, as both contemporary observers and modern historians have pointed out. The initial membership consisted only of clubs from the New York metropolitan area and its geographic footprint did not extend much further during its first several years. Last, strictly speaking, the membership consisted of clubs, not individual players. But at that time clubs consisted only of players; there were no stockholders, managers, administrators or other “hired hands” involved in club operation. As Ryczek put it: “players and management…were generally one and the same.”7 Member-players organized, “financed” (via dues), and operated the clubs, and so the distinction was irrelevant for naming the organization. For example, today professional baseball clubs include many non-playing “members” (employees).

BACKGROUND

At the NABBP’s founding, the contemporary and somewhat informal baseball rules stipulated that a batter could be put out if his batted ball was caught on the first bound as well as on the fly. This rule was included in an early set written down in 1845 by the Knickerbocker Club of New York to guide intramural play among club members. They were concise, containing only 14 specific rules, called “sections,” on a single page.8 Section 6 reads as follows: “A ball being struck or tipped, and caught either flying or on the first bound, is a hand out.”9 David Block observes that the bound out is “usually thought of as a Knickerbocker innovation [although] the rule may actually have been a legacy of earlier pastimes.”10 By the mid-1850s, the Knickerbocker rules had become a model for other clubs playing the New York game. For example, an 1856 New York Clipper article lists 17 rules of baseball, including a Rule 6 describing the bound out that was worded identically to Section 6 of the Knickerbocker rules.11 At its initial meeting, the NABBP adopted by majority vote a set of playing rules largely based on the Knickerbocker rules including the bound out, although the club no longer supported it.12

Catching on the bound was usually the easier play, requiring less athletic skill. This was particularly true in this pre-glove era when balls were caught bare-handed. Outfielders could stay back and catch short hits over the infield on the first bounce rather than running in and attempting a risky bare-handed fly catch, risky regarding both a successful catch and possible injury. Infielders catching a proverbial one-hopper immediately would record an out (e.g.) without having to throw to first base and without the first baseman having to make a bare-handed catch, both opportunities for errors. Of course, athletic plays are certainly possible on balls that have bounced once in order to catch them before a second bounce occurs. However, overall it was generally understood that the fly game was significantly more demanding.13

Accordingly, the game’s aficionados came to regard the bound game as less “manly.” This was an issue in the early days of baseball because of sensitivity regarding criticisms about adults playing a child’s school-yard game. These could be countered if baseball was perceived as athletically challenging and “scientific,” i.e., requiring high skill levels and strategy. The various clubs had differing average skill levels, with less skilled players attracted to so-called “muffin” clubs that favored the bound game precisely because it was easier. It also “leveled the playing field” between clubs with different skill levels, to the advantage of weaker clubs. Thus, tensions arose between these clubs and those comprised of more skillful players who generally preferred the fly game that maximized the advantage of their athletic ability.

Aside from the fly game’s increased difficulty, proponents of the bound game were concerned that the fly game gave an advantage to the batter that might bring forth an undesirable cascade of other rule changes to offset that advantage.14 Also, as noted above, bound catches decreased the likelihood of injury to players’ hands in this pre-glove era. Another factor was that easier outs meant fewer errors and less scoring and therefore shorter games, which was more attractive both for players and for working fans with limited time to spend at the ball park. And in this era before stadium lights, it meant fewer games cut short because of darkness.

BASEBALL CONVENTIONS OF 1857–6415

The first convention of baseball clubs was held in New York City in two sessions on January 22 and February 25 of 1857, although the NABBP was not founded until the next convention a year later. Sixteen clubs were involved in at least one session of the 1857 meetings, 14 in both, all from the New York metro area. Conventions continued to be held in New York throughout the Association’s first decade. At the January 1857 meeting a Rules Committee was appointed to formulate proposals for playing rules to be presented to the general body for discussion and approval by majority vote. This established the modus operandi for determining rule changes that continued throughout the NABBP’s history: the Rules Committee met prior to the convention to develop rule change proposals to be acted upon at the convention. All matches between NABBP clubs were required to use the rules thereby established, although for particular games occasional departures were allowed on an ad hoc basis by mutual agreement of the involved clubs. Intramural contests among members within clubs were not subject to the requirement.

Clubs were allowed two delegates to the conventions and all those present were required to vote.16 Thus the number of votes cast on a particular issue could exceed the number of clubs represented. Some were concerned that delegate selection biased voting against the fly game. Inter-club matches where the rules were required were between the “first nines” consisting of each club’s best players, while the usually many more members who were less skilled mainly played less formal intramural games. However, delegates did not need to be from a club’s first nine and often included “muffin” members. It was argued that these delegates voted with their intramural games in mind, expressing their preference for the easier bound game.17

The bound game versus fly game question was an issue at each annual convention until the bound out on fair balls was finally eliminated at the convention of December 1864, first taking effect for the 1865 season. The bound elimination votes at each of the nine conventions from 1857 to 1864 are summarized in Table 1. And the issue was no doubt an informal subject of debate during the years prior to the NABBP’s formation.

Table 1. Votes to Eliminate the Bound Out at Baseball Conventions Prior to Seasons 1857–65

At the initial 1857 convention a set of playing rules was adopted, essentially a modified version of the Knickerbocker rules that included the bound out, as noted above. The bound vs fly game issue was “hugely controversial” and, perhaps for that reason, the Rules Committee side-stepped it and did not present a proposal for change.18 At the March 1858 convention, with 23 clubs present, “considerable time was consumed” over a fly game-only proposal made by the Committee before it lost by a close 13–17 vote.19 Again, at the March 1859 convention, “a lengthy discussion ensued upon a proposition” by the Committee to eliminate bound outs, but it failed by a one-sided 15–47 vote.20 The number of clubs had increased by more than 50 percent in one year, from 23 to 36, and the new members may have been largely “muffin” clubs leery of the fly game. At the March 1860 convention, with a pre-Civil War high of 62 clubs present, “the biggest controversy…as it was for several years, was whether to stay with the bound game.”21 Again, a proposal for its elimination lost, by 37–55. This was less one-sided but still not close. The convention that preceded the 1861 season occurred in December of 1860, and henceforth the annual conventions would be held in December. Fifty-four clubs attended the meeting on December 12, 1860, the last pre-war convention. They again debated a fly game proposal described as “base ball’s most contentious issue,” but once more it did not pass, although the vote was closer at 42–51.22

The Civil War began in April of 1861, just prior to the 1861 season, and the main fighting ended in April of 1865. The NABBP conventions continued during the war years although the number of participating clubs dropped significantly. At the first two war conventions, in December of 1861 and December of 1862, only 34 and 30 clubs, respectively, were in attendance. This was only about half the pre-war high number. Likely because of the distractions and uncertainties created by the onslaught of war, the Committee on Rules and Regulation proposed no playing rule changes at either meeting. As William Ryczek noted, with the onset of the war, “the baseball world fell almost dormant.”23 Thus, while the fly game vs bound game issue was discussed at both meetings, no action was taken.

That changed at the December 9, 1863, convention that preceded the last war-time season. A war-time low of 28 clubs attended. The Committee’s decision to again present a proposal may have been prompted by hopeful war news. The Union victory at Gettysburg and the fall of Vicksburg, both in early July 1863, had made a Confederate defeat and a return to normality seem inevitable. In fact, the Committee proposed a fly game rules amendment and “the highlight of the [December 9] meeting was the discussion and voting on the adoption of the fly game.”24 Highlight or not, the fly game proposal again went down, albeit for the last time, by a close 22–25 vote. At the next convention on December 14, 1864, 30 clubs participated. Although unknown at the time, this meeting preceded the first post-war season. Once more “the main event [was] the vote on the fly game…[which] at last prevailed by a 32-to-19 count,” a solid majority.25 Henceforth, outs on fair batted balls could only be made by a catch on the fly, an important step in the maturity of the sport and in establishing baseball as an adult pastime. And, of course, modern baseball would be radically different if the bound game had not been eliminated. Nevertheless, the bound out for foul balls was retained for another two decades.26

THE IMPACT ON GAME OUTCOMES

After years of controversy, the bound out rule finally was eliminated from NABBP match play. The 1865 season was the first without the rule and an interesting question is: how much difference did it make? All involved in the debate agreed that under the fly game getting outs was more difficult. One would expect, therefore, that the sudden elimination of the easier bound out would result in more runs scored and allowed by each club, i.e., an increase in the total runs for each of its games. Thus, the difference in total runs, if any, before and after the rule change would be an approximate measure of the difference in difficulty.

An ideal experiment to determine this would be to arrange a significant number of fly and bound games between each of several pairs of teams of similar strength and observe the total runs scored. Of course, this is not possible. In reality, the best we can do is compare total runs scored in 1864 and 1865 in games among the same set of similar teams in each year. The New York metro area with its many clubs at that time provides the best opportunity for such an analysis. We identify a set of similar metro area clubs on the field in both 1864 and 1865 that comprise most of the major area clubs in those two years. We examine the games played within this group; games against outsiders are excluded. While professionals were ostensibly not allowed under NABBP rules, it’s clear that by 1865 some sub rosa player compensation was occurring, and so most, if not all, of these metro-area clubs were at least semi-professional.

Our sample is based on the lists of clubs identified for 1864 and 1865 in Wright’s encyclopedic NABBP history.27 We select 14 significant New York metro-area clubs present in both years, including those across the Hudson River in New Jersey and the East River in Brooklyn, then a separate city. The Wright data include game scores for all sample games.

Table 2 shows the 14 sample clubs in alphabetical order and their won-lost records in games among themselves for both years.28 The Atlantics at 12–0–1 and Mutuals at 14–2–0 dominate 1864, with the Actives and Excelsiors the only other clubs above .500. In 1865 the Atlantics again are at the top at 14–0–0, with five other clubs above .500. In 1864, club games-played range from the Eurekas and Stars at three each, to the Empires and Mutuals at 16 each, with six clubs at 10 or more games. In 1865, the range is from the Resolutes at two to the Actives at 16, with seven clubs at 10 or more.

Table 2. Sample NABBP Clubs and Their 1864 and 1865 Won-Lost Records in Games Among Themselves

 

Table 3 shows the average total runs scored and allowed per game (RPG) in 1864 and 1865 for our 14 sample clubs, and the increases in RPG from 1864 to 1865. The average RPG was 38.2 in 1864 and 48.9 in 1865. In 1864 the Eagles and Eckfords had the highest two RPGs with 45.0 and 44.3, respectively. The Gothams and the Empires had the lowest with 32.0 and 32.7, respectively. In 1865 the Stars and the Excelsiors had the highest RPG with 67.0 and 63.0, respectively. The Mutuals and the Newarks were the lowest with 35.9 and 39.6, respectively.

 

Table 3. Increase in Runs Scored and Allowed Per Game from 1864 to 1865 for 14 Sample NABBP Clubs in Games Among Themselves

The key variable in our analysis is the increase in each club’s RPG from 1864 to 1865, shown in the last column of Table 3. This provides a rough measure of the difference in difficulty between the bound and fly games. The Star and Enterprise clubs had the largest RPG increases with 23.3 and 22.3, respectively. The Eckfords and the Mutuals had the smallest increases at –1.0 (a decrease) and 0.5, respectively. For our 14 club sample, the average RPG increase from 1864 to 1865 was 10.7 or 28.0 percent. There was but one decrease.

The RPG increase has a high degree of statistical significance. We apply a paired difference-between-means Student t-test with a null hypothesis of a zero difference between the two years for our sample clubs. The t-statistic is 5.07 with a significance level of 99.99 percent (p-value 0.0001, degrees of freedom=12).29 Alternatively, we can apply a binomial test with a null hypothesis that the individual club RPG increases are equally likely to be positive or negative (probability=0.5). We find that the probability of observing one or zero negative values (decreases) out of 14 is only 0.00091.30 The two significance tests are consistent and provide strong evidence that the increase in runs from 1864 to 1865 was not a random happenstance, confirming that the fly game indeed made fielding more difficult.

It should be noted that in 1864, by mutual consent, clubs occasionally agreed to drop the bound rule for individual games. To the extent that this occurred, the 1864 run totals would have been higher and the increase in runs to 1865 lower. Thus, our above analysis would be an under estimate of the actual impact of switching to the fly game. For example, initially the 1864 Star club of Brooklyn decided to play the fly game only, although it caused difficulties in scheduling games and they dropped the condition mid-season.31 Similarly, in 1865 the rules allowed clubs, by mutual consent, to play the bound game. However, as Hershberger notes, “the new rule was adopted with remarkably little difficulty.…Only a handful of bound games are documented to 1865 or later in adult play.”32

SUMMARY AND CONCLUSIONS

While it seems strange from a modern perspective, in baseball’s earliest days the dominant controversy regarding playing rules was whether to discontinue allowing batters to be called out when their batted balls were caught on the first bounce. It took many years of vigorous debate and several votes at the annual NABBP conventions before the so-called bound game was finally eliminated in December 1864. Accordingly, an out on a batted ball in fair territory could now only be made if the ball was caught on the fly, the clearly more difficult play. This was a key step in establishing baseball as a “manly” sport worthy of serious attention by adult athletes, spectators and journalists.

Our analysis indicates that the quantitative impact of eliminating the bound game involved an increase of roughly one quarter in total runs scored and allowed per game from 1864 to 1865. The reader can of course evaluate whether, qualitatively, this impact was “large,” “middling,” or “small.” Be that as it may, the difference was not so large as to impede the fly game adoption, which seems to have occurred smoothly with little subsequent controversy, i.e., “manliness” was apparently achieved at an acceptable “cost.”

Thus, a critical component of the modern game was in place for the first post-Civil War season. As Ryczek noted, after the “stagnation of the war years…in 1865, the [New York] game was relatively unknown [nationally] and its future clearly in doubt.”33 Nevertheless, the post-war years saw a dramatic growth in the number of clubs adopting the New York game and a major expansion of baseball’s geographic footprint as it truly became the national pastime. For example, at the convention in December of 1865, “the number of official participating clubs stood at 91,” triple the number at the previous convention one year earlier, and the growth continued through the late 1860s.34 The post-war years also saw the transition to the above-board and fully professional game, and in 1869 clubs began to openly (and “legally”) operate as businesses with players as their employees. Switching from the bound game to the fly game likely played an important role in promoting these changes. 

WOODY ECKARD, PHD is a retired economics professor living in Evergreen, Colorado, with his wife Jacky. Among his academic publications are five papers on the economics of MLB. More recently he has published in SABR’s Baseball Research Journal, The National Pastime, and Nineteenth Century Notes. He is a Rockies fan and a SABR member for about 30 years.

Notes

1. For example, see Richard Hershberger, “1857: The First Baseball Convention,” in Jeremy K. Hodges and Bill Nowlin, Editors, Base Ball’s 19th Century “Winter” Meetings: 1857–1900 (Phoenix: Society for American Baseball Research, 2018), 6.

2. Marshall D. Wright, The National Association of Baseball Players, 1857–1870 (Jefferson NC: McFarland & Company, 2000), 83.

3. Robert Tholkes, “Section One Introduction: The Baseball Winter Meetings of 1857–1865,” in Hodges and Nowlin, 1.

4. Richard Hershberger, Strike Four: The Evolution of Baseball (London: Rowan & Littlefield, 2019), 57.

5. Warren Goldstein, Playing for Keeps: A History of Early Baseball (Ithaca and London: Cornell University Press, 1989), 48.

6. Robert Tholkes, “Growing Pains: The 1859 National Association of Base Ball Players Convention,” in Hodges and Nowlin, 22.

7. William J. Ryczek, When Johnny Came Sliding Home: The Post-Civil War Baseball Boom, 1865–1870 (Jefferson, NC: McFarland & Company, 1998), 43.

8. The 2025 Official Rules of Major League Baseball contains 192 pages. https://mktg.mlbstatic.com/mlb/official-information/2025-official-baseball-rules.pdf, accessed April 30, 2026.

9. The complete Knickerbocker Rules, comprising barely more than a single page, are available as part of the 19th Century League and Team Documents Project, organized by SABR’s Nineteenth Century Committee. https://sabr.app.box.com/s/xpr3tl7hw9iwnc5b499pr2yzsv85u8nv/file/1794109396429, accessed April 30, 2026.

10. David Block, Baseball Before We Knew It: A Search for the Roots of the Game (Lincoln NE: University of Nebraska Press, 2005), 86. Block also notes: “Unlike the familiar fly out, however, the bound rule is seldom found in the [early] history of bat-and-ball games.”

11. “Base Ball: How to Play the Game—Rules for Its Government,” New York Clipper, December 13, 1856, 268.

12. Block, 87.

13. For example, see Wright, 82–84; Ryczek, 44–45; John Thorn, Baseball in the Garden of Eden: The Secret History of the Early Game (New York: Simon and Schuster Paperbacks, 2011), 75, 106; David Nemec, The Official Rules of Baseball: An Anecdotal Look at the Rules of Baseball and How They Came to Be (New York: Barnes and Noble Books, 1999), 92; and Goldstein, 48–53.

14. For example, see Tholkes, 20 and 24.

15. This section draws heavily from Part I, Section I: The Baseball Winter Meetings of 1857–1865 in the SABR publication Base Ball’s 19th Century “Winter” Meetings: 1857–1900 (Phoenix: Society for American Baseball Research, 2018), in Hodges and Nowlin.

16. “Constitution of the National Association of Base Ball Players—1861,” 19th Century League and Team Documents Project, organized by SABR’s Nineteenth Century Committee, https://sabr.app.box.com/s/kbe9tr64kel2bgstk58fa5atepq7jk7m/file/1842066890213, accessed April 30, 2026.

17. “The Next Convention: The Fly Game vs. the Bound,” New York Clipper, November 19, 1864, 250.

18. Hershberger, “1857,” 5.

19. Robert Tholkes, “Building on the Foundation: The 1858 National Association of Base Ball Players Convention,” in Hodges and Nowlin, 14.

20. Robert Tholkes, “Growing Pains,” 10 and 21.

21. William J. Ryczek, “1860 Convention of the National Association of Base Ball Players,” in Hodges and Nowlin, 26.

22. John Zinn, “National Association of Base Ball Players 1861 Annual Meeting,” in Hodges and Nowlin, 32.

23. Ryczek, When Johnny Came Sliding Home, 13.

24. Eric Miklich, “To Fly or Not and Other Monumental Changes: The 1864 Convention of the National Association of Base Ball Players,” in Hodges and Nowlin, 49.

25. John Zinn, “National Association of Base Ball Players 1865 Annual Meeting,” in Hodges and Nowlin, 60.

26. Hershberger, Strike Four, 62. For example, an 1879 article “The Bound-Rule in the Fly Game” (New York Clipper, May 17, 1879, 61) argued against the foul-bound out by claiming that its elimination would not lengthen game playing time. In this era of primitive protective gear, catchers often positioned themselves well behind the batter, which in turn enabled bound-out catches on foul-tips that were generally admired as athletic plays.

27. Wright, 82–109.

28. Brief histories for ten of these clubs can be found in Base Ball Founders: The Clubs, Players and Cities of the Northeast that Established the Game, edited by Peter Morris, William J. Ryczek, Jan Finkel, Leonard Levin and Richard Malatzky (Jefferson NC: McFarland & Company, 2013). The four clubs not included are the Enterprise, Gotham, Newark, and Resolute.

