Hardball Times came out with the opposite perspective: “No matter how long a hitter lasts or how many home runs he hits, we still don’t see any signs of a second-half decline.”4 However, the list of caveats to their analysis was almost as long as their analysis, which might lead to some skepticism.

We hope to put this subject to rest with some clear assumptions and a careful consideration from multiple perspectives.

WHAT IS A HOME RUN DERBY CURSE?

The goal of this analysis is to determine if the claim of a Home Run Derby curse is borne out by the performance of the players who participated. In order to do so, we need to determine how the idea of a Home Run Derby Curse should be interpreted statistically.

Interpretation 1

A player who participates in the Home Run Derby experiences a decrease in offensive and power hitting statistics in the second half, as compared to the first half of that season.

Interpretation 2

A player who participates in the Home Run Derby experiences a decrease in offensive and power hitting statistics in the second half, as compared to his usual production.

Behind the first interpretation is the assumption that a player would have continued to perform at the same level for the rest of the season had he not participated in the Derby. There is certainly some reason to believe that this is true—the player is clearly capable of performing at this level, having done so for half of a season. However, if this level is substantially above his typical level, it may be unreasonable to expect this to continue for the full 162 games. So it seems that this interpretation would tend to predict for the second half a level of performance that is higher than one should reasonably expect.

Behind the second interpretation is the assumption that a player’s career statistics are more indicative of his likely performance than is his first half of the season. Players selected to participate in the Derby are those leading the league in power hitting in the first half of the season and so are, for all except the best of players, performing at a level above their average statistics. Similarly, participants in the Derby are often having an excellent season at the peak of their careers, so a somewhat higher level of performance is to be expected again in the second half of the season. So it seems that this interpretation would tend to predict a level of performance in the second half that is lower than one should reasonably expect.

Neither interpretation is perfect, so we will consider both comparisons, looking at the difference between the post-Derby statistics and pre-Derby statistics, and then at the post-Derby statistics and the players’ usual statistics. In addition, we will consider a third comparison, where we will build a comparable dataset to estimate the expected regression to the mean and to see if a similar effect can be found in a dataset where the actual participation in the Derby is not present as a variable.

ANALYSIS 1: ON ALL PARTICIPANTS IN THE HOME RUN DERBY

In our first pass through the data, for each player who ever participated in the Home Run Derby, we collected all of his statistics for all seasons, separating any seasons where he participated in the Home Run Derby from any seasons where he did not participate. We restricted the seasons to those where the player reached a total of 502 plate appearances, in order to exclude any unusual averages for a player. The total number of player-seasons in the data is 1,111 (up to and including the 2009 season), 192 of which were seasons where a player participated in the Derby. There were six player-seasons where a player participated in the Derby and did not reach 502 plate appearances, and so those were excluded. This number is small enough to give some indication that participation in the Derby may not be linked to injury in the second half, though the number of occurrences of this is too small to allow us to perform any statistical inference process.

In order to simplify the analysis, we have focused on two offensive statistics: OPS and the percentage of plate appearances that were home runs. We found similar results with other statistics, so the analysis does not depend substantially on this choice. Note that these players averaged 10 to 15 fewer games played after the All-Star Break than before (due to its timing in the schedule more than their own playing time), so only statistics that are computed per at-bat, per plate appearance, or per game would make sense in these comparisons.

Comparison 1.1: Pre-Derby to Post-Derby, for Seasons Where Player Did Participate

Clearly, there is a significant overall drop-off in production for those players who participated in the Derby; both decreases are statistically significant (OPS, P < 10-5, HR %, P < 10-6). This difference, essentially, is the origin of the idea of a Home Run Derby curse; however, some decrease should be expected, as noted above.

Comparison 1.2: First Half to Second Half, for Seasons Where Player Did Not Participate

Both of these differences are not statistically significant, so, in a typical season, these players perform at about the same level after the All-Star Break as they do before. However, these levels are substantially lower than the level they perform at in seasons where they are selected to the Derby, which is also to be expected, since they were not among the league leaders in power hitting when the Derby participants were invited.

Comparison 1.3: First Half to Second Half, All Seasons

Again, we see essentially no change; the overall levels are slightly higher since they include more of these players’ best seasons. However, the important comparison to make here is between the performance after the Home Run Derby and these two half-seasons: post-Derby performance is closer to pre-Derby performance than it is to these same players’ average performance:

Comparison 1.4: Post-Derby Participation versus Pre-Derby and versus Typical Season

Note: It may appear that differences do not add up exactly due to round-off effects.

The differences in the second and third columns are clearly statistically significant (versus first-half OPS: P < 10-8 and HR %: P < 10-10; versus second-half OPS: P < 10-5 and HR %: P <10-7; first column is from comparison 1.1), so the players’ performance has declined somewhat from pre-Derby performance but is still superior to their own average performance. This leads us to believe that the “second-half slump” could be simply due to a regression to their mean.

In order to test this, it makes sense