29. The p-value and t-statistic were calculated using Excel’s “T.TEST” and “T.INV.2T” functions.

30. The probability was calculated using Excel’s “BINOM.DIST” function.

31. Craig B. Wolf, William J. Ryzcek, and Peter Morris, “Star Base Ball Club,” in Base Ball Founders, 149–50.

32. Hershberger, Strike Four, 61.

33. Ryczek, When Johnny Came Sliding Home, 22.

34. Julia Hodges, “The 1866 National Association of Base Ball Players Annual Convention: Held December 13. 1865,” in Hodges and Nowlin, 64.

NOTABLE LH MIDDLE INFIELDERS PRIOR TO 1871

Reach, the second baseman for the champion Eckfords in 1862 and 1863, and later the Athletics of Philadelphia, was just one of several prominent LH second basemen on top-tier amateur teams of the 1860s. The Rockford Forest Citys had lefty Bob Addy at second base from 1866 to 1870. Playing behind 16-year-old pitcher Albert Spalding, Addy made several noteworthy defensive plays in Rockford’s stunning upset of the Washington Nationals on July 25, 1867.10 During the five years that Addy toiled for the Forest Citys, another lefty, Lip Pike, manned second base for three high-profile opponents: the Athletics of Philadelphia, Mutuals of New York, and Atlantics of Brooklyn. Pike collected a game-high seven assists in the Atlantics’ June 14, 1870, win over the Cincinnati Red Stockings that ended the first openly professional team’s string of 81 games without a loss.11

In contrast to the situation at second base, LH shortstops on prominent amateur teams of the 1860s tended to be part-timers who spent most of their time at other positions. Fergy Malone was the Philadelphia Athletics regular shortstop in 1862, but played the position infrequently after transitioning into catching.12 John McMullin, a pitcher/outfielder destined to be the National Association’s first southpaw to pitch regularly, was one of three shortstops for the 1869 Athletics, and Ed Pinkham, a pitcher/outfielder for various Brooklyn teams during and after the Civil War, dabbled at shortstop for the Eckfords in 1869.13,14

So why did lefties find regular roles at second base during this period but not at shortstop? Individual circumstances aside, two factors would appear to apply: 1) shortstops have less time to make throws to first base than second basemen do, so the extra steps taken by shortstops to get into position end up being costly, and 2) LH second basemen can more often take advantage of their simpler footwork (as compared to righties) in making throws to second base, than LH shortstops can with their similar advantage in making throws to third base.

PREVALENCE OF LH MIDDLE INFIELDERS AFTER 1870

Statistics compiled at Baseball Reference enable a more quantitative sense of the prevalence of LHMIs beginning with the advent of the National Association of Professional Base Ball Players in 1871. As illustrated in Figure 2a, LH second basemen made 296 game appearances in the 1870s across the NA (1871–75) and National League (1876–79), as compared with LH shortstops, who made 257. Ratioed to the 2,031 championship (regular season) games played over that span, LH second basemen appeared in roughly 1 out of every 7 contests, LH shortstops about 1 in 8 (Figure 2b).

 

Figure 2a. LHMI Game Appearances NA, NL, AA, UA, PL AND AL

 

Figure 2b. LHMI Game Appearances Ratioed to Total League Games NA, NL, AA, UA, PL AND AL

In the 1880s, LH second basemen made nearly four-times as many appearances across the three major leagues of that decade (the NL, American Association and Union Association), but at a slightly lower frequency owing to the far greater number of games played. LH shortstops made 739 appearances, about one in every 12 contests. The number of LHMI appearances dropped significantly in the 1890s and by the 1900s, just a handful of games were played with LHMIs; about one in every 330 games for second basemen and once in every 1900 games for shortstops. Though not shown here, LHMI appearances in subsequent decades were even fewer.

Table 1. LHMI Game Appearances by Decade

BILLY BARNIE AND HIS LHMIS

The franchise most reliant on LHMIs was the American Association Baltimore Orioles, which put them in lineups 620 times. Nearly all of those came between 1883 and 1891, under manager Billy Barnie.

Barnie installed lefty Jimmy Macullar as his regular shortstop between 1884 and 1886, used lefty Bill Greenwood as his regular second baseman in 1887 and 1888, and in his final year as Baltimore manager, 1891, started the season with lefty George Van Haltren at short.15 He also wasn’t afraid to plug in other lefties at second base and shortstop for a game or two.

So, why might Barnie have used LHMIs so often? His faith in them may have been a product of his connections to Lip Pike and Al Reach. In 1874, Barnie shared catching duties on the Hartford Dark Blues, a team managed by Pike, and it was Reach who hired Barnie in 1882 to be the manager of his Philadelphia entry in the League Alliance, a team later dubbed the Phillies.16 The author has yet to find quotations from either Barnie or Pike touting the use of left-handed middle infielders, but Reach was known to favor them. In 1898, the then-57-year-old sporting goods mogul was quoted as preferring the use of southpaws at all positions in the infield, reportedly saying that lefties are “in the best natural position to throw to first after making a stop.”17 Perhaps not coincidentally, Reach’s Phillies would be the third-most frequent user of LHMIs after the Baltimore and the Brooklyn franchises.

Table 2. Franchises with the highest number of appearances by LHMIs (1871–2024)

 

Table 3. Baltimore Orioles LHMIs (1883–91)

RECORD OF TEAMS THAT RELIED MOST HEAVILY ON LHMIS

Forty-eight professional teams between 1871 and 1905 had one or more LHMIs appear in 10 or more games (Figure 3): 10 National Association teams, 21 National League teams, 15 American Association teams, one Union Association team and one American League team. Of those 48, only 16 had records above .500. The median winning percentage of the 48 was a lowly .435—equivalent to a 70-win team in a 162-game schedule.

The winningest such team was the 1871 Athletics of Philadelphia (.750 winning percentage), first champions of the NA, whose second baseman was Al Reach. The data points surrounded by pentagons represent Billy Barnie’s Orioles teams, which fall equally on either side of .500. Notably absent from the many nineteenth-century teams listed in Table 4 are that era’s most dominant teams. The NA Boston Red Stockings did not use a single LHMI, nor did the Ned Hanlon-led Baltimore Orioles teams that won three NL pennants in the mid-1890s. The American Association St. Louis Browns played only three games with an LHMI, all in 1882, their only sub-.500 season.

 

Table 4. Winning Percentage of Teams with One or More LHMIs Who Appeared in at Least 10 Games

LH DOUBLE PLAY COMBINATIONS, 1871–2024

With so many teams relying on LHMIs in the late-nineteenth century, which (if any) put two on the field at the same time to form a left-handed double play combination? Online sources such as Baseball Reference don’t currently provide such information, so I set about answering that question myself. Starting with Stathead Baseball queries for lefties who played second base or shortstop between 1871 and 2024, I extracted the number of regular season games each played at those positions by season. I then flagged teams that used a LH second baseman and a different LH shortstop at any time during a season. Finally, I combed through contemporary box scores to identify specific games in which a LH DP combination was used.

This analysis identified 63 regular season games in which a LH second baseman played alongside a LH shortstop; 19 NA games 27 AA games, 16 NL games and 1 AL game. None were found in the Union Association, Players’ League or Negro Leagues, with the possible exception of the 1942 Jacksonville Red Caps of the Negro American League. The Red Caps used lefty William Dyke at second base for one game and lefty Jabbo Andrews at short for one game, but the few Red Caps box-scores that I have uncovered do not show them playing together as middle infielders. A total of 12 teams deployed LH DP combinations, none after 1902. No team employed their LHMI pairings for more than 19 games, with most doing so only once or twice.

The two teams that used a LH double play combination for more than a dozen games, the 1874 NL Hartford Dark Blues and the 1889 AA Columbus squad, each lost more than two-thirds of those contests. In aggregate, teams that used LH double play combinations won fewer than a third of the games they played (20 of 63).

The underlying database used to identify LH double play combinations resides at Baseball Reference, which as of March 2026 lacked definition of the throwing arm for many nineteenth-century ballplayers. Just on teams known to have used a LH second baseman or shortstop between 1871 and 1909, over 100 middle infielders have an unknown throwing arm. Assuming that some of those were lefties, the list of teams that used LH DP combos may well be longer than that shown in Figure 4.

Figure 4. Number of Games Played with Left-Handed Double Play Combination, by Decade and League

Pending future handedness discoveries, let’s take a closer look at the 12 teams we know used a LH double play combination, in particular who were their unorthodox tandems, how those pairings came to be and how they fared in the field. As detailed below, nearly all of these LH double play combinations were stop-gap measures—temporary assignments after the right-handed partner of a LHMI regular proved unable to play or produce.

 

Table 5. List of Teams that Fielded a Left-Handed Double Play Combination

LEFT-HANDED DOUBLE PLAY COMBINATIONS—EXTENDED ENGAGEMENTS

The 1874 Hartford Blue Legs used two double-play combinations: first, Lip Pike at second base and Bob Addy for one game at shortstop and then Addy at short and Pike at short for 18 games. On August 11, Hartford’s regular shortstop, Tom Barlow, fell ill during a home game against the Philadelphia White Stockings. Facing the Whites the next day in Boston, Pike, the team captain, moved regular second baseman Addy to short, and installed himself at second base.20 Barlow returned to the lineup for Hartford’s next NA championship season game, but a few weeks later was hospitalized. Pike put himself at short and left Addy at second, positions they manned for the rest of the season.

In the games that they played together, both Addy and Pike fielded their positions well, registering normalized fielding percentages (ratioed to league average for their positions) of 1.07 and 1.01, respectively. Describing the duo’s defensive work in one contest, the Brooklyn Union wrote “…Addy and Pike played sharply in their positions.”21

Some 120 years later, the cause for Barlow’s lengthy absence at the tail end of the 1874 season was touched on in Ken Burns’ sweeping documentary, Baseball. In the first inning/episode of that eleven-part PBS series, a letter Barlow that sent to the Boston Times was read in which he claimed that a shot of morphine to relieve pain from a catching injury he suffered on August 10, 1874 sent him on a path to addiction.22 Barlow in fact played shortstop that day, and didn’t catch at all for Hartford in 1874, but whatever prompted his illness the next day may have led to the first known use of a LH DP combination in a professional baseball organization.

1874 HARTFORD DARK BLUES

Not for another 15 years did a major league team lean so heavily on a LH double play combination—the 1889 Columbus “Babies,” as some Ohio newspapers called the newest addition to the American Association.23 Throughout that season, lefty Bill Greenwood was Columbus’ regular second baseman, on his way to establishing the major league record for most games played by a LH second baseman (538). When righty shortstop Henry Easterday became unavailable for 17 games while tending to his late father’s affairs, regular third baseman Lefty Marr, a southpaw, manned his position. For three games, on July 6 through 8 against the defending AA champion St. Louis Browns, lefty Spud Johnson backfilled at third base, giving Columbus the only major league lineup known to include a LH second baseman, shortstop and third baseman.24

 

1889 COLUMBUS “BABIES”

In the games where they were paired as middle infielders, both Greenwood and Marr fielded slightly below league average. In their eighth game together, on July 13 in Louisville, Marr committed 5 errors. A merciless game summary in the next day’s Louisville Courier-Journal claimed that “if Mr. Marr could have stopped anything short of a wrecked freight train, the spectators failed to see it,” noted “[Marr] has the bad habit of throwing at the clouds,” and depicted Marr in crude cartoon form as comically bow-legged.25

Figure 5. Lefty Marr depiction in the July 14, 1889 edition of the Louisville Courier-Journal after committing five errors the day before.

LEFT-HANDED DOUBLE PLAY COMBINATIONS—LIMITED ENGAGEMENTS

The 1877 Cincinnati Reds began the year with lefty Jimmy Hallinan as their regular second baseman and righty Jack Manning at shortstop. A month into the NL season, Manning, arguably the worst-fielding shortstop in the league, made two costly errors in a road loss to the St. Louis Brown Stockings. For the Reds next game, back home in Cincinnati on June 5 against the Chicago White Stockings, manager-captain-center fielder Lip Pike installed himself at shortstop. Pike played the position “splendidly” that day according to the Cincinnati Enquirer, but in the Reds’ next game, made four errors in an 11–6 loss.26 Two days later, Pike resigned as captain of the 3–10 Reds and moved back into the outfield.27

1877 CINCINNATI REDS

Through the first nine weeks of the 1879 season, LH rookie Jimmy Macullar spent most days manning shortstop for the Syracuse Stars alongside slick-fielding rookie second baseman Jack Farrell. When Farrell turned up sick for a July 8 battle with the Cincinnati Reds, lefty Hick Carpenter was installed at second base.28 Carpenter, also in his first year as a major leaguer, did well that day but made four errors in his next game as a second baseman; he was “utterly at sea whenever a ball was batted in his direction” according to the Chicago Tribune.29 Farrell replaced Carpenter in the Stars’ next game and Carpenter never again played second base in the major leagues. He did go on to play more games at third base than any other lefty, 1059, most while a member of the Reds. Macullar was also destined to set a positional record, his 325 games at shortstop the most for any portsider.

The inaugural edition of the NL Philadelphia Phillies featured lefty Bill McClellan as its regular shortstop with LH utilityman Bill Harbridge as his backup. When manager-captain-second baseman Bob “Death to Flying Things” Ferguson came up with a finger injury before a game on May 12 with the Chicago White Stockings, he moved Harbridge in from left field for a few games.30 A few weeks later, when Ferguson was away recruiting, Harbridge again replaced him for handful of games.31 In the last of eight games that Harbridge and McClellan were paired as a double-play combination, the Philadelphia Times identified Harbridge as one of several Phillies who made great running catches, and claimed McClellan “outdid himself at short-stop.”32

The first regular season major league game played by the franchise that would become the Dodgers featured captain Bill Greenwood at second base and lefty John Cassidy, a last-minute replacement, at shortstop. The day before, the club had released its sore-armed and/or sore-handed shortstop, Denny Mack.33 An outfielder by trade, Cassidy made two errors in the first inning of the May 1 opener, paving the way for the Washington Nationals to score six runs. Catcher Jack Corcoran was shifted to shortstop for Brooklyn’s next game, followed by Billy Geer, a refugee from the Philadelphia Keystones of the Union Association. Soon to become a prolific and oft-incarcerated check forger, Geer was Brooklyn’s everyday shortstop for the rest of the season.34

As noted earlier, Billy Barnie’s 1884 Orioles had LH Jimmy Macullar as their everyday shortstop. With his 22–13 squad fighting for the AA lead, Barnie put LH catcher Sam Trott at second base in place of light-hitting (.205/.275/.293) Tim Manning for a June 26 game in Indianapolis. Solid infield play by the Trott-Macullar duo “provoked much applause” from Hoosier fans, according to the Baltimore Sun.35 Barnie paired Trott with Macullar five more times that summer. In a July 15 game in Cincinnati, Trott and Macullar teamed up on a 4–3–6 twin-killing that the Sun called “a lightning double play.”36

By 1886, LH Bill McClellan had replaced Greenwood as Brooklyn’s second baseman. On Sunday, May 16, the Brooklyns were hosting the Athletics of Philadelphia for a game at Ridgewood Park in Queens County, a location that allowed the club to skirt state and local blue laws. Unable to handle the swift offerings of pitcher Henry Porter in early going, LH substitute catcher Dave Oldfield was moved to shortstop in the third inning. This proved to be the only middle infield appearance in Oldfield’s brief (48 game) major league career.

 

1886 BROOKLYN

On September 25, 1892, shortstop Bill Dahlen of the Chicago Colts found himself in a Milwaukee courtroom. He was defending himself from a lawsuit filed by the Brewers of the recently-defunct Western League for accepting $500 advance money before jumping to the Colts. In Dahlen’s absence, Chicago captain Cap Anson moved LH Jimmy Ryan from left field to shortstop for that afternoon’s series finale in Pittsburgh. With Dahlen still unavailable the next day for a game in Louisville, Anson kept Ryan at short and moved rookie right fielder George Decker, another portsider, to second base in place of weak-hitting Jim Connor.38 The Colts were “Chicagoed” (shutout) by the Colonels, 11–0, but the Chicago Inter Ocean reported that Decker “played a fine game.”39 Anson kept Decker at second base for the last seven games of the season, paired with Dahlen at shortstop for five and Ryan once again for the final two.

The Colts opened the 1893 season with Decker as their second baseman. Two weeks into the season, Dahlen stopped a “hot grounder” with his left eye during pre-game warmups in St. Louis, and so Anson put Ryan in at shortstop, as he’d done the year before.40 Ryan handled five chances flawlessly but Decker was one of several Colts accused of “particularly rank…work” by the St. Louis Post-Dispatch in a loss to the Browns.41

 

1892 CHICAGO COLTS

 

1893 CHICAGO COLTS

The most recent major league team to use a LH double play combination was the 1902 St. Louis Browns of the American League. Heading into the final day of the season, the Browns had clinched second place behind the Philadelphia Athletics. After winning the opening game of their September 28 home doubleheader with the Chicago White Sox, Browns manager Jimmy McAleer decided to mix things up. He shuffled his regular lineup, moving many of his players out of their regular positions. LH right-fielder Charlie Hemphill started the game at second base, with LH left-fielder (and future Hall of Famer) Jesse Burkett at shortstop. Chicago manager Clark Griffith also got in on the fun, sending catcher Sam Mertes (normally a left fielder) out to pitch, with pitcher Frank Isbell (usually the first baseman) as his backstop. He then had the duo switch positions every inning.

A few frames into the “diamond burlesque,” Burkett went in to pitch, but before he did, he turned a 6–6–3 double play from his position at short.42 Hemphill, the only Brownie to spend the entire game at one position, was lauded for his play in the field by the St. Louis Globe-Democrat. “Hemphill did some really first-class work at second, and he would make a high-class infielder with practice.”43 Over the remaining eight years of his major league career, Hemphill played in the infield just once more—at second base for four innings in 1904.

 

1902 ST. LOUIS BROWNS

DEFENSIVE METRICS

Twin Killings

Across the dozen LH double play combinations identified above, six double plays were turned in which both middle infielders were credited with an assist or putout. The earliest was the 4–3–6 twin killing turned by Trott and Macullar of the 1884 Orioles. The other five were turned by the 1889 Columbus tandem of Greenwood and Marr: a 4–6–3 twin killing on July 6, 1889 and four 6–4–3 double plays pulled off across three games later that same month.44 Six more double plays were converted in which only one of the two LH middle infielders was credited with an assist or putout.

Excluding the 1874 NA duo of Addy and Pike, as double play totals were frequently left unreported in most contemporary accounts of NA games, LH double play combinations were involved in a double play roughly once in every 40 chances (0.0236 DP/chance). That is significantly less frequent than annual major league averages for all middle infielders between 1876 and 1902, who turned between 0.039 and 0.072 DP/chance (Figure 7). Further analysis would be needed to tease out how much of that difference is due to the left-handedness of the double play combinations versus their lack of familiarity, either to one another or the position they were playing.

Figure 7. Average DP/chance for middle infielders across all major leagues, 1876–1902.

Fielding Percentages

Looking at fielding percentages for regularly-used LHMIs relative to their peers, an interesting trend emerges. During the NA years (1871–75), roughly half of the left-handed middle infielders who appeared in 10 or more games fielded above league-average. That group included second basemen Al Reach, Bob Addy and Lip Pike as well as shortstop Billy Redmond of the short-lived 1875 St. Louis Red Stockings. From 1876 through 1890, LHMIs fielded their positions at a level above league-average in only four of 33 instances where a player appeared in 10 or more games—shortstop Jimmy Macullar of the 1884 Orioles (1.005), second baseman Bill McClellan of the 1885 Brooklyns (1.001), second baseman Bill Greenwood of the 1887 Orioles (1.024), a year in which he led all AA second basemen in fielding percentage, and Elmer Sutcliffe of the 1888 Detroit Wolverines (1.023). Every LHMI used for 10 games or more in a season after 1890, totaling 11 instances across eight players, fielded below league-average.45

The inability of LHMIs to perform defensively at what would now be called replacement level may well have reinforced the perspective that lefties were ill-suited for the middle infield positions and helped contribute to their dying off.

 

Figure 8. Fielding percentages for all LHMIs who appeared in 10 or more games in a season, normalized to league average for their position.

The last data point in Figure 7 corresponds to Willie Keeler, a LH outfielder who played a dozen games at second base for the 1905 New York Highlanders. The future Hall of Famer, who advised batters to “keep your eyes clear and hit ‘em where they ain’t,” was no fan of left-handers as middle infielders.46 A few years before manning the keystone sack for the Highlanders, Keeler was asked if a left-handed second baseman, shortstop or third baseman could succeed in the infield. “No, not in the big league” was his reply, made at a time when the NL was the only major league in operation.47 Keeler’s stance, similar to that of Chadwick before him, still governs the placement of left-handed ballplayers all these years later. 

LARRY DeFILLIPO is a retired aerospace engineer and former Division III college pitcher who lives in Kennewick, Washington, with his wife Kelly. His work has been published in BRJ, The National Pastime and several SABR special publications, most recently a celebration of the 2001 Seattle Mariners titled “Two Outs, So What!” Particularly intrigued by baseball’s formative years, he has twice presented at the Fred Ivor-Campbell Nineteenth Century Baseball Conference. He’s authored dozens of game stories for SABR’s Games Project, many ballplayers and ballpark biographies for SABR’s Biography Project, and serves as a fact-checker for both of those endeavors.

Author’s Note

As an 11-year-old southpaw, I was stationed at second-base, by a Little League coach who was willing to defy convention. Long fascinated with that experience, I had the opportunity to relive it of sorts 40 years later, by briefly playing shortstop on a senior softball team.

Sources

The author relied on Baseball Reference for season-specific player, team and league statistics and on box scores and summaries published in the following newspapers for game-by-game statistics: Baltimore Sun, Boston Evening Transcript, Boston Globe, Brooklyn Eagle, Brooklyn Times, Brooklyn Union, Buffalo Courier-Express, Chicago Inter Ocean, Chicago Tribune, Cincinnati Enquirer, Cleveland Evening Post, Cleveland Leader, Cleveland Plain Dealer, Columbus Dispatch, Detroit Free Press, Hamilton (Ontario) Spectator, Hartford Courant, Indianapolis Journal, Kansas City Journal, Kansas City Times, Louisville Courier-Journal, New York Clipper, New York Sun, The New York Times, New York Tribune, New York World, Philadelphia Inquirer, Philadelphia Sunday Dispatch, Philadelphia Times, Pittsburgh Commercial Gazette, Pittsburgh Post, Rochester Democrat and Chronicle, St. Louis Globe-Democrat, St. Louis Republic, St. Paul Globe, The Sporting Life, Troy Daily Times, Washington National Republican, Washington Post, Washington Chronicle, Worcester (Massachusetts) Evening Gazette.

Notes

1. Lauren Julius Harris, “In Fencing, What Gives Left-Handers the Edge? Views From the Present and the Distant Past,” Laterality, January 2010: 15.

2. Peggy Kane-Hopton, “Recipe for a Setter,” USA Volleyball, https://usavolleyball.org/resource/recipe-for-a-setter/, accessed March 20, 2026.

3. “Luke Appling Stats & Facts,” This Day in Baseball website, https://thisdayinbaseball.com/luke-appling-page/, accessed July 11, 2025.

4. Alex Pavlovic, “Pitching Panda: Pablo Sandoval’s Journey From Wild Little Leaguer to Mowing Down Dodgers,” NBC Bay Area website, April 28, 2018, https://www.nbcbayarea.com/news/sports/pitching_panda__pablo_sandoval_s_journey_from_wild_little_leaguer_to_mowing_down_dodgers/61167/.

5. “Left-handers who played 2B, post-1920,” Quirky Research website, https://www.quirkyresearch.com/baseball-lists/left-handers-who-played-2b-post-1920/, accessed July 12, 2025. On May 22, 1954, Nino Escalera of the Cincinnati Reds filled in for regular shortstop Roy McMillan in the bottom of the eighth inning for one batter: Stan Musial. Escalera was stationed not on the infield dirt for Musial’s at-bat, but as fourth outfielder on the right side of the field. Tony S. Oliver, “Nino Escalera,” SABR Biography Project, https://sabr.org/bioproj/person/nino-escalera/.

6. David Block, Baseball Before We Knew It (Lincoln, Nebraska: University of Nebraska Press, 2006), 67.

7. Richard Sandomir, “Founding Rules of ‘Base Ball’ Sell for $3.26 Million in Auction,” New York Times, April 14, 2016, https://www.nytimes.com/2016/04/25/sports/baseball/founding-rules-of-baseball-sell-for-3-million-in-auction.html; “The Laws of Base Ball,” Doc Adams Baseball website, https://docadamsbaseball.org/photo-galleries/laws-base-ball/, accessed July 10, 2025.

8. New York Clipper, August 11, 1866.

9. New York Clipper, January 11, 1873.

10. A play-by-play account published in the Washington Daily National Intelligencer on the following Monday highlighted a “good play” by Addy in the first, a “well done” on a pop fly in the fifth and a ball “put lively to first” in the eighth for an inning-ending double play. An adjacent article described the final testimony in the trial of fugitive John H. Suratt for his role in the plot to kidnap President Abraham Lincoln. That scheme resulted in John Wilkes Booth assassinating Lincoln in April 1865. “Base Ball Affairs,” Washington Daily National Intelligencer, July 29, 1867: 3.

11. “Atlantics vs. Red Stockings,” New York Tribune, June 15, 1870: 5.

12. “Athletic Club of Philadelphia,” New York Clipper, March 12, 1870: 389; See also, for example “A Game of Base Ball,” Philadelphia Inquirer, July 19, 1867: 2.

13. Steve Hatcher, “John McMullin,” SABR Biography Project, https://sabr.org/bioproj/person/john-mcmullin/; Athletic Club of Philadelphia;” “Base Ball,” Philadelphia Inquirer, October 19, 1869: 1.

14. “Powhatan vs. Eckford,” Brooklyn Eagle, July 13, 1869: 2.

15. Van Haltren, who had spent most of his career as an outfielder/pitcher, proved to be a poor defensive shortstop. This prompted Barnie to search nationwide for a replacement. He found one in 18-year-old John McGraw, a right-handed shortstop playing in Cedar Rapids, Iowa. Later moved to third base, McGraw starred under Barnie’s successor, Ned Hanlon, as the Orioles team dominated the NL in the mid-1890s. Larry DeFillipo, “August 26, 1891: John McGraw beats back butterflies to ignite game-winning rally in debut,” SABR Games Project, https://sabr.org/gamesproj/game/august-26-1891-john-mcgraw-beats-back-butterflies-to-ignite-game-winning-rally-in-debut/.

16. Robert D. Warrington, “Philadelphia in the 1882 League Alliance,” SABR Baseball Research Journal, Fall 2019, https://sabr.org/journal/article/philadelphia-in-the-1882-league-alliance/.

17. “Left-Handed Ball Players,” Anaconda (Montana) Standard, April 14, 1898: 12.

18. Lefties John Shoup (the first major leaguer born in West Virginia) and Oscar Walker (the first player to hit a home run at the original Polo Grounds) played two games and one game, respectively, at second base for St. Louis in the inaugural season of the American Association.

19. Eleven teams were identified that used different lefties at second base and shortstop during a regular season, but never at the same time: 1871 Troy Haymakers (NA), 1873 Philadelphia White Stockings (NA), 1882, 83, 87, and 88 Baltimore Orioles (AA), 1883 Louisville Eclipse (AA), 1888 Detroit Wolverines (NL), 1889 Chicago White Stockings (NL), 1890 Rochester Hop Bitters/Broncos (AA), and 1899 St. Louis Browns (NL).

20. The Dark Blues were playing in Boston to take advantage of larger gate receipts while the hometown Red Stockings were off touring the British Isles. “Philadelphia vs. Hartford,” New York Clipper, August 22, 1874: 165.

21. “A Close Game with the Mutuals,” Brooklyn Union, October 16, 1874: 3.

22. “Inning 1: I Was a Catcher,” Baseball: A Film by Ken Burns, The Baseball Film Project, Inc., 1994.

23. See, for example “Viau’s Fine Work,” Cincinnati Enquirer, June 12, 1889: 2 and “Ball Talk,” Columbus Evening Dispatch, July 20, 1889: 4.

24. Larry DeFillipo, “July 6, 1889: Columbus starts lefties at second base, third base and shortstop in loss to St. Louis,” SABR Games Project, https://sabr.org/gamesproj/game/july-6-1889-columbus-starts-lefties-at-second-base-third-base-and-shortstop-in-loss-to-st-louis/.

25. “A Ten Inning Game,” Louisville Courier-Journal, July 14, 1889: 4.

26. “The Leather-Lammers,” Cincinnati Enquirer, June 6, 1877: 2; “Base-Ball,” Cincinnati Enquirer, June 8, 1877: 2.

27. “Base-Ball,” Cincinnati Enquirer, June 10, 1877: 8.

28. See, for example, glowing praise for Farrell’s gloveless work by Cincinnati sportswriter O.P. Caylor in “Victory,” Cincinnati Enquirer, June 5, 1879: 12 and alluded to in “Notes,” Buffalo Commercial, June 10, 1879: 3. Farrell’s absence is mentioned in “Yesterday’s Base Ball Games, and Other Sporting News,” Buffalo Courier Express, July 10, 1879: 4.

29. “Chicago vs. Syracuse,” Chicago Tribune, July 11, 1879: 5.

30. “Chicago 6, Philadelphia 3,” Pittsburgh Post-Gazette, May 14, 1883: 2.

31. In the period between his two absences, Ferguson was replaced as captain by Blondie Purcell, making it unclear whose decision it was to again use Harbridge at second base. Brian McKenna, “Bob Ferguson,” SABR Biography Project, https://sabr.org/bioproj/person/bob-ferguson-2/; “Base Ball Notes,” Philadelphia Times, June 13, 1883: 1.

32. “The Buffaloes ‘Chicagoed’ by the Philadelphias in a Splendid Game,” Philadelphia Times, June 15, 1883: 3.

33. “The National Game,” New York Sun, May 1, 1884: 3; “The Progress of the Base Ball Season,” Brooklyn Eagle, May 4, 1884: 9.

34. Bill Carle, “Billy Geer,” SABR Biography Project, https://sabr.org/bioproj/person/billy-geer/.

35. “The Baltimore Defeat the Indianapolis Club by a Score of 3 to 1,” Baltimore Sun, June 27, 1884: 4.

36. “The National Game,” Baltimore Sun, July 16, 1884: 4.

37. “Base-Ball,” Baltimore Sun, June 17, 1885: 4.

38. One of four righties Anson used at second base, Connor had managed only two hits in 34 at-bats.

39. “Calcine for Colts,” Chicago Inter Ocean, September 27, 1892: 6.

40. “Batting Clothes On,” Chicago Inter Ocean, May 11, 1893: 4.

41. “Tebeau’s Tigers,” St. Louis Post-Dispatch, May 11, 1893: 6.

42. “Browns and White Sox Close Season in Unique Manner,” St. Louis Republic, September 29, 1902: 4.

43. “Browns Final Game,” St. Louis Globe-Democrat, September 29, 1902: 4.

44. The 6–4–3 double plays were turned on July 9 versus the Cincinnati Reds, July 20 versus the Baltimore Orioles and July 27 when two were converted in a game with the Louisville Colonels.

45. Those players were second basemen George Decker, Jake Boyd, and Willie Keeler and shortstops George Van Haltren, Jimmy Ryan, Billy Hulen, Russ Hall, and Scott Hardesty.

46. “Baseball,” Jersey City (New Jersey) News, February 19, 1902: 3.

47. “A Talk with Billy Keeler,” Brooklyn Eagle, January 9, 1898: 9.

It is not exactly known when, how, or why the 40-year-old began his employment with the Philadelphia Phillies in 1887, then in only their sixth year of existence.17 In 1900, his official occupation in the census was still carriage builder.18 It’s possible, among other scenarios, that he worked in some sort of part-time capacity with the team or was employed off the books. But his role was almost certainly somehow related to the maintenance of the grounds, as just two years later the field at then-National League Park was entrusted solely to him and his many eccentricities.

The Paynes lived in an apartment in the upper-level clubhouse of the ballpark until 1918, before moving to the lower-level clubhouse. His wife was known to cook for the unmarried ball players, and “if the game was still in progress while she was preparing the meal, outfielders could usually tell what was on the menu as the smell drifted out the window.”19

Payne always seemed to be in the middle of the action, and bits and bobs of his peculiar doings appeared at random in newspaper coverage of the Phillies, often in jest. One day in the early 1920s, he solved the problem of mower-free lawn care by letting two ewes and a ram run around the outfield, which “for the penny-pinching Phillies saved the expense of hiring workers and buying equipment to keep the grass trimmed.” They remained until 1925 and were retired only after the ram attacked longtime Phillies executive Bill Shettsline.20

Payne, whose daughter was baptized on Halloween, also had a “hobby for black cats,” much to the dismay of the superstitious home club.21,22 At the onset of a particular series against the Braves in 1929, he set one loose in front of the visiting dugout to jinx the Phillies’ losing streak against their foe.23

He was also very particular about his baseballs, which he guarded “as if they were lumps of gold,” and would even go as far as to mark them with blue pencil so he knew which were his if anyone should take one.24

Stan Baumgartner, who pitched for the club from 1914–16 and 1921–22 before embarking on a sportswriting career, recalled in the Philadelphia Inquirer that the first time he ran onto the field to warm up with a new ball, Payne stopped him in his tracks.

“Just a minute son, you aren’t well enough acquainted around here to get a brand-new ball to play with. Wait until you’re dry behind the ears,” Payne told him, mentioning he had once said the same to Alexander and other veterans. “And see that little door back there. That is the way back to the clubhouse when you get knocked out. The hinges are well-greased, so you can sneak out quietly.”25

His abrasiveness was often couched in jest, which helped endear him to those around him. But he was also fiercely righteous and not one to shy away from physical altercation if he deemed it necessary. One time in 1927, the octogenarian witnessed an ironworker at the stadium assaulting a younger, smaller employee. According to Payne’s friend Stewart Boggs, Phillies head telegraph operator, Payne “did not like that.” With his gnarled knuckles—which, according to Boggs, were as such from his amateur bare-handed catching days—Payne “challenged the warlike bird, and gave him the trimming of his life.”26

The groundskeeper also left some room for more than a bit of vanity. He was beyond confident he was the best in the world at keeping a ball field in order.

Prior to the 1916 campaign, Payne was one of several head field chiefs who erred in laying out the pitching rubber to the specifications provided by National League Secretary John Heydler in the league’s annual diagram. Heydler’s instruction showed “60.5’”—intended to mean 60-and-a-half feet, the same distance it had been for two-plus decades. Some, like Payne, interpreted it as 60 feet, five inches. Payne apparently could not be convinced he should have put the mound back an inch and then doubled down by offering to “bet everything except his war record that he was right.”27

In February 1909, just a few years into his head role, Payne scoffed at the work of his Philadelphia Athletics’ counterpart Joe Schroeder in preparing the field at the newly built Shibe Park for play. He asserted, “[Connie] Mack can never win the pennant on grounds like Schroeder’s” and that it “looked like the green-eyed monster.”28

The A’s, for what it’s worth, went on to win three of the next five World Series, and Payne’s comments landed him in some hot water. The day after his public ridicule of Schroeder, a report in the Coatesville Record indicted a man named Trouleib would succeed Payne as groundskeeper that year and that Manager Billy Murray “would not discuss the matter.”29

Payne kept his gig, but clearly didn’t learn his lesson. Two decades later, just before 1929 Opening Day, he claimed he had “out-grassed” Athletics’ landscaper Bill McCalley, and called upon “three experts from leading seed stores” to settle the matter.30 There was never a public resolution on the superior seeding, and the A’s won the World Series that year, too, while the Phillies finished 27.5 games out of first place.

Yet Payne’s arrogance and idiosyncrasies were not only tolerated, they were celebrated. Part of that, no doubt, was his demeanor. The papers would not have published jokes at his expense (like a bad bounce being called a “Sam Payne base hit”), nor would he be “known by thousands of players and fans” if he was not, at heart, a good-natured fellow.31,32

But much of Payne’s popularity stemmed from the tremendous efforts he put forth on the field for the club. Ray Benge, who pitched for the Phillies during Payne’s later years, recalled to Philadelphia’s Old Ballparks author Rich Westcott that “the infield and outfield were fine,” despite well-documented and near universal condemnation of the park’s other amenities. Payne was, as Westcott wrote, part of a “proud line of groundskeepers who worked hard to maintain the field despite the club’s limited funds.”33

Beyond managing the playing grounds at Broad and Huntingdon streets, Payne was responsible for the upkeep of the playing surfaces at Phillies’ spring training. That was no easy task. From the time he was named head groundskeeper in 1902 until he readied the field in Winter Haven at 82 in 1930, Phillies spring training was held in 14 unique locations across six states plus the District of Columbia. If he also had a hand in setting up the camps from 1887–1901, add another four sites and two more states to the list.34

Some of these locations had previous infrastructure, like Rickwood Field in Birmingham, Alabama, where the Phillies trained in 1911. Some had none at all. Several weeks before Christmas in 1913, Payne made his first trip to Wilmington, North Carolina, “in order to lay out the diamond and give instructions as to the kind of soil to be used.”35 Coincidentally, the site was “ensconced in the shadow of Fort Fisher, where Sam Payne fought and bled for the glorious cause of the Union…before the massaging of baseball parks became a popular means of earning a livelihood.”36

Touring the site with officials, he determined a location for the diamond as a team of workers cleared away “trees, stumps and grass.”37 Payne returned at a later date to level the field, and then during spring training itself had to deal with the effects of a rare ice and snow storm when camp started, which the Philadelphia Inquirer’s Nasium joked may have been “reprisal for the conduct of the Phils’ groundskeeper during the Civil War.”38

At Leesburg, Florida, in 1922, the entire ballpark was constructed at zero cost by local businessmen, lawyers, doctors, grocerymen and “other public spirited citizens from a hayfield and forest in just seven weeks,” with cypress timber and sod hauled in from 16 miles away.39 At the center of it all was Payne, who was sent down in early February to teach the locals “how to construct a ballground that didn’t have a tin can for a roof and three rough and ready rocks for the bases.”40

Not surprisingly, the rigor of the spring work caught up with the aging Payne. In 1928, he suffered a heart attack in Winter Haven, Florida, that nearly killed him, though he was said to be “up and around again and completed his job” after resting a few days.41

A few years later, in the lead up to the 1932 season, it became too much, at least in the eye of Phillies’ management. Payne, who had long been the “dean of all groundskeepers” was “relieved of his duties” and retired.42 It was something Baumgartner said Payne did not vocally oppose, but that “one could see it in his actions” he was not happy.43

The Phillies had a history of taking care of Payne financially beyond his salary—the players gave him and trainer Mike Dee a pool of World Series share money in 1915—and that did not change in retirement.44 The club set him up with a pension that required absolutely nothing of him to collect.45 Yet Payne remained on hand at every game, usually in a box above the Phillies’ dugout, “puffing at one of his famous black cigars and offering advice to his successors.”46,47

In his older age, Payne moved into his son George’s Riverside, New Jersey, home.48 George had been one of Payne’s only close remaining family members for several decades, as two of Payne’s siblings who survived childhood, Emma and William, along with his daughter, Mary, all had died between 1903 and 1913, and his wife, Elizabeth, in 1917.49,50,51,52

On July 24, 1933, Payne himself could not outlast complications of a stroke he suffered some time before.53 At the time of his passing, he was one of the last living links in Phillies history between 1887, when he joined the club, and the 1930s, and perhaps the only constant with the team through all those years.

He began his career when the fledgling club, managed by pioneer Harry Wright, had just moved from its original home at Recreation Park into the grounds that would eventually come to be known as Baker Bowl. He witnessed firsthand the prowess of the Phillies clubs of the 1890s, stocked full of future Hall of Famers. He was, literally, along for the ride during the club’s first-ever pennant win, experiencing the elation of a Game 1 World Series victory on the field he prepared himself, and later the sorrow as the Phillies nine fell to the Red Sox. He slogged through the team’s doldrums of the 1920s as the game and world changed immensely around him, yet still brought a sense of juvenile enjoyment to the ballpark, as richly documented by local journalists of the era.

Just prior to his interment at Mount Moriah Cemetery in Yeadon, Pennsylvania, several obituaries were published for Payne by those writers, the most lengthy and personal by his old friend Baumgartner.54 He concluded his thoughts with the following, in the Philadelphia Inquirer:

“Good old Sam! When it is time for us to do our pitching in the new league, we hope Sam Payne is guarding the balls in the dugout.”55 

KENNY AYRES is a public relations professional who spent nearly a decade working in the Philadelphia Phillies’ baseball communications department. He contributed to various historical projects for the team, including the “Pioneers in Pinstripes” initiative to honor the lesser-known trailblazers of Phillies integration. Kenny has also contributed to the SABR BioProject and pens a blog called “Hidden in Haverford” for his local historical society. He lives in Havertown, Pennsylvania, with his wife, soon-to-be-three sons, goldendoodle and fish.

Notes

1. “Phillies, Beaning Braves, Capture National’s Flag,” Philadelphia Inquirer, September 30, 1915, 10.

2. “Phillies Here for Just a Few Minutes,” Philadelphia Inquirer, September 28, 1915, 12.

3. “Phillies, Beaning Braves, Capture National’s Flag.”

4. Stan Baumgartner, “Sam Payne, Groundkeeper for Phils for 30 Years, Dies,” Philadelphia Inquirer, July 26, 1933, 13–14.

5. “Phillies Here for Just a Few Minutes.”

6. “Ol’ Sam Payne of Phillies Dies,” Morning Call (Pennsylvania), July 26, 1933, 13.

7. “1850 United States Federal Census,” Philadelphia North Mulberry Ward, United States Census Bureau, https://www.ancestry.com/imageviewer/collections/8054/images/4205378_00465?pId=5044385.

8. “William Rowland Payne,” Pennsylvania, US., Death Certificates, 1906–72, https://www.ancestry.com/search/collections/5164/records/601688515.

9. “William Rowland Payne,” Philadelphia, Pennsylvania, US, Death Certificates Index, 1803–1915, https://www.ancestry.com/search/collections/2535/records/1224064?ssrc=pt&tid=73029330&pid=30265450945.

10. “1860 United States Federal Census,” Philadelphia Ward 10 East District, United States Census Bureau, https://www.ancestry.com/search/collections/7667/records/4514076.

11. “U.S., Naval Enlistment Rendezvous, 1855–1891,” https://www.ancestry.com/search/collections/60368/records/209927?tid=73029330&pid=30265450944&ssrc=pt.

12. Baumgartner, 14.

13. Jim Nasium, “Sam Payne’s Historic Doings of War Days Bested by Weather Men in His Attack on Fort Fisher,” Philadelphia Inquirer, February 28, 1914, 12.

14. “Samuel Payne,” Pennsylvania, US, Veterans Burial Cards, 1777–2012, https://www.ancestry.com/search/collections/1967/records/1027263.

15. “Marriages, Grace Episcopal Church,” Pennsylvania and New Jersey, US , Church and Town Records, 1669–2013, https://www.ancestry.com/search/collections/2451/records/2090008.

16. “1880 United States Federal Census,” Philadelphia 202, United States Census Bureau, https://www.ancestry.com/search/collections/6742/records/232470.

17. Baumgartner, 13.

18. “1900 United States Federal Census,” Philadelphia Ward 13, District 0222, United States Census Bureau, https://www.ancestry.com/search/collections/7602/records/47629118.

19. Rich Westcott, Philadelphia’s Old Ballparks (Philadelphia: Temple University Press, 1996), 42–43.

20. Westcott, 46.

21. Baptisms, Pennsylvania and New Jersey, US, Church and Town Records, 1669–2013, https://www.ancestry.com/search/collections/2451/records/2090239?tid=&pid=&queryId=023662b3-c6e1-4029-a49c-a24e618c30e4&_phsrc=dhj321&_phstart=successSource.

22. Baumgartner, 14.

23. Philly Busters,” Philadelphia Inquirer, May 30, 1929, 10.

24. Baumgartner, 14.

25. Baumgartner, 13–14.

26. “Jerry Donovan Still an Active Fan,” Morning Call, June 29, 1927, 18.

27. “Nearly Every Groundkeeper in the Country Has Erred in Laying Out His Diamond,” Pittsburgh Press, January 29, 1916, 20.

28. “Sport Gossip,” The Reveille (Montana), February 26, 1909, 3.

29. “Phillies Gather for Southern Training Trip,” Coatesville Record, February 27, 1909, 4.

30. James C. Isaminger, “Under the Spotlight,” Philadelphia Inquirer, April 14, 1929, 52.

31. “Philly Bingles,” Philadelphia Inquirer, July 1, 1931, 14.

32. “Sam Payne Dies at Riverside Home,” Evening Courier (New Jersey), July 26, 1933, 19.

33. Westcott, 46.

34. Philadelphia Phillies, 2025 Philadelphia Phillies Media Guide (Philadelphia, PA: Philadelphia Phillies, 2025), 459.

35. “Early Start for Phillies’ Groundkeeper Sam Payne,” Lansing State Journal, December 15, 1913, 5.

36. Nasium.

37. “Preparing for Phillies,” Wilmington Morning Star, December 4, 1913, 5.

38. Nasium.

39. Tampa Tribune, March 12, 1922, 23.

40. Gordon Mackay, “Leesburg Mayor Tips Phils Off to a Star,” Philadelphia Inquirer, February 2, 1922, 17.

41. “Sam Payne Dies at Riverside Home” 19.

42. “Ol’ Sam Payne of Phillies Dies”

43. Baumgartner, 13.

44. “Losers in World’s Series Get Their Share of Cash,” The Journal Times (Wisconsin), October 14, 1915, 6.

45. Baumgartner, 13.

46. “Sam Payne Dies at Riverside Home” 19.

47. Baumgartner, 13.

48. Baumgartner, 13.

49. “Emma Elizabeth Washbourn,” Philadelphia, Pennsylvania, US, Death Certificates Index, 1803–1915, https://www.ancestry.com/search/collections/2535/records/1148283?ssrc=pt&tid=73029330&pid=30265450943.

50. “William Rowland Payne,” Pennsylvania, US, Death Certificates, 1906–72.

51. “Mary Elizabeth Payne,” Philadelphia, Pennsylvania, Death Certificates Index, 1803–1915, https://www.ancestry.com/family-tree/person/tree/83272366/person/42479785792/facts.

52. “Died,” Philadelphia Inquirer, February 27, 1917, 7.

53. “Sam Payne Dies at Riverside Home” 19.

54. “Samuel Payne,” Pennsylvania, US, Veterans Burial Cards, 1777–2012, https://www.ancestry.com/search/collections/1967/records/1027263.

55. Baumgartner, 14.

BACKGROUND

Referees, umpires, and other duly appointed officials play an important adjudicatory role in nearly every major sporting contest. Consequently, the in-game performance of referees is of great interest to sports leagues and fans, and even to researchers. Several of the latter have conducted interesting investigations of referee performance and the various factors that may affect it. These studies span a range of sports and research questions. Some investigate the effects of the home team’s crowd on the referee’s contributions to the so-called home advantage, while others study the influence of game situations, or the impact of referees’ age and experience, on referees’ overall performance. In regard to the latter, one study considered the effects of referee experience on referee performance in association football (English soccer) and found that experience, at least up to a certain level, is positively associated with the number of fouls called against players on the home team, suggesting that more experienced referees tend to be less influenced by the game’s spectators.1 Another investigation of over 8000 decisions made by a group of 32 Australian Football League umpires found that while match characteristics (e.g., match location and match attendance) had little effect on umpire error rates, more experienced umpires had lower error rates than those with less experience.2 Additional studies have reported generally positive effects of age and experience on referee performance in volleyball, basketball, and handball.3,4,5

Baseball is perhaps the most thoroughly studied sport of all, and one of its referees, the home-plate umpire, must make and announce hundreds of decisions known as pitch calls (either balls or strikes) during each game. Hence it is not surprising that the performance of home-plate umpires and the factors that may affect it have been intensely scrutinized. An important metric of umpire performance is “accuracy,” which is the percentage of pitch calls that are correct, in reference to the rule-book strike zone (RBSZ). One factor that has been shown to be extremely influential on umpire accuracy is the “count,” i.e., the cumulative number of called balls and the cumulative number of strikes (called or swinging) over all pitches received by the batter in the current plate appearance, immediately prior to the current pitch.6,7,8 Another is the handedness of the batter, as it seems that until recently there was a substantial shift of the called strike zone to the left of the RBSZ, and thus also a decline in umpire accuracy, for a left-handed batter relative to a right-handed batter., Some evidence has been found for racial discrimination in umpires’ pitch calls, with strikes more likely to be called when the umpire and pitcher match races, although additional investigation, using more extensive data, was unable to replicate this finding.11,12 It has also been shown that umpires tend to grant a larger strike zone to high-status pitchers (All-Stars) than to other pitchers.13 A home advantage in umpire pitch calls was documented, with home-team batters receiving more called balls on actual balls and fewer called strikes on actual strikes.14 Increasing air temperature (especially temperatures exceeding 95°F) and increasing levels of air pollution (especially carbon monoxide) were found to have significant negative effects on umpire accuracy, suggesting that there may be other, rather more obscure factors affecting umpire performance that remain to be discovered.15 Other work has documented continual improvement in umpire accuracy from 2008–23, a period during which technology to monitor ball-strike calls, together with an evaluation and feedback system for Major League umpires, was implemented.16,17,18

Surprisingly, relatively few published studies exist of the effects of age or experience on umpire performance in baseball, especially since home plate officiating is different from officiating in many sports in that it requires very little movement on the part of the officials. This results in baseball umpires being capable of performing the duties of their position for longer, and to a more advanced age. We are aware of two relevant studies. The first, using data from 2009–14, found that less experienced umpires improved more over time than those with more experience.19 The second, using data from the slightly broader period 2008–15, showed that younger umpires tended to improve more over this period than older umpires.20 But these studies focused on the effects of age or experience on umpire improvement over time rather than on time-adjusted comparisons of umpire performance. It would be entirely possible, for example, for less experienced umpires to perform worse than those with more experience, even if the former improve faster. Furthermore, those previous studies considered how umpire performance is associated with either age or experience marginally (individually), not jointly (simultaneously). The age and experience of MLB umpires are highly positively correlated: it is shown herein, for example, that among the 129 MLB umpires who called at least one game between 2015 and 2023, this correlation was 0.96. Consequently, an effect on performance that is attributed to age could actually be attributable to experience or vice versa, or even to some combination of the two. Moreover, it is possible that the association of performance with age, adjusted for experience, is quite different than the association of performance with age marginally. Likewise, it is possible that the association of performance with experience, adjusted for age, is different than the association of performance with experience marginally. The main objective of this article is to investigate whether, and how, MLB umpire performance is associated with umpire age and experience, both marginally and jointly.

We measure umpire performance using two specific measures provided in a database known as “UmpScorecards,” the source of which is described in the next section. The two performance measures are: 1) accuracy of called pitches, relative to the RBSZ, and 2) consistency of called balls and strikes, regardless of whether the pitches were actually called in accordance with the RBSZ. Using mixed-effects weighted beta regression methods, we determine how, and to what extent, these performance measures, adjusted for year, are associated with age, experience, and a third, related variable: the age at which the umpire was hired.

Before analyzing the data, it is difficult to predict the nature of any association between umpire performance and age or experience. On one hand, evidence from other sports shows a positive relationship between these variables, which might suggest a similar pattern in baseball. On the other hand, when an automated feedback system was introduced in 2006, some umpires—many of whom are still active—were initially resistant to incorporating its feedback and may still be so to some extent. In addition, it is reasonable to expect that advanced age could eventually affect visual acuity and stamina. These considerations point toward the possibility of a negative association. Given these competing possibilities, we do not make any prior assumptions about the direction of the relationship between umpire performance and age or experience. Instead, we test a null hypothesis of no association against a two-sided alternative, allowing the data to determine whether any observed relationship is positive or negative.

DATA

The use of pitch tracking technology has revolutionized analytics in baseball. Beginning in a single Major League Baseball (MLB) stadium in 2006, and then expanding to a league-wide rollout prior to the 2008 season, the PITCHf/x camera system, developed by Sportsvision, used a pair of cameras to track pitch-related data including trajectory, speed, break, and location. These values were provided to broadcasters and MLB in real time before being released to the public.21,22 In 2015, the StatCast system added optical cameras in an attempt to capture all in-game actions not already collected by PITCHf/x (i.e., player position, ground ball location and speed, etc.).23 PITCHf/x was deprecated following the 2016 season in favor of “TrackMan,” which is based on phased-array Doppler radar collected via a sensor mounted above home plate.24 The use of Doppler radar allows for better estimation of the variables associated with the flight of the baseball including back spin, side spin, and speed.25 The data collected by the StatCast system, including data while a ball is in flight measured via TrackMan, are released to the public following each game.

In this study, we use StatCast data from 2015–23 (i.e., PITCHf/x for the 2015 and 2016 seasons, TrackMan for the period 2017–19, and Hawk-Eye from 2020–23) compiled by Umpire Scorecards (umpscorecards.com) (UmpScorecards hereafter). UmpScorecards uses the daily release of data from the StatCast system to quantify the accuracy and consistency of each individual home plate umpire from the previous day’s MLB games. These values are defined by UmpScorecards as follows.

Accuracy represents the proportion of taken pitches called correctly over a game. UmpScorecards uses the pitch location provided by StatCast, the estimated RBSZ based on the unique attributes of a given batter, and an algorithm to determine the likelihood that a given pitch was a strike based on Monte Carlo simulation of a pitch’s potential true location (i.e., accounting for error in the location estimate provided by TrackMan). Using 500 potential true location values, a pitch is determined to be incorrectly called if 1) the probability that the pitch was in fact a strike is over 90% and the umpire called it a ball or 2) the probability that the pitch was in fact a ball is over 90% and the umpire called it a strike.

Consistency represents the proportion of taken pitches considered consistent with the umpire’s established zone (EUZ) in any given game.26 The boundary of the EUZ is defined by the area where a given pitch has a greater than 50% chance of being called a strike by that umpire. Therefore, a pitch is consistent if 1) the pitch fell within the EUZ and was called a strike or 2) it fell outside of the EUZ and was called a ball. Consistency is a relevant additional measure of performance because it seems to be the case that baseball players, managers, and fans will tolerate some level of inaccuracy from an umpire as long as his calls are consistent throughout the course of a game.27

Accuracy and consistency are proportions, hence bounded within [0,1]. The statistical methods we use herein to analyze the effects of age and experience on these metrics will properly account for their bounded support.

UmpScorecards provides accuracy and consistency on a game-by-game basis for each home plate umpire. We used the data from years 2015–23, for which there were 18,682 games played. For our analyses, we supplemented these data by some umpire-specific information, namely age and years of experience at the MLB level of the umpire as of the opening day of the given season. This additional information is not provided by StatCast or UmpScorecards but was obtained from Retrosheet. From the age (in years) and experience (in years) of each umpire, we obtained his age-at-hiring by forming the difference, age minus experience. The ages, years of experience, and ages at hiring of the umpires in our study ranged from 27 to 69, 0 to 45, and 24 to 41, respectively. UmpScorecards provides a third umpire performance metric called favor, which represents the effect of an umpire on the absolute difference in run expectancies of incorrect versus correct calls for the two teams. A more thorough explanation of this metric can be found at umpscorecards.com or elsewhere.28 We considered this metric in our study initially, but found that its association with umpire age and experience was much weaker than those of the other two metrics with age and experience, so we opted not to include it herein.

EXPLORATORY DATA ANALYSES

Prior to performing formal inferential methods to address our research objective, we do a bit of exploratory data analysis here to gain some familiarity with the data and glean its major features. The features discovered will inform our subsequent formal statistical analysis.

Figure 1 displays plots of annual averages of accuracy and consistency versus year over the 9-year study period, 2015–23. Averages were taken over all games in a given year. Vertical bars extending from the 5th to the 95th percentiles of a metric in each year are also shown to convey dispersion.

The plots reveal that umpires improved from 2015–23 in both accuracy and consistency, which comports with previously published reports of improvements in accuracy over earlier time periods 2009–14 and 2008–15.29,30 They also show that the improvements from 2016 to 2017, the year the switch was made from PITCHf/x to Trackman, were of similar magnitude to improvements in some other years.

Because we wish to explore the relationship between each performance metric and age and experience, free of the confounding effect of year, we subtract the annual averages shown in Figure 1 from the performance metrics for all subsequent exploratory data analyses. The resulting metrics are referred to as year-adjusted metrics. The interpercentile ranges between the 5th and 95th percentiles of the metrics vary somewhat over years, tending to decline over time but only slightly; they are about 20% smaller in 2023 than they were in 2015. The interpercentile ranges also reveal a slight amount of left skewness, which is to be expected considering the upper bound of 1.0 (100% in the figure).

Accuracy and consistency, though distinct as measures of performance, could be associated with one another. The scatterplot of the two year-adjusted metrics, shown in Figure 2, investigates this issue. The unit of observation in the scatterplot is a game. The plot shows that accuracy and consistency are significantly positively associated. The strength of the linear association, as measured by Pearson’s correlation coefficient, is 0.52, which is highly statistically significant.

Figure 2. Scatter plot showing the relationship between year-adjusted umpire accuracy and consistency. The unit of observation is a game.

Since accuracy and consistency are observed repeatedly over a lengthy period, it is possible that one or both is correlated over time within umpires. To examine this possibility, we computed the pairwise correlations, for each pair of years, of year-adjusted metrics averaged over all games called by an umpire in a year. These correlations are listed in Table 1.

Table 1. Sample pairwise correlations between years for (a) accuracy, and (b) consistency.

They indicate that there is substantial positive temporal correlation in umpire accuracy, and somewhat less (though still appreciable) positive temporal correlation in consistency. Furthermore, the temporal correlation does not appear to attenuate with elapsed time as it would under an autoregressive model but instead fluctuates around a constant. The average pairwise correlation among accuracy measurements is 0.49, while that among consistency measurements is 0.22.

Turning our attention from the performance metrics to age and experience, recall that these variables are highly positively correlated (Pearson’s r=0.96). Figure 3 is a matrix scatterplot of age, experience, and age-at-hiring. The unit of observation in this scatterplot is an umpire-year combination, of which there are 833 in the dataset. The middle plot in the first column shows the strong linear relationship between age and experience. This relationship is due partly to a shared one-year increment of these variables with each passing year and partly to the fact that most umpires are hired in their late twenties or early thirties, so that there is relatively little dispersion in experience among umpires of any given age.

Such a strong correlation between variables that we wish to use as regressors is unfortunate and leads us to consider not only age and experience, but also the derived variable age-at-hiring, as regressors. Figure 3 shows that the correlations between age-at-hiring and age, and age-at-hiring and experience, are still statistically significant, but much smaller in magnitude than the correlation between age and experience. The signs of the correlations between age-at-hiring and the other two variables are of no surprise, matching as they do the signs of the coefficients on age and experience in the definition of age-at-hiring. Note that at most two of these three variables may be used as regressors in any regression analysis, due to their perfect collinearity.

Figures 4 and 5 (below), consist of bivariate scatterplots of both year-adjusted performance metrics versus umpire age, umpire experience, or umpire age-at-hiring. Each point plotted in Figure 4 represents a metric for an individual game, while a point plotted in Figure 5 represents an average metric over all games called by an umpire in a given year. Note that the scale along the vertical axis differs in the two figures. These two figures suggest that the marginal associations between year-adjusted accuracy and both age and experience are negative, and the same is true of the marginal associations between year-adjusted consistency and both age and experience. In contrast, the marginal associations between both metrics and age-at-hiring appear to be positive, though not strongly so. Each scatterplot reveals considerable game-to-game variability (noise) in the performance metrics, which is reduced substantially when the metric is averaged over all games called by an umpire in a given year (Figure 5). Because of this, and because our regressors (age, experience, and age-at-hiring) do not change within a given year, we take an umpire-year combination, rather than a game, as the basic unit of observation for our more formal analysis described in the next section. As noted previously, there are 833 such units in the dataset.

Figure 4. Bivariate scatterplots depicting the relationships of year-adjusted accuracy and consistency with umpire age, experience, and age-at-hiring. Each point plotted corresponds to a single game. Ordinary least squares lines are superimposed to indicate overall trend.

 

Figure 5. Bivariate scatterplots depicting the relationships of year-adjusted accuracy and consistency with umpire age, experience, and age-at-hiring. Each point plotted represents the average value of a metric over all games called by an individual umpire in a year. The fitted linear mean model and fitted quadratic mean model from beta regressions are superimposed in two different lines.

 

STATISTICAL ANALYSIS

To more quantitatively address the relationships of umpire performance with age, experience, and age-at-hiring, we carried out various regression analyses, as follows. The dependent variable for these regressions was accuracy or consistency, computed by averaging over all games called by an umpire during a given year. These (averaged) metrics have bounded continuous support in (0,1). To account properly for this support, we used beta regression methods.31 Because the numbers of games each umpire called in any given year varied considerably, the performance metrics varied in reliability across umpire-years and we therefore weighted each umpire’s performance metric for a given year by the number of games he called in that year. The regressors in these weighted beta regressions included indicator variables for year (to account for the previously documented improvement over years noted previously in our exploratory data analysis), plus one or two of the variables age, experience, and age-at-hiring. Furthermore, to account for the substantial but non-attenuating temporal correlation within umpires discovered in our exploratory data analysis, we included random umpire effects, which are assumed to be independently and identically normally distributed with mean zero and variance σ²_u.

Thus, the model fitted to the observed values {y_ij}, where y_ij is either the accuracy or consistency of umpire i in year j, is specified, in part, by the beta probability density function

where Γ(·) denotes the gamma function; ϕ is a precision (inverse dispersion) parameter; w_ij is the number of games called by umpire i in year j; μ_ij=E(y_ij) and Var(y_ij)=μ_ij(1−μ_ij)/(1+ϕw_ij). The remaining part of the model specification stipulates that μ_ij is linked to the regressors and random umpire effects via a logit link function:

where xT_ij=(x_ij1,…, x_ijk) is a vector of k regressors; β=(β₁,…, β_k)^T is a k-vector of fixed unknown regression coefficients (which in our case consists of year effects and one or two of the slope coefficients on age, experience, and age-at-hiring); and u_i is the random effect of the umpire. This model is a mixed effects variant of a weighted beta regression model.32

Table 2. Results of mixed-effects weighted beta regressions of umpire accuracy on indicator variables for years and one or two of the regressors age, experience (Exp), and age-at-hiring (AAH). The quantities listed are the maximum likelihood estimates of regression parameters and p-values of the tests of the null hypothesis that the parameters are equal to zero. An asterisk indicates that the p-value corresponding to a regression coefficient is less than or equal to 0.001.

Table 3. Results of mixed-effects weighted beta regressions of umpire consistency on indicator variables for years and one or two of the regressors age, experience (Exp), and age-at-hiring (AAH). The quantities listed are the maximum likelihood estimates of regression parameters and p-values of the tests of the null hypothesis that the parameters are equal to zero. An asterisk indicates that the p-value corresponding to a regression coefficient is less than or equal to 0.001.

The rows below the first show the conditional probabilities of scoring runs when starting with runners already on base. For example, the second row represents probabilities when starting with a runner on first base (“100”), while the third row represents starting with a runner on second base (“010”), which reflects the current MLB extra-inning rule.

These probabilities highlight the significant impact of starting base runner states on expected run outcomes. For instance, with no runners on base (“000”), the probability of scoring no runs is 72.2%.With a runner on second (“010”), this drops to 40.1%, reflecting a much higher likelihood of scoring.

Using probabilities from Table 1, Table 2 calculates the likelihood of both teams scoring the same number of runs based on starting base runner states.

The key findings from Table 2 is that starting with no runners on base (“000”) yields the highest probability (54.9%) of the game continuing into the next inning. Adding runners significantly reduces this probability. For example, starting with a runner on first (“100”) lowers the probability to 38.8%, while starting with bases loaded (“111”) drops it to just 17.1%.

This pattern underscores how beginning extra innings with runners on base accelerates game resolution. Notably, starting with a runner on third (“001”) results in a less steep drop compared to other scenarios, due to the fact that it is easier to score the runner from third and a likely outcome is both teams scoring 1 run.

Table 3 shows the percentage of games that would end in each inning under various starting base runner scenarios. Under traditional rules (“000”), only 45.1% of games conclude in the 10th inning, with nearly 10% lasting beyond the 13th inning. This allows for rare but memorable marathon games, with about 1% extending to 17 innings or more.

Starting with a runner on second (“010”) under current MLB rules results in 69.8% of games ending in the 10th inning and less than a 3% chance of games extending beyond 13 innings. Starting with bases loaded (“111”) ends 82.9% of games in the 10th inning, making it the fastest game-resolution scenario.

Another thing to consider besides how many extra innings a game will go is how many extra runs will be scored in total during the extra innings. If there are a lot of extra runs scored from “Ghost Runners” does it still feel like a game of baseball?

Table 4 calculates the expected total runs scored during extra innings, conditional on the starting base runner state. Under traditional rules (“000”), the expected runs scored is 1.14 per inning.4 Starting with a runner on second (“010”) increases expected runs to 1.59, representing an additional 0.35 runs per inning compared to traditional rules. Starting with bases loaded (“111”) leads to the highest expected runs, at 2.72 per inning which is a significant increase of 1.58 runs compared to traditional rules.

This increase in scoring reflects the strategic emphasis on resolving games more quickly but could alter the dynamics of managerial decision-making and fan experience.

 

Table 5. College Baseball Expected Probability of Scoring Runs for the Rest of the Half-Inning

RESULTS—COLLEGE DATA

Table 5 presents the probabilities of scoring 0 to 8 runs in an inning under different starting base runner scenarios for college baseball. Similar to the MLB data in Table 1, the first row represents the baseline probabilities when starting with no runners on base (“000”). However, college baseball teams are less likely to score 0 runs in an inning compared to MLB teams, with a 63.4% chance versus 72.2%. This reflects a higher scoring environment in college baseball, likely due to differences in talent levels, ballpark dimensions, and pitching depth.

For instance, starting with no runners on base (“000”) leads to an average of 0.79 runs scored per half-inning in college baseball, which is slightly higher than the MLB average of 0.521 runs. Adding a runner on second base (“010”), as used in the MLB extra-inning rule, increases the probability of scoring to 32.2% for one run and to 16.8% for two runs, further amplifying the scoring environment in college baseball.

Table 6 provides the probability of both teams scoring the same number of runs under various starting base runner conditions. In college baseball, the probability of both teams scoring 0 runs when starting with no runners on base (“000”) is 44.1%, 15% lower than the MLB equivalent of 54.9%. This suggests that college extra-inning games are inherently more likely to resolve without requiring adjustments to starting base runner conditions.

For example, starting with a runner on second base (“010”) lowers the probability of both teams scoring the same number of runs to 23.0%, compared to 28.8% in MLB. This reflects a faster resolution of games in college baseball due to a greater likelihood of scoring by at least one team in each inning.

Table 7 illustrates the percentage of games that would end in each inning under different starting base runner scenarios. Under traditional rules with no runners on base (“000”), 55.9% of college baseball games would end in the 10th inning, compared to 45.1% in MLB. Similarly, the percentage of games lasting beyond 13 innings is lower in college baseball (approximately 3%) than in MLB (nearly 10%).

 

Table 7. College Baseball Percent of Time Game Would Be Over in Each Inning if Extra Inning Base Runners Start on Bases

Table 8 calculates the expected total runs scored during extra innings based on starting base runner scenarios. Under traditional rules (“000”), college teams score an average of 0.79 runs per inning, compared to 1.14 in MLB. Starting with a runner on second base (“010”) increases expected runs to 1.58, aligning closely with the MLB’s expected value of 1.59.

The most dramatic increases occur when starting with bases loaded (“111”), where expected runs reach 3.03 in college baseball versus 2.72 in MLB. This emphasizes the higher scoring environment of college baseball and highlights the potential impact of these rule modifications on game outcomes and strategy.

SUMMARY

For both MLB and college baseball, starting extra innings with bases loaded resolves games the fastest, reducing extra innings beyond the 10th by 97% in MLB and 95% in college baseball. However, this comes at the cost of significantly increased scoring, adding an additional 2.72 to 3.03 runs per game compared to traditional rules.

Starting with a runner on second base, as currently used in MLB, offers a balanced compromise. It reduces extra innings beyond the 10th by 74.2% in MLB and 80.1% in college baseball, with a smaller increase in scoring at 1.58 additional runs per game. These findings indicate that runner-on-base scenarios effectively accelerate game resolution but come with varying impacts depending on the starting base runner condition and the level of play.

CONCLUSION

If college baseball conferences are considering adopting extra-inning rules with runners on base, this study provides a clear understanding of the potential outcomes. Starting extra innings with a runner on second base offers a balanced approach, reducing extra innings beyond the 10th by 86% while increasing runs by 1.58 per game. This option preserves the potential for occasional extended games (e.g., 0.3% lasting 14 innings or more) while maintaining a relatively traditional scoring dynamic.

Alternatively, starting extra innings with bases loaded minimizes game duration, reducing extra innings beyond the 10th by 95% in college baseball. However, this approach significantly increases scoring, adding 3.03 runs per game on average. Decision-makers must weigh the benefits of faster game resolution against the potential impacts on game strategy, player workload, and the fan experience.

Further research could explore how these rule changes affect player performance, fan engagement, and the broader perception of baseball as a strategic and endurance-driven sport. 

DAVID C. HYLAND, PHD, is a professor of finance and sabermetrics at Xavier University, where he also serves as Director of Baseball Analytics for the Musketeers’ baseball program. A SABR member since 2018, he sits on the board for the Frontier League’s Florence Y’alls and is a lifelong fan of the Cincinnati Reds.

Sources

Retrosheet MLB Play by Play Data: https://www.retrosheet.org/.

Macht, Norman L. “Beyond the 9th: The Drama of Baseball’s Marathon Matches.” Peanuts & Crackerjack, January 13, 2024. https://peanutsandcrackerjack.com/blog/baseballs-longest-games, accessed November 27, 2024.

Tourtellotte, Shane. “Beyond the Ninth Inning.” The Hardball Times, May 8, 2014. https://tht.fangraphs.com/beyond-the-ninth-inning/.

Hyland, David C. “Rounding Second: A Probabilistic Investigation of the Major League Baseball Modified Extra Innings Rule.” SABR Baseball Research Journal, Volume 51, Number 2 (Fall 2022), 61–65.

Palmer, Pete and John Thorn. The Hidden Game of Baseball: A Revolutionary Approach to Baseball and Its Statistics (New York: Doubleday, 1984)

Tango, Tom, Michael Lichtman, and Andrew Dolphin. The Book: Playing the Percentages in Baseball (Lincoln, NE: Potomac Books, 2007).

Notes

1. For a discussion of particularly exciting extra innings games see: https://peanutsandcrackerjack.com/blog/baseballs-longest-games.

2. For a discussion of the extra inning environment across years see: https://tht.fangraphs.com/beyond-the-ninth-inning/.

3. The information used here was obtained free of charge from Retrosheet. Interested parties may contact Retrosheet at www.retrosheet.org.

4. This is a combination of both team’s scored runs.

Likewise, ascertaining the standard deviation (SD) for Ruth’s W% values clearly shows that his 1929 12.27 W% is a serious outlier: For 1926–32, the average W% is 19.46 with an SD of 3.33. Excluding the 1929 W%, the average W% is 20.53 with an SD of 1.20.8

Similarly, the Z-score for the 1929 W% value is –2.31, a score which fully supports excluding 1929’s W% in the statistical analysis of Ruth’s walks during the 1926–1932 seasons.9

Note also that Ruth’s strikeout rate in 1929 (11.85%) was lower than his strikeout rate in 1928 (16.23%), as well as those in 1927 (16.67%) and 1926 (15.35%). We’ll come back to that later.

So, while the 1929 W% is a serious outlier and can be excluded with 99% confidence in evaluating Ruth’s bases on balls performance in the 1926–32 period, it is real—Ruth actually achieved that abnormally low 12.27 W%. The salient question then becomes: Why did Ruth walk so infrequently in 1929?

To address this question, the first order of business is to assess the overall walk rates for the AL during the 1926–32 period—i.e., was there anything unusual or systemically different about bases on balls during the 1929 season? Table 2 presents the relevant stats for the three true outcomes for the American League for the 1926–32 seasons.

Table 2. American League Statistics for the Three True Outcomes (1926-32)

As can be seen, there does not appear to be anything unusual or out of sorts for any of the three true outcomes—there are no serious outliers. The 1929 values for the three true outcomes are pretty-much smack-dab in the middle of the values for the other six seasons. So, league-wise, there was nothing peculiar about the 1929 season with respect to the strikeouts, homers, and walks for the AL players overall. What about particular players—such as those players who have a knack for drawing bases on balls? Did any of them—in addition to Ruth—encounter an anomalous decline in walks in 1929? In the next section we examine the pertinent stats for the AL players who accumulated the most walks during the 1926–32 seasons.

Other Players with a Knack for Drawing Bases on Balls

During the 1926–32 seasons, the top-ten players in the American League who accumulated the most walks were: Babe Ruth (884), Max Bishop (802), Lou Gehrig (760), Lu Blue (670), Willie Kamm (495), Earle Combs (479), Goose Goslin (469), Mickey Cochrane (465), Tony Lazzeri (463), and Jimmie Foxx (461). Appendix A (available online) provides a list of the Top-Ten AL players in walks for each season during the 1926–32 time period. Appendix B provides tables corresponding to Table 1 for each of the above-mentioned players.

Table 3 provides a comparison of Ruth’s W% performance with the W%s for the other top-ten walkers. The items included are the W% range, the median W% (and the year), the composite W%, the mean W% (and the SD), the outlier W% (and the year), and the Q-Test quotient for evaluating the outlier W%.

Table 3. Comparison of W% Achieved by the Top–Ten AL Players in Walks (1926–32)

Babe Ruth’s 1929 W% of 12.27 with a Q-Test quotient of 0.717 can be excluded with 99% confidence in conducting a statistical analysis of his walk performance during the 1926–32 seasons, the datum rejection quotient being Q>0.680. None of the outlier W% values for the other players can be excluded—even with only 90% confidence, the datum rejection quotient being Q>0.507. Thus, among the AL’s top players in drawing bases on balls during the 1926–1932 time frame, only The Bambino experienced a grossly anomalous season with respect to receiving free passes. What made Ruth unique in this regard?

What was different for Ruth in 1929? What about the pitchers against whom the Sultan of Swat squared off? In the next section we examine Ruth’s walk performance against the pitchers he faced.

The Pitchers Who Faced Babe Ruth

We have already demonstrated that Ruth’s reduced number of walks in 1929 was not the consequence of a league-wide effect. Perhaps his decrease in walks was due to a select group of pitchers who collectively prevented Ruth from walking at his usual rate. The key question for this section is: were there significant differences in Ruth’s W% for 1929 compared with his W% in other seasons for the pitchers he faced? To address this question, it is important to point out that Ruth’s composite W% for the 1926–28 seasons was 20.62, and for 1930–32 his composite W% was 20.44. Based on Ruth’s composite W% for both the 1926–28 and 1930–32 periods (20.53), it is reasonable to expect that Ruth would have amassed about 120 walks in 1929, i.e., 48 more walks than the 72 walks he actually accumulated in the 587 plate appearances he had in the 135 games he played. By analyzing individual pitcher performances against Ruth we can determine which pitchers were particularly responsible for Ruth’s reduced bases on balls.

Appendix C provides relevant information for each of the 62 pitchers against whom Babe Ruth had at least one PA in 1929. According to the W% values that Ruth accomplished against these hurlers, it would have been expected that he would have ended up with around 118 walks, a figure which is reasonably close to the 120 walks estimated for Ruth assuming typical performance in the 135 games he played in 1929. In actuality, he collected 72 walks.

While Ruth had comparatively high numbers of “missed” walks from a few pitchers, it seems that most of his “missing” walks were generally spread out. The term “missed” walks indicates the difference between the number of walks Ruth would have received under usual circumstances and the number of walks he actually received. The pitchers who subjected Ruth with the most “missed” walks were: Ed Morris (Red Sox, 4.33), Bobby Burke (Nationals, 4.13), Ownie Carroll (Tigers, 3.38), Red Faber (White Sox, 3.32), Tommy Thomas (White Sox, 3.32) and Garland Braxton (Nationals, 3.14). These six moundsmen collectively shortchanged Ruth by about 21–22 walks, less than half of the “missing” 46–48 walks. Of the 55 pitchers who faced Ruth in 1929 and in 1926–28 and/or 1930–32 (i.e., excluding the seven “1929-only” pitchers), only 14 hurlers exceeded their expected number of walks issued to Ruth. The pitchers who surpassed their expected number of walks issued to Ruth the most were: George Smith (Tigers, 2.45), Willis Hudlin (Indians, 2.08), Johnny Miljus (Indians, 2.00), George Earnshaw (Athletics, 1.40), Wes Ferrell (Indians, 1.20), and General Crowder (Browns, 1.18). So, the story does not seem to be that a few pitchers effectively joined forces to shackle Ruth’s typical excellent walk-drawing ability, thereby suppressing his expected bases on balls by 46–48 free passes.

At this point we know who the pitchers were that walked Ruth—at a reduced rate—in 1929. But, we don’t yet know why. Did the pitchers, in general, throw more strikes, which Ruth swung at—and hit? Was Ruth less selective and/or less patient against these pitchers than he had been in the past (1926–28)? It should be emphasized that when Ruth did swing the bat in 1929 he was successful 34.5% of the time in hitting the ball safely—i.e., getting a hit. For the 1926–1928 seasons he had compiled a composite .349 batting average, just four points higher than his 1929 batting average. And, as previously shown, he smacked an AL-leading 46 homers in 1929, despite missing 16 games during June due to a chest cold. Thus, in 1929, when Ruth swung the bat, he hit for average and he hit for power—just as he had done in his three previous seasons. And as he would also do in his next three seasons. So, at this point, there is not yet a clear answer to the question, “Why did Babe Ruth have an anomalously low W% in 1929?” Right now, all that can be said is that it seems that The Babe just swung at pitches more frequently in 1929 than he did in 1926–28 and than he would in 1930–32.

BABE RUTH’S SPLITS (1926–32)

We next turn our attention to the specific situations in which Ruth walked—and did not walk. Was there anything different about Ruth’s 1929 walks compared to his walks in 1926–28 and 1930–32 that would show up in his splits for these seasons? Table 4 exhibits some of the splits compiled for Ruth by Retrosheet.

Table 4. Splits for Bases on Balls Received by Babe Ruth (1926–32)

The information given in Table 4 shows that, on a percentage basis, Ruth’s 1929 home-away walks were 50–50, which is right in line with the 49–51 split he had for the entire 1926–1932 period. Similarly, his righty-lefty walks in 1929 were 76–24, which is fairly close to the 70–30 split for the 1926–1932 time frame. Likewise for the splits for runners on base—in 1929, The Bambino walked with the bases empty 46% of the time, which is reasonably close to the 42% he had during the 1926–32 seasons. So, nothing stands out as exceptional in these splits for the walks Ruth received in 1929.

Another split worth examining is Ruth’s position in the batting order. Table 5 provides pertinent information on his walks as a function of his batting slot. As can be readily seen, 1929 is noticeably different from the other six seasons.

Table 5. The Players Who Batted Behind Ruth (1926–32)

In 1929, Ruth split his time equally between the number three slot and the number four slot. For the 1926 season, Ruth primarily batted in the number four slot [126 games (84.5%)]. For the 1927 and 1930–1932 seasons, Ruth occupied the number three slot exclusively—100%. In the 1928 season, Ruth batted in the number three hole most of the time [132 games (85.7%)]. Rather than Ruth’s spot in the batting order, his tendency to be walked would likely be most affected by who was batting immediately behind him.

Eight different players batted right after Ruth in 1929. Each of the eight had at least one game behind Ruth when he was the number three batter; Lou Gehrig followed Ruth in the most games [35 out of the 66 games (53%)]. Three of the eight players split up batting behind Ruth when he was the number four batter; Tony Lazzeri followed Ruth in the most games (55 out of the 66 games, 83%).

Upon examining Table 5, two questions immediately jump out: (1) Was there any significant difference in Ruth’s 1929 W% when Gehrig followed him in the number three slot compared to his composite W% when the other seven players followed him in the number three slot? (2) How did Ruth’s 1929 W% with Lazzeri batting behind him (when Ruth batted clean-up) compare with Ruth’s 1930 W% with Lazzeri batting behind him (when Ruth batted third in the lineup)? Here are the answers:

In the 35 games that Gehrig followed Ruth (batting third) in 1929, Ruth had 147 plate appearances and drew 21 walks, which afforded a 14.3 W%. For the 31 games that Dickey, Combs, Meusel, Lazzeri, Durst, Paschal, and Byrd followed Ruth (batting third), Ruth had 124 plate appearances and received 12 bases on balls, which gave a 9.7 W%. Thus, not surprisingly (based on Ruth’s W% in the 1927 and 1930–32 seasons), Gehrig batting right behind Ruth had a significant positive impact on Ruth’s W% compared to Dickey et al. However, the 14.3 W% that Ruth produced in 1929 with Gehrig batting behind him was substantially and significantly less than the 20-plus W% that Ruth fashioned when Gehrig was the batter hitting right behind him in the 1927 and 1930–32 seasons. Why was that?

In the 55 games that Lazzeri followed Ruth (batting cleanup) in 1929, Ruth had 249 plate appearances and drew 35 walks, which afforded him a 14.1 W%. In 1930, with Ruth batting third, Lazzeri followed The Bambino in 82 games, during which Ruth had 317 plate appearances and 86 walks, affording a 27.1 W%. So, just as was the case with Gehrig batting behind Ruth in 1929 (in the third slot), with Lazzeri batting behind Ruth in 1929 (in the fourth slot), Ruth’s W% was substantially and significantly less in 1929. Why was that?

In 1929, Ruth’s W% with either Gehrig or Lazerri hitting immediately behind him was relatively lackluster—14.3% and 14.1%, respectively—compared to the composite 20.53 W% he manufactured in the 1926–28 and 1930–32 seasons. Akin to what was found for the pitchers, for the players who batted behind Ruth we know what the impact was. But, we don’t know why Ruth had a sharply reduced W% in 1929. The take-away message from the various splits considered in this section is that a definitive answer to the question, “Why did The Bambino’s walks plummet in 1929?” did not emerge.

Streaks

Was Ruth’s 1929 decline in bases on balls the result of a few streaks of extremely low walk rates? To address this possibility, Table 6 provides a chronology of Ruth’s performance as a hitter and as a walker in 10-game increments.

Table 6. Chronology of Babe Ruth’s BA and OBA in 10-Game Increments (1929)

As can be seen, there were three 10-game spans in which Ruth had only one or zero walks—(1) May 15–25 (one walk); (2) August 17–27 (one walk); (3) August 28–September 07 (zero walks). For the other ten 10-game periods Ruth typically walked between six and seven times. So, those three 10-gamers with one or zero walks cost Ruth about 20 walks—less than half of the “missing” 46–48 walks. To reach the expected 118–120 walks, Ruth needed to average about nine walks every ten games. So, Ruth just walked less than normal pretty much every week. Had Ruth walked between six and seven times in each of the 13 10-game segments and 3 times in the 5-game segment he would have amassed a total of about 87 walks, a total not even remotely close to the 118–120 walks he would accumulate in a typical 1926–28 or 1930–32 season. Thus, the take-away message here is: three drastic periodic walk slumps, while contributors, were not the cause of Ruth’s low number of walks in 1929. Appendix D provides three tables which give some self-explanatory details about those three 10-gamers. The Yankees went 13–17 in those 30 games. Perhaps the only positive item in the 30 games was that Ruth did slug eight home runs.

Babe Ruth’s Walks on a Team-by-Team Basis

Next, we examined the walks Ruth received in 1929 on a team-by-team basis.10 As indicated previously, in 1929 Ruth should have accumulated between about 118 and 120 walks. Extrapolating from the 118 walks that Ruth should have collected (instead of the 72 walks he actually received), in his 587 plate appearances he would have been hit by a pitched ball 5 times (instead of 3 times), hit 9 sacrifice flies (instead of 14), had 455 at bats (instead of 498), collected 157 hits (instead of 172), and slugged 42 homers (instead of 46). He still would have led the league in home runs as Gehrig finished in second place with 35 homers.

Table 7 presents the numbers of walks Ruth received from each team during the 1926–28 and 1930–32 seasons and his expected and actual walks for 1929.

Table 7. Walks Received by Babe Ruth on a Team-By-Team Basis (1926–32)

Inspection of Table 7 reveals that each of the seven opposition teams walked Ruth fewer times in 1929 than expected based on the free passes they issued to him in the 1926–28 and 1930–32 seasons. Significantly, the number of “missing” bases on balls were pretty much the same for each club—6–8 “missing” walks (except for Boston which shortchanged Ruth by 4 walks). Thus, the take-away here is that his “missing” walks in 1929 were not dependent on any particular opposition team’s mound staff.

SUMMARY

Under ordinary circumstances, like those during the 1926–28 and 1930–32 seasons, Babe Ruth would have reached first base via a walk 118–120 times in 1929. However, since he walked only 72 times, it means that 46–48 free passes were “missing.”

We know Ruth walked less in 1929. We know that Ruth’s total of 72 walks in 1929 is a statistically significant outlier, which can be excluded with 99% confidence. But, we have not yet found a definitive answer as to why he walked less in 1929. Babe Ruth was the only player among the top-ten AL players in total walks during the 1926–1932 time frame who suffered a significantly reduced W% in 1929 (or any other season). The top-ten included seven Hall of Famers, three of whom—Gehrig, Combs, and Lazzeri—were Ruth’s teammates. From the information presented in the Results section, we have essentially learned that there is no “on-the-field” explanation for Ruth’s anomalously low walk rate in 1929: W%(1929)=12.27; W%(1926–28)=20.62; W%(1930–32)=20.44; W%(1926–28,30–32)=20.53.

The bottom-line take-away from the Results section is that it seems that Ruth himself was the primary reason for his unusually low number of walks (and W%) in 1929.

DISCUSSION

When a pitcher hurls the ball toward the plate, the batter has two choices: (1) he can choose to swing at the pitch or (2) he can choose to not swing at the pitch. In order for a player to get a walk, he has to choose to not swing at least four times in a plate appearance. For Babe Ruth, during the 1926–28 and 1930–32 seasons, he chose to not swing a sufficient number of times that he ended up drawing walks at the rate of 20.53%. In 1929, Ruth instead chose to swing—and hit the ball—enough times that he ended up drawing walks at the rate of only 12.27%. Thus, in 1929, it appears that Ruth chose to swing at pitches more frequently than he did in the 1926–28 seasons and than he would in the 1930–32 seasons.

That Ruth swung at more pitches in 1929 can be reasonably interpreted to mean that he had less patience and was less selective (more aggressive?) in the batter’s box than he was in the 1926–28 campaigns and than he would be in the 1930–32 campaigns. And, very importantly, when he did swing at the pitches in 1929, he hit them just as effectively as he did in every other year during the 1926–28 and 1930–32 seasons. It is also important to point out that Babe Ruth’s intentional walks were not a factor at all in his stark decrease in walks in 1929. On average, The Sultan of Swat was purposely walked 7.7 times per season during 1926–28 and 6.0 times per year during 1930–32. In 1929 Ruth was walked intentionally five times.11

Why would Babe Ruth have less patience and be less selective (more aggressive?) in the batter’s box in 1929 compared to his previous three seasons and his subsequent three seasons? As described above, based on our research, the Why does not seem to be related directly to baseball—i.e., to what happens between the foul lines. Perhaps, Ruth simply decided to be less selective (more aggressive?) in 1929 in hopes of getting more hits and more homers (and, therefore, drive in more runs) than he had during his (three) prior seasons. However, when his 1929 results were pretty much in alignment with those in his 1926–28 seasons, he reverted back to his more selective approach for 1930 (and 1931 and 1932). While this simple explanation is plausible, we, instead, surmise that the why may have been of a more-personal nature to Babe, perhaps subconsciously so.

Off-the-Diamond Influence

On Friday, January 11, 1929, while Babe Ruth was residing in New York City, Helen Ruth, George Herman’s estranged wife, perished in a house fire in Watertown, Massachusetts. Babe learned of this tragedy the next night (Saturday) while he and his mistress, Claire Hodgson, were at a party hosted by his teammate, Joe Dugan. Later, on Sunday, after having taken a 1:15AM train to Boston, Ruth told the reporters who besieged his hotel room, “My wife and I have not lived together for the last three years. During that time I have seldom met her. I have done all that I can to comply with her wishes. Her death is a great shock to me.”12 As described in three biographies of Babe Ruth, this was a tremendously emotional time for Ruth, exacerbated with several subsequent complications that resulted in Helen’s funeral and interment finally taking place on Thursday, January 17.13

On April 17, 1929, less than 100 days after Ruth’s wife had died, Babe married Claire Hodgson, a former model and actress whom he had first met in May of 1923, when the Yankees were playing the Nationals in Washington. As described in biographies of Ruth, he and Claire had been a couple for the past three years.14

Either or both of these happenings could have affected Ruth’s mindset such that he chose—consciously or unconsciously—to swing more frequently at the pitches offered to him, thereby taking fewer pitches resulting in drawing fewer walks during the 1929 baseball season than he had drawn during the 1926–28 seasons (and would draw during the 1930–32 seasons).

It’s also possible that financial matters affected Ruth’s mindset in 1929. While one might assume he was increasingly worried about the financial state of the country, as the great stock market crash that ushered in the Great Depression would happen after the season ended. But Ruth was well insulated from the disaster thanks to the counsel of his investment manager/agent, Christy Walsh. With Walsh’s fiscally-conservative guidance, Ruth had been persuaded to open an irrevocable trust at the Bank of Manhattan in February 1927. “The deal was: all ancillary income would go into the trust while Ruth kept his Yankee salary to live on and play with.”15 Adhering (at least somewhat) to Walsh’s strategy, over the ensuing years Ruth “invested 70 percent of his [investment] money in fixed-income US government and municipal bonds and 30 percent in dividend-paying blue chips, utilities, and railroads.…When the crash came, the King of Clout would not take a hit.”16

However, Ruth’s financial situation was unexpectedly tight in 1929. Although he had been legally separated from Helen, he was required by law to provide financial support for their daughter, Dorothy. As it developed, at the time of Helen’s death, Ruth was more than $30,000 behind in his payments to Helen, and had not made a payment in 16 months.17 Ruth was continuing with his modus operandi: “I like to live as big as I can.”18 Within the next year (from the date of Helen’s death on January 11, 1929, until everything was finally settled with Helen’s estate on January 7, 1930), Ruth caught up with his debt, paying a total of $33,057.04 to Helen’s estate.19

Here are the pertinent financial details for Babe Ruth (1928–30): In 1928, Ruth earned $44,233 from endorsements, $70,000 in salary from the Yankees, and $3200 in dividends. He contributed only $10,000 to his trust.20 That left him with $107,433 (less taxes) to live on and play with. Nothing was paid to Helen. In 1929, Ruth earned $34,225 from endorsements, $70,000 in salary from the Yankees, and $4,000 in dividends. He contributed just $20,000 to his trust. Thus, he had only $88,225 (less taxes) to live on and play with.21 BUT, he also had to pay Helen’s estate $33,057 in back payments and interest over the last four months of the year after settling with Helen’s estate.22 Thus, in 1929, Ruth really had just $55,168 (less taxes—more on that in a moment) to live on and play with—less than half as much as he had had the previous year. In 1930, Ruth earned a total of $114,262 ($28,967 from endorsements, $80,000 in salary from the Yankees, and $5295 from dividends). He contributed a whopping $50,000 to his trust. Thus, even with Helen completely out of the picture, his bottom-line to live on play with was “just” $64,262 (less taxes), an amount which was considerably less than his 1928’s $107,433 (less taxes).23 However, it is noted that Ruth’s comparatively exorbitant $50,000 investment in his trust (rather than using much of it as “play” money) is in alignment with (a) Babe being now (presumably happily) married to Claire (who exercised a relatively firm grip on the purse strings) and (b) Babe legally adopting Claire’s daughter, Julia (and with Claire legally adopting Ruth’s daughter, Dorothy).24

Ruth’s unexpected tight financial situation in 1929, initiated by Helen’s untimely death, likely weighed heavily on Ruth as the new baseball season was about to begin and continued throughout the entire campaign. And, as if that was not bad enough, midway through the 1929 season Ruth was informed by the Internal Revenue Service that he was being audited for underpayment of his 1927 taxes. The IRS claimed he had underpaid his federal taxes for that year by nearly 20% and still owed them almost $4000. Even though that amount was just 5% of his annual salary, dealing with the IRS is not typically a pleasant task, and likely does nothing to reduce any stress. In December he settled the case, for just under $4000.25

A Possible Explanation

A possible way for Ruth to mollify the emotional anxiety of his financial situation (and any lingering grief over Helen’s passing) could have been for him to really focus on playing baseball, especially batting. In particular, getting hits. But one can only get hits by swinging the bat. And, if one swings the bat, one can’t get pitches called balls. And, if one doesn’t get four called balls in a plate appearance, one can’t draw a walk.

So, in 1929, it is possible that Ruth was less patient and less selective (more aggressive?) in the batter’s box. He could have swung at pitches more frequently than he had in the past, when he was not emotionally and financially stressed, and would again in the near term (i.e., the very next season), when the financial stress had been alleviated, and any emotional stress was further in the background.

Our Hypothesis

In 1929, with his mind distracted by his unexpected and pervasive year-long personal stress (chiefly financial), Babe Ruth chose (perhaps subconsciously) to swing at—and hit—more pitches (on a percentage basis) than he had in the 1926–28 seasons and than he would in the 1930–32 seasons, which resulted in him drawing fewer bases on balls in 1929, thereby producing a significantly lower walk rate (W%=12.27) than that he had fashioned in the 1926–28 seasons (W%=20.62) and than he would in the 1930–32 seasons (W%=20.44).

Unfortunately, the “to swing at—and hit—more pitches” contention in our hypothesis cannot be supported with hard and fast numbers. There are no data available on the actual numbers of the pitches and the calls of the pitches that Ruth received and swung at during Ruth’s playing time. Such pitch information has only been officially tracked since 1988 for pitch counts, e.g., balls and strikes, and since 2008 for pitch classifications, e.g., curveballs, sliders, cut fastballs, etc. and types of strikes.26,27

Nonetheless, while we hypothesize that, in 1929, Ruth was swinging at pitches more frequently, he was not swinging wildly at pitches. He hit .345 (only four points lower than the composite .349 batting average he had compiled during the 1926–28 seasons). And, he still hit with power—he belted a league-leading 46 circuit clouts (a 9.24% home run rate, just 1.01% less than the 10.25% home run rate he had produced during his financially stress-free 1926–28 seasons). Moreover, as noted earlier, Ruth struck out at an even lower rate in 1929 (11.85%) than he had in the 1926–28 campaigns (16.10%). One cannot get a hit if one swings and misses.

We also state that Ruth may not have knowingly or purposely chosen to swing at more pitches and thereby receive fewer walks in 1929 than in the 1926–28 seasons and in the 1930–32 seasons. His season-long choosing to swing at more pitches in 1929 may have been governed by his subconscious (not conscious) response to the financial stress he was enduring. Being proficient at receiving bases on balls and thereby enhancing one’s on base percentage was not an item of daily interest (or motivation) during the 1926–1932 period. The nowadays very useful and highly regarded on base percentage metric (OBP) was totally unknown during Ruth’s diamond career. OBP was not created and introduced until 1954 (thanks to Alan Roth and Branch Rickey) and did not reach the forefront for the evaluation of batter performance until 1973 (thanks to Pete Palmer).28,29 The official recognition of OBP by major league baseball did not occur until 1984.

During Ruth’s time, the batting records that appeared each week in The Sporting News and in the sports sections of numerous Sunday newspapers did not include the walks that batters received. The only stats presented were games (G), at bats (AB), runs (R), hits (H), runs batted in (RBI) and batting average (Pct or Ave). It was not until a few months after the end of the baseball season that the number of walks players received were published in The Sporting News and other newspapers. See Appendix E for the pertinent accounts provided in The Sporting News for the American League’s bases on balls leaders during the 1926–1932 seasons. For the 1929 season, the following statement, which is germane to our discussion, was included in The Sporting News article: “Ruth, who has been honored for years with more than 100 passes per season and holds the record with 170 [established in 1923], walked 72 times in 135 games [in 1929].”30

Once the financial burden of settling Helen’s estate was finally eliminated on January 7, 1930, so was Ruth’s financial stress. In the 1930 diamond campaign Ruth resumed his usual unfettered performance in the batter’s box. He returned to his more disciplined selective swinging and thereby achieved his normal high walk rate: W%=20.12. And, furthermore, as shown in Table 1, Ruth slightly improved his strikeout rate in 1930, lowering it to 11.78% while increasing his batting average 14 points to .359 and upping his home run rate to 9.46%.

THE PSYCHOLOGY OF HITTING

A batter has an infinitesimally brief time in which to decide whether or not to swing at a pitch.

“Depending on the pitcher and his delivery, the ball begins its flight [to the plate] roughly fifty-six to fifty-eight feet from the hitter. It’s traveling about 139 feet per second and so will cross the plate about four tenths of a second after being released.…So, the hitter must begin his swing at least 0.19 seconds or so before the moment of contact.”31

Thus, during that split-second time the batter needs to ascertain the speed (angular velocity) of the ball and decide whether or not to swing at the ball. If the initial decision is to swing, the batter must also decide where (horizontally and vertically) to swing the bat in order to intercept the ball. Also very important, close to the end of that “split second” is the batter’s reaction time for his critical final decision—to check his swing or to swing through.

By virtue of making it to the major leagues, MLB hitters are among the best in the world at reaction time and eye-hand coordination. Two of the greatest hitters in baseball history, Babe Ruth and Albert Pujols, stood out among their peers to such a degree that they specifically were scientifically evaluated for their seemingly superhuman abilities.

In 1921, psychology researchers at Columbia University tested Babe Ruth’s visual reactions and coordination. They discovered “that his eyes [vision] and ears [hearing] function more rapidly than those of other players; that his brain records sensations more quickly and transmits its orders to the muscles much faster than does that of the average man,” resulting in the ability of his brain to record sensations and more quickly transmit them to muscular movement. For example, they measured the response time of the average man to the stimulus of light as 180 one-thousandths of a second. Babe Ruth, however, needed only 160 one-thousandths of a second to make the same response.32 In 2006, scientists at Washington University (in St. Louis, Missouri) replicated the tests, using many of the same methods, which are still the standards for such examinations, and found similar results for Albert Pujols.33

We suggest that Babe Ruth was affected mentally—his mind being distracted—during the 1929 season due his stressful personal life situation (chiefly financial), and that this stress-induced distraction impacted his approach to judging pitches—i.e., first deciding whether to swing or to not swing and then deciding whether to swing through or check his swing. In 1929, we suggest that, because of his financial stress, Ruth chose (subconsciously?) to both swing more frequently and to swing through more frequently than he had done in the 1926–28 seasons and than he would in the 1930–32 seasons.

Evidence in Support of our Hypothesis

As presented in Atkinson and Hilgard’s Introduction to Psychology, “Another common reaction to a stressful situation is anger, which may lead to aggression. … Direct aggression toward the source of frustration is not always possible or wise. When circumstances block direct attack on the cause of frustration, aggression may be displaced [such as swinging a baseball bat at a pitched ball].”34 Furthermore, “In addition to emotional reaction, people often show substantial cognitive impairment when faced with serious stressors. They find it hard to concentrate and organize their thoughts logically. As a result, their performance on tasks, particularly complex tasks, tends to deteriorate [such as having reduced reaction time to decide whether or not to check the swing of the bat at a pitched ball—a very complicated task].”35,36

For Ruth, in 1929, because of his financial stress, rather than take a close pitch, he may have been more likely to swing at the pitch or to not react quickly enough to check his swing, which resulted in him receiving fewer walks than he would have if not burdened and distracted by the anxiety of his financial situation.

It is important to emphasize that while Ruth was less patient and less selective (more aggressive?) at bat during the 1929 season, his “bat-swing” mechanics were so highly developed that his decreased selectivity (increased aggressiveness?) did not diminish his overall performance as a hitter. He just walked less because he swung more. Because of receiving fewer walks, his on base percentage went down (as did his run scoring—see Appendix F, but his power did not. In 1929 he led the league in home runs and slugging average, as well as in the nowadays highly regarded metric “On Base Plus Slugging” (OPS).37 Ruth was not swinging out of control—recall that his strikeout rate in 1929 (11.85%) was lower than it was in 1928 (16.23%). He was just swinging more often (and/or checking his swing less often). As a result, his overall season performance does not stand out as below normal except in the category of bases on balls.

We liken Babe Ruth’s (subconsciously-governed?) increased swinging (and decreased checked swings) to the classic subconsciously-controlled action of an automobile driver routinely driving his car along the same route day after day.38,39,40 Because of unanticipated anxiety or stress, the automobile driver, when confronted with an amber traffic signal, might speed up slightly to “make the light” rather than slowing down and stopping for the upcoming red light as he would normally do when not under stress. The Bambino, because of the anxiety and stress of his unexpected season-long tight financial situation in 1929, swung at close pitches that he normally would have checked and usually received a “ball” call. Because the pitch was close enough to being a strike in his hitting zone, he was still able to hit the ball with his normal high level of skill such that his batting performance was not negatively impacted.

CONCLUDING REMARKS

Babe Ruth’s 1929 season was anomalous with regard to his 12.27 W% compared to the composite 20.53 W% he achieved during the 1926–28 and 1930–32 seasons. 1929’s 12.27 W% is a serious statistical outlier in the 1926–1932 sequence of W% results, as well as for his entire career.41 As described in the Results section, we have ascertained that the why appears to be of his own doing throughout the duration of the 1929 season and was not dependent, for example, on the pitchers he faced or the teammates who batted behind him. Instead we suggest that the why was of a personal nature for Ruth, directly related to his unexpected financial anxiety which cascaded from the unexpected premature tragic passing of his estranged wife. The financial stress consumed the entirety of 1929—from her death on January 11 until her estate was settled on January 7, 1930.

Not surprisingly, a diamond consequence attributable to a personal situation is not unheard of. There are numerous examples of players hitting home runs on special days, such as birthdays.42 Similarly, there are many instances of players “promising to try to do something special” for a child dealing with a life-threatening situation or condition—such as, in 2022, Tampa Bay’s Brett Phillips coming through for 8-year old Chloe Grimes battling cancer or, in 2016, Boston’s David Ortiz declaring that he’s “gonna hit a home run for you” (Maverick Schutte, a 5-year old with a congenital heart defect).43 Of course, there’s the famous example involving George Herman and Johnny Sylvester (an 11-year old hospitalized with a serious brain injury)—The Bambino signed a baseball with the message, “I’ll knock a homer for [you in] Wednesday’s game [of the 1926 World Series]. Babe Ruth.”44 Fulfilling his pledge, Ruth proceeded to belt three round-trippers in that game.

Another example, particularly germane to this article, concerns Hank Aaron’s 1971 season. Aaron had a stellar season that year following a five year “winding down my career decline” during which he compiled a relatively low .294 batting average while averaging 39 homers per season. In his previous twelve seasons (including his 1954 rookie campaign) he had assembled a sterling .320 batting average—the highest composite batting average in the majors during the 1954–1965 time frame—and averaged 33 homers per year. In 1971, following his 1966–1970 decline, he fashioned a robust .327 batting average and walloped 47 home runs—the most homers he slugged in a single season during his Hall of Fame career. In his autobiography, Aaron, who in 1971 was going through a divorce from his first wife stated, “I felt lonely and angry, and, to a degree, I was taking my domestic problems out on the pitchers. The only way I knew to feel better was to pound the ball into the seats.”45 With his personal issues behind him, Aaron returned to his “winding down my career” level of performance in his final three nearly full-time seasons (1972–74), composing a rather pedestrian .278 batting average and averaging 31 homers per year. It seems reasonable to presume that there are other examples, besides Ruth and Aaron, of a player’s performance between the foul lines having been impacted by personal off-the-diamond circumstances.

Babe Ruth apparently never commented on why the number of his bases on balls (or W%) in 1929 was so anomalously low compared with his other seasons (particularly 1926–28 and 1930–32). Thus, we may never know exactly why. None of the biographies of The Bambino (end notes 4–6) even included mention of the anomalously low number of walks he received in 1929. Likewise, as best as we were able to determine, with the exception of the aforementioned solitary sentence in The Sporting News (end note 30), none of the numerous books and newspaper and magazine articles on The Sultan of Swat mentioned anything about his anomalously low number of walks in 1929. We contend that our hypothesis is plausible and that the documented facts of Ruth’s finances during the 1928–30 period fully support the plausibility of our hypothesis.46 

HERM KRABBENHOFT is a retired organic chemist (BS, Wayne State University, 1970; PhD, University of Michigan, 1974) and author of Leadoff Batters of Major League Baseball (McFarland, 2001). Among the various baseball research topics he has pioneered are: Ultimate Grand Slam Homers, Consecutive Games On Base Safely (CGOBS) Streaks, Quasi-Cycles, Imperfect Perfectos, Downtown Golden Sombreros, Pitcher’s Cycles, and Predators on the Mound; Prey at the Plate. In addition to The National Pastime and the Baseball Research Journal, Herm has contributed articles to the newsletters for these SABR Committees: 19th Century, Deadball Era, Statistical Analysis, and Baseball Records. Krabbenhoft has received three SABR Baseball Research Awards (1992, 1996, 2013).

MICHAEL HAUPERT is co-chair of the SABR Business of Baseball Committee.

Acknowledgments

Grateful thanks are extended to Larry Annis, Bill Deane, Chris Green, Jeanie Krabbenhoft, Cassidy Lent, Pete Palmer, Jeff Robbins, Gary Stone, Mary Anne Todgham, and Dixie Tourangeau for very helpful discussions and inputs.

Notes

1. David Firstman, “The Growth of ‘Three True Outcomes’: From Usenet Joke to Baseball Flashpoint,” SABR Baseball Research Journal, Volume 47, Number 1 (Spring 2018), 29–37.

2. Robert W. Creamer, Babe…The Legend Comes to Life (Simon and Schuster, 1974; reprinted by Penguin, 1986), 301.

3. Creamer, 1974.

4. Babe Ruth (as told to Bob Considine), The Babe Ruth Story (E.P. Dutton & Co., 1948, Pocket Book edition).

5. Leigh Montville, The Big Bam (New York: Doubleday, 2006).

6. Jane Leavy, Big Fella: Babe Ruth and the World He Created (Harper Collins, 2018).

7. Kathryn Haas, “Rejection of Outliers (Q-Test),” May 8, 2024. Accessed January 6, 2025. https://chem.libretexts.org/Courses/Duke_University/CHEM_310L%3A_Physical_Chemistry_I_Laboratory/CHEM310L_-_Physical_Chemistry_I_Lab_Manual/09%3A_Under_Construction/9.09%3A_The_Treatment_of_Experimental_Error/9.9.04%3A_Rejection_of_Outliers_(Q-test). Following the Q-Test procedure using the W% values given in Table 1, one calculates Q(exp) to be 0.717 [(19.31—12.27) / (22.09—12.27) = 7.04 / 9.82 = 0.717]. According to the Q-Test table for 7 data, Q (99%) is 0.680. Since Q(exp) is greater than Q(99%), the datum 12.27 can be excluded with 99% confidence.

8. The means and standard deviations were obtained from the Standard Deviation Calculator on “Calculator.Net.” Accessed January 11–15, 2025. https://www.calculator.net/standard-deviation-calculator.html?

9. The Z-score was obtained from the Z Score Calculator. https://www.calculatorsoup.com/calculators/statistics/z-score-calculator.php. Accessed July 18, 2025.

10. The authors thank Chris Green for the guidance to consider Ruth’s walks on a team-by-team basis—Chris Green, email correspondence with the authors, July 9–11, 2025.

11. It is important to point out that “intentional bases on balls (IBB)” were not an officially recorded stat until 1955. Thus, the IBB numbers stated here (as given on the Retrosheet website) are based on available information in game descriptions presented in various newspaper accounts and may not be complete. The authors thank Bill Deane for bringing this to their attention—Bill Deane, email correspondence with the authors, July 21–24, 2025.

12. Creamer, 338.

13. Creamer, 335–41; Montville, 281–87; Leavy, 339–55.

14. Creamer, 341; Montville, 178–80, 196, 204, 209, 263, 288–90; Leavy, 58, 252, 254–55, 260, 274, 276–84.

15. Leavy, 132.

16. Leavy, 395.

17. Creamer, 228–29, 281–82, 302–03, 320–23; Montville, 44, 52–54, 120, 130, 157, 163, 170, 178, 207–8, 365; Leavy, 7–58, 83, 207–8, 242, 248–50, 274–75.

18. Creamer, outside back cover.

19. Michael Haupert, “The Business of Being the Babe,” SABR Baseball Research Journal, Volume 50, Number 1 (Spring 2021), 7.

20. Leavy, 501–11.

21. Leavy, 501–11.

22. $2,000 (August 9, 1929), $13,000 (September 4, 1929), $18,057.04 (January 7, 1930). Letter from James J. Conlin to Christy Walsh, September 4, 1929.

23. Leavy, 501–11.

24. Leavy, 372–75.

25. Letter from IRS to George Herman Ruth, December 18, 1929.

26. Cory Schwartz and Sam Sharpe, “MLB Pitch Classification,” MLB Technology Blog, February 3, 2020. https://technology.mlblogs.com/mlb-pitch-classification-64a1e32ee079. Accessed July 17, 2025.

27. Mike Petriello, “Feel the breeze: The pitches that get the most extreme whiffs,” MLB.com, February 22, 2024. https://www.mlb.com/news/biggest-statcast-bat-tracking-missed-pitches-of-2023. Accessed July 17, 2025.

28. Branch Rickey, “Goodby to Some Old Baseball Ideas,” Life, August 2, 1954, 78.

29. Pete Palmer, “On Base Average for Players,” SABR Baseball Research Journal, Volume 2 (1973), 87.

30. “Simmons’ Value to A’s Shown in Run Scoring,” The Sporting News, January 23, 1930, 7.

31. Mike Stadler, The Psychology of Baseball (New York: Gotham Books, 2007), 7, 15.

32. Hugh S. Fullerton, “Why Babe Ruth is the Greatest Home-Run Hitter,” Popular Science Monthly, Volume 99, Number 4, 19.

33. Gary Everding, “St. Louis Cardinals slugger Pujols gets Babe Ruth test at Washington University,” The [Washington University] Source, August 22, 2006. https://source.washu.edu/2006/08/st-louis-cardinals-slugger-pujols-gets-babe-ruth-test-at-washington-university/. Accessed February 5, 2025.

34. Susan Nolen-Hoeksema, Barbara L. Frederickson, Geoff R. Loftus, Willem A. Wagenaar, Atkinson and Hilgard’s Introduction to Psychology (Boston: Engage Learning, 2009), 502. https://invent.ilmkidunya.com/images/Section/introduction-to-psychology-css-psychology-book.pdf. Accessed February 13, 2025.

35. Susan Nolen-Hoeksema, Barbara L. Frederickson, Geoff R. Loftus, Willem A. Wagenaar, 512, “Cognitive impairment.”

36. That hitting a baseball is a “very complicated task” is supported by what Ted Williams stated: “Hitting a baseball—I’ve said it a thousand times—is the single most difficult thing to do in sport.” Ted Williams and John Underwood, The Science of Hitting (1970, free copy). https://dt5602vnjxv0c.cloudfront.net/portals/27871/docs/the%20science%20of%20hitting%20by%20ted%20williams.pdf. Accessed July 19, 2025.

37. Pete Palmer, “Why OPS Works,” SABR Baseball Research Journal, Volume 48, Number 2 (Fall 2019), 43.

38. Susan Nolen-Hoeksema, Barbara L. Frederickson, Geoff R. Loftus, Willem A. Wagenaar, Chapter 6, “Consciousness.”

39. Eliezer J. Sternberg, NeuroLogic (New York: Pantheon Books, 2015), Chapter 2, “Can Zombies Drive to Work?”

40. Adam Gazzaley and Larry D. Rosen, The Distracted Mind (Cambridge, MA: MIT Press), 94.

41. Conducting the Q-Test on Babe Ruth’s entire full-time field-position career [i.e., excluding the seasons he pitched for the Red Sox (1914–19) and the abnormal partial seasons he had with the Yankees in 1922 (a six-week suspension by Commissioner Landis, which resulted in Ruth missing the first 33 games of the season) and in 1925 (illness, dubbed “the bellyache heard ’round the world,” and surgery, which resulted in Ruth missing the first 41 games of the season)], asserts that the 1929 W% (12.27) can be rejected as an outlier with 99% confidence—Q-quotient = 0.628; Q-quotient threshold for data point rejection with 99% confidence = 0.617. See: “Dixon’s Q Test: Definition, Step by Step Examples + Q Critical Values Tables,” Statistics How To, https://www.statisticshowto.com/dixons-q-test/.

42. (a) Herm Krabbenhoft, “Birthdays: Motivation for Enhanced Home Run Performance,” By The Numbers, SABR Statistical Analysis Committee, Volume 2, Number 3 (June 1990), 7–10. (b) Sarah Langs, “9 Outstanding baseball birthday performances,” MLB.com, January 2, 2023. https://www.mlb.com/news/best-baseball-birthday-performances. Accessed August 7, 2025.

43. (a) Adam Berry, “‘Chloe, you’re an inspiration’: Phillips homers for young fan,” MLB.com, April 13, 2022. https://www.mlb.com/news/brett-phillips-hits-home-run-inspired-by-young-fan. Accessed August 20, 2025. (b) Nik DeCosta-Klipa, “David Ortiz keeps promise to inspirational young fan with game-winning home run,” Boston Globe, April 30, 2016. https://www.boston.com/sports/boston-red-sox/2016/04/30/david-ortiz-promise-homer-fan/. Accessed August 20, 2025.

44. “Ruth and Johnny Sylvester,” Babe Ruth Central. Accessed August 7, 2025. https://www.baberuthcentral.com/babesimpact/legends/little-johnny-sylvester/; “The Babe, The Boy, & The Ball,” YouTube MetroFocus, July 16, 2018. https://www.google.com/search?q=babe+ruth+johnny+sylvester+ball&rlz=1C5CHFA_enUS971US972&oq=babe+ruth+johnn&gs_lcrp=EgZjaHJvbWUqCAgBEEUYJxg7MgYIABBFGDkyCAgBEEUYJxg7MgcIAhAuGIAEMggIAxAAGBYYHjIICAQQABgWGB4yBggFEEUYPDIGCAYQRRg8MgYIBxBFGDzSAQg2NzkwajBqN6gCALACAA&sourceid=chrome&ie=UTF-#fpstate=ive&vld=cid:2ad8b06d,vid:URuK7wlgvYo,st:0. Accessed August 31, 2025.

45. Hank Aaron with Lonnie Wheeler, If I Had a Hammer (New York: Harpercollins, 1991), 210.

46. Some of the research in this article was presented at SABR 53, the 2025 convention of the Society for American Baseball Research in Mike Haupert and Herm Krabbenhoft’s presentation, “Babe Ruth’s Anomalous 1929 Season.”

Some baseball analysts have pointed to baseball’s adoption of its “Clean Ball Policy” following the August 1920 beaning death of Cleveland SS Ray Chapman as a major catalyst of the surge in hitting and scoring that marked the turning point demarcating the end of baseball’s “Deadball Era” and the dawn of the modern game. If this hypothesis is true, this offensive surge should show up mainly in the later innings, when scuffed and dirty balls would have previously remained in play; the new policy would have had little or no impact in the early innings, when fresh baseballs were always in play. I tested this hypothesis by comparing total runs per 9 IP, ERA, OPS, HR per 9 IP, and SO per 9 IP in 1921–29 versus 1912–20 in the AL and NL for each inning and for three-inning groupings (1–3, 4–6, 7–9). Highly significant improvements (increased scoring, OPS and HR and decreased SO) were observed in every inning in each league after 1920. While these improvements tended to be somewhat smaller in the first three innings than later in the game, the differences between inning categories were of borderline statistical significance at best. Thus, MLB’s adoption of the Clean Ball Policy seems to have played only a minor role in the offensive resurgence of the 1920s.

INTRODUCTION

The 1920 season marked a watershed in the history of major league baseball (MLB). It was the year when Kenesaw Mountain Landis was named Baseball Commissioner in the aftermath of the gambling scandal that forever tainted the 1919 World Series.1 This season was also noteworthy for the founding of the Negro National League, the first (retroactively) recognized major league for non-white players.2 The 1920 season also marked Babe Ruth’s debut as a Yankee and as a full-time outfielder; he hit an astounding 54 HR, nearly doubling his previous MLB record of 29 HR set in 1919.3

On a somber note, 1920 was also the season in which Cleveland’s beloved 29-year-old star shortstop, Ray Chapman, was hit in the head and killed by a submarine fastball thrown by Yankee Carl Mays in the top of the fifth inning on August 16.4 It was an overcast and rainy afternoon, and the ball was damp and discolored. Chapman, who habitually crowded the plate, never saw the pitch coming until it was too late. Although MLB disregarded calls for mandatory batting helmets until many years later, it took immediate steps to require prompt removal of scuffed and discolored baseballs from play—the “Clean Ball Policy.”

Most importantly—and perhaps not coincidentally—the 1920 season is widely regarded as the inflection point marking MLB’s transition from the nearly two-decade scoring slump known as the “Deadball Era” to the free-swinging modern game.5 The term “deadball” is largely a misnomer, since it attributes the scarcity of runs to the characteristics of the ball used in the early twentieth century, which in fact was the same as the ball used in the mid-1890s, when the league-wide ERA was at its all-time high.6 The decline in scoring around the turn of the century was due mostly to a combination of the influx of stronger, harder throwing pitchers, the popularization of the spitball, and improvement in fielding gloves, and was greatly accelerated by the adoption of the foul-strike rule in 1901 (NL) and 1903 (AL).7 MLB did try to stimulate scoring starting in 1910 by substituting cork for the hard rubber core to make baseballs lighter and livelier, but this change brought only a modest and transient increase in scoring in 1911–1913.8

Although the first signs of MLB’s offensive resurgence of the 1920s actually appeared as early as 1918 or 1919, the hypothesis that the “Clean Ball Policy” adopted after the August 1920 death of Ray Chapman might have fueled this resurgence has recently gained currency.9 After all, it stands to reason that balls that have been discolored, scuffed, softened, and/or misshapen by repeated use may become harder to see and to hit. Fortunately, it is quite easy to test this hypothesis by comparing inning-by-inning splits of run scoring and other offensive indices before and after 1920. Since each game started with a fresh baseball even before 1920, the implementation of the Clean Ball Policy could have affected scoring only after balls would otherwise have been in play long enough to become scuffed or dirty. Thus, we should see little or no impact on scoring in the first inning but an ever widening impact as one progresses from the second through the ninth (and extra) innings. We will now compare and contrast the actual inning-by-inning splits in runs and other related performance measures in the nine years immediately preceding (1912–20) and following (1921–29) MLB’s implementation of the Clean Ball Policy.

A roughed-up baseball from the Deadball Era. (Library of Congress)

METHODS

All data used in this article were taken from Baseball Reference.10 Inning-by-inning splits were calculated using their Stathead tool.11 These splits are only available starting in 1912 and are unavailable for the Negro Leagues. Although splits are available for the Federal League, we confined our analysis to the American (AL) and National (NL) Leagues to keep the number of teams constant from year to year. Since the Clean Ball Policy was not in effect through most of the 1920 season, we classified 1920 as a pre-Clean Ball Policy season in our grouped analyses.

The outcome parameters we examined were total runs (R), earned runs (ER), home runs (HR), and strikeouts (SO), each normalized per 9 IP per team, and on-base plus slugging percentage (OPS). There were slight discrepancies in R, HR, and SO between the Baseball Reference pitching and batting databases presumably due to missing data; we used the numbers from the pitching stats.

Analyses of variance were performed using Microsoft Excel’s Data Analysis Tools add-in. Two-way ANOVA models with replicates were used. The main factors were the Inning-by-Inning Split (10 categories—first to ninth innings and extra innings), and Period (2 categories—1912–20 and 1921–29), and their interaction (whether the change in outcome between the two time periods differs by Inning Split). Yearly totals from each of the two leagues and nine seasons provided the 18 replicates (2*9) for each Inning*Period category. This ANOVA had 359 (2*10*18-1) degrees of freedom. The alpha level was set at 0.05. We also repeated these analyses after collapsing the inning splits into three categories—1–3, 4–6, 7–9—and omitting the Extra Innings data. In these ANOVAs, each Inning Split*Period category had 54 replicates (3*2*9) and there were 323 (2*3*54-1) degrees of freedom.

RESULTS

Figures 1–4 show the temporal trends for scoring, OPS, HR, and SO for each league from 1910–30.12

Figure 1. Total and Earned Runs per 9 IP

 

Figure 2. On-Base Plus Slugging Percentage

 

Figure 3. Home Runs per 9 IP

 

Figure 4. Strikeouts per 9 IP

 

To address the extent (if any) to which this offensive surge was fueled by MLB’s adoption of the Clean Ball Policy after the August 1920 death of Ray Chapman, inning-by-inning splits in run scoring, OPS, HR and SO were compared in the nine seasons following this tragedy (1921–29) versus the nine seasons preceding this tragedy (1912–20).13 If the Clean Ball Policy played a significant role in the offensive surge, one would expect to see no increases in offensive metrics in the first inning and ever growing increases in these metrics as one progressed through innings 2–9 and into extra innings. This is not what happened.

Table 1. Scoring, OPS, HR, and SO Before and After Adoption of the Clean Ball Policy

Offensive production clearly rose after 1920 across the board (Table 1). Teams scored roughly one more run (and one more ER) per 9 IP in 1921–29 than in 1912–20 for every inning split category. OPS also rose consistently, HR rates increased two- to three-fold, and strikeout rates dropped. Note also that scoring is consistently highest in the first inning (when a team’s best hitters come to the plate) and lowest in the second inning (when the bottom of the order usually comes to the plate) in both time periods. This effect is smoothed out when three-inning groupings were analyzed (bottom three rows). Offensive production follows no particular pattern thereafter except for a drop-off in extra innings.

The key question for our present purpose is whether the increase in offensive production after introduction of the Clean Ball Policy in late 1920 was significantly greater in the later innings (when this policy should in theory have had the most impact) than in the earlier innings (when this policy should in theory have had little or no impact).

Table 2 shows the increases in scoring, OPS, and HR rate and the decrease in SO rate between 1912–20 and 1921–29 for each inning and for three three-inning groupings (which exclude extra innings).

Clearly, there was substantial improvement in every offensive indicator – more total and earned runs, higher OPS, more home runs, and fewer strikeouts – across the board, even in the first inning, before baseballs had much chance to become dirty or scuffed. Thus, the adoption of the Clean Ball Policy was clearly not the primary cause of the offensive renaissance of the 1920s. That being said, the changes – especially in OPS – appear to be greater in innings 4–9 and in extra innings than in innings 1–3. Two-way ANOVA was performed to address the statistical significance of these more subtle differences (Table 3).

Table 3. Two-Way ANOVA for Changes in Scoring, OPS, HR, and SO By Inning and Time Period

We did the ANOVA in two ways: 1) by individual inning, with the composite of extra innings as the 10th category, and 2) by three-inning grouping, excluding extra innings. Clearly, the average differences between the nine year periods preceding and following 1920 were overwhelmingly significant for every offensive indicator. The offensive differences by inning were also highly significant when considered inning by inning (10 categories) but not when collapsed into three-inning groupings, in which the highest and lowest scoring innings (the first and second) offset each other in the Innings 1–3 category. Most importantly for our hypothesis, the interaction between Inning Split and Time Period (which tests the whether the offensive metrics improved more in the later than the early innings) was statistically significant only for HR (P=0.047) in the inning-by-inning analysis and for HR (P=0.012) and OPS (P=0.022) in the analysis of three-inning groupings. Thus, while the Clean Ball Policy may have had a marginally stimulatory impact on offense, it was not the major driver of the transformation from the “deadball” to the “live ball” era.

The eight groups are as follows:

1. Fastest 50% of average bat speed of the heaviest 50% of the tallest 50% of qualified players (n=27)

2. Slowest 50% of average bat speed of the heaviest 50% of the tallest 50% of qualified players (n=28)

3. Fastest 50% of average bat speed of the lightest 50% of the tallest 50% of qualified players (n=27)

4. Slowest 50% of average bat speed of the lightest 50% of the tallest 50% of qualified players (n=28)

5. Fastest 50% of average bat speed of the heaviest 50% of the shortest 50% of qualified players (n=32)

6. Slowest 50% of average bat speed of the heaviest 50% of the shortest 50% qualified players (n=32)

7. Fastest 50% of average bat speed of the lightest 50% of the shortest 50% of qualified players (n=28)

8. Slowest 50% of average bat speed of the lightest 50% of the shortest 50% of qualified players (n=26)

Once grouped, each manipulatable swing aspect “attack angle, attack direction, and contact point in front of center of mass” was individually compared to the exit velocity for that group. The correlation coefficient (r) was first found between each respective group and exit velocity. Then, the equation:

was used to solve for the t–statistic (t). The t–statistic is a value that is used to quantify the difference between a sample’s estimated value and an assumed value. The t–statistic was then used to determine the p–value using (p) the Excel function “T.DIST.2(t, n-2)”. The p-value was then determined and used to either prove or reject the null hypothesis. A p-value of <.05 correlated with a rejection of the null hypothesis. A p-value of >.05 correlated with an acceptance of the null hypothesis.

RESULTS

Under the search parameters set for, 226 active MLB players qualified for this study during the 2025 season. The first swing metric compared to average exit velocity was attack direction, which is the horizontal angle at which the sweet spot of the bat makes contact with the baseball. Across all eight groups there was no significant relationship found between a player’s average exit velocity and attack direction (Table 1). This was confirmed by the p-values across all eight groups being greater than .05, thus accepting the null hypothesis. The null hypothesis for this group states there is no significant relationship between average exit velocity and attack direction.

The next swing metric compared to average exit velocity was the attack angle, which is the vertical angle of the bat as it comes into contact with the baseball. The only group of players which demonstrated a significant relationship between these two metrics was group 7, which comprised the fastest 50% of average bat speed of the lightest 50% of the shortest 50% of qualified players. This was indicated by a p-value of less than .05, which rejects the null hypothesis that there is no significant correlation between attack angle and average exit velocity. For all the other 7 groups, there was no significant relationship found between these two variables based on a p-value greater than .05 (Table 2). This accepts the null hypothesis that there is no significant relationship between average exit velocity and attack angle.

Table 2. Statistical Values of the Comparison of Eight Stratified Player groups Between Attack Angle and Exit Velocity

The final swing metric compared to average exit velocity was the contact point in front of a batter’s center of mass, which is the point in front of the batter’s center of mass, measured in inches, at which the bat makes contact with the ball. Across all eight groups there was no significant relationship found between a player’s average exit velocity and contact point in front of their center of mass (Table 3). This was confirmed by the p-values across all eight groups being greater than .05, thus accepting the null hypothesis. The null hypothesis for this group states there is no significant relationship between average exit velocity and contact point in front of a batter’s center of mass.

CONCLUSION

In baseball, one of the most valuable qualities a hitter can possess is the ability to generate high exit velocity. A player’s batting average is one of the strongest indicators of offensive success in the MLB, yet it is notoriously difficult to predict.9 Research has shown, however, that higher average batted-ball exit velocity is directly linked to improved hitting outcomes, including increased batting average, slugging percentage, and extra-base hit production. Therefore, the ability to produce a higher average exit velocity as a hitter is highly desirable. While a player’s height and weight are generally non-modifiable variables, the ability to manipulate a hitter’s swing mechanics is often desirable in search of greater productivity.10

In the present study, we examined the effects of a batter’s attack angle, attack direction, and contact point in front of the center of mass in regard to their effect on average exit velocity of a batted ball. Significance was found between attack angle and average exit velocity amongst one subset of players (Group 7: fastest 50% of average bat speed of the lightest 50% of the shortest 50% of qualified players). Rationale for this may suggest that for shorter, lighter players with above-average bat speed, a greater upward bat path at contact may contribute to increased exit velocity. This finding supports the concept that optimal swing mechanics may vary depending on player-specific characteristics.11 However, it is important to note that this relationship was not observed across the majority of player groups.

Additionally, while anthropometric characteristics such as height and weight have historically been associated with performance, the findings of this study support the growing body of literature suggesting their contribution to hitting outcomes is limited. While trends in professional baseball have shown increases in player size over time (11,12), these factors alone do not appear to strongly dictate exit velocity or overall hitting success.12,13 This is further supported by Orishimo et al., who demonstrated that lower extremity kinematics and kinetic sequencing contribute more significantly to bat speed and swing efficiency than static anthropometric measures.14

Another important consideration is that while this study evaluated attack angle and attack direction independently, these variables are components of the broader concept of swing path, which likely plays a more critical role in determining batted-ball outcomes. Nakashima et al. highlighted that swing path directly influences timing precision and contact quality, emphasizing that hitting performance is dependent on a multifactorial interaction between bat trajectory, timing, and coordination rather than isolated swing parameters.15 This may explain why limited significant relationships were identified in this study when evaluating individual swing metrics in isolation.

The remainder of modifiable swing mechanics failed to reach statistical significance across the remaining player subgroups. While the current study encompassed 226 players, dividing them into eight subgroups resulted in relatively small sample sizes (N range 26–32), which may limit statistical power. The authors believe that increasing the number of seasons analyzed could provide a larger dataset and greater insight into subgroup-specific trends (13).

Furthermore, while this study confirms that hitters are more likely to increase their average exit velocity by focusing on known contributors such as increased bat speed (2) and increased muscle mass gain (3), these relationships are already well established in the literature. The more meaningful implication of this study is that isolated adjustments to swing mechanics, such as attack angle, attack direction, or contact point, may not independently result in improved hitting performance for most players. Instead, improvements in batted-ball outcomes likely require a comprehensive approach that incorporates bat speed development, efficient kinetic sequencing, and individualized swing mechanics.

In conclusion, the adjustment of attack angle may benefit a small subgroup of hitters based on the findings of this study, while adjustments to attack direction and contact point in front of the center of mass are unlikely to independently increase exit velocity. Future research should incorporate larger sample sizes, longer timeframes, and a more integrated analysis of swing path and full-body mechanics to better understand their relationship with hitting performance. 

RYAN MARRA is a medical student at Duquesne University and a former collegiate baseball player at Brown University. He has a passion for sports medicine and baseball and hopes to practice medicine in a field that allows him to stay active within the baseball community.

Notes

1. Mohammadreza Hojat and Gang Xu. “A Visitor’s Guide to Effect Sizes—Statistical Significance Versus Practical (Clinical) Importance of Research Findings.” Advances in Health Science Education: Theory and Practice 9, 241–49 (2004).

2. Jake Singleton. “Exit Velocity and a Player’s Offensive Value | Sports Analytics Group at Berkeley.” Sports Analytics Group Berkeley, November 2, 2017. https://sportsanalytics.studentorg.berkeley.edu/articles/mlb-exit-velocity.html.

3. Alan M. Nathan, “Dynamics of the baseball-bat collision,” American Journal of Physics, November 1, 2000, 979–90. https://pubs.aip.org/aapt/ajp/article-abstract/68/11/979/1055418/Dynamics-of-the-baseball-bat-collision.

4. Yungchien Chu, Karen Keenan, Katelyn Allison, Scott Lephart, and Timothy Sell, “The positive correlation between trunk, leg, and shoulder strength and linear bat velocity at different ball locations during the baseball swing in adult baseball hitters,” Isokinetics and Exercise Science, 23:4, November 1, 2015, 237–44.

5. “Statcast Swing Path/Attack Angle.” Baseball Savant, Major League Baseball, 2025, http://baseballsavant.mlb.com/leaderboard/bat-tracking/swing-path-attack-angle?sortColumn=avg_intercept_y_vs_batter&sortDirection=desc. Accessed 25 June 2025.

6. Michael E. Houston, Gaining Weight: The Scientific Basis of Increasing Skeletal Muscle Mass, Canadian Science Publishing, August 1999.

7. Jordan N. Kohn, Liam Lochhead, Jiren Feng, Ryan Bobb, and L. Gregory Appelbaum. Strength, speed, and anthropometric predictors of in-game batting performance in baseball. Journal of Sports Sciences 42:8, (2024) 720–27.

8. B.S. Everitt and A. Skrondal, The Cambridge Dictionary of Statistics. 4th ed., Vol. 1, (Cambridge, Cambridge University Press, 2010).

9. Sarah R. Bailey, Jason Loeppky, and Tim B. Swartz, “The Prediction of Batting Averages in Major League Baseball,” MDPI, April 3, 2020. https://www.mdpi.com/2571-905X/3/2/8.

10. Dhanjoo Ghista, Applied Biomedical Engineering Mechanics (Boca Raton: CRC Press, 2008).

11. William Carvajal, Andrés Ríos, Ivis Echevarría, Miriam Martinez, Julio Miñoso, and Dialvis Rodríguez, “Body type and performance of elite Cuban baseball players,” MEDICc Review, April 2009, 11:2, 15–20.

12. Ryan L. Crotin, Charles M. Forsythe, Thomas Karakolis, and Shivam Bhan, “Physical size associations to offensive performance among major league leaders,” Journal of Strength and Conditioning Research, September 2014, 28:9, 2391–6.

13. Ryan L. Crotin, Christian M. Conforti, David J. Szymanski, and Jordan Oseguera, “Anthropometric Evaluation of First Round Draft Selections in Major League Baseball,” Journal of Strength and Conditioning Research, August 2023, 37:8, 1609–15.

14. Karl F. Orishimo, Ian J. Kremenic, Edward Modica Jr., Takumi Fukunaga, Malachy P. McHugh, and Srina Bharam, “Lower extremity kinematic and kinetic factors associated with bat speed at ball contact during the baseball swing,” Sports Biomechanics, December 2024, 23:12, 3406–17.

15. Hirotaka Nakashima, Gen Horiuchi, Arata Kimura, and Shinji Sakurai, “Acceptable range of timing error at bat-ball impact in baseball depends on the bat swing path,” Frontiers in Sports and Active Living, March 2025. https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2025.1557145/full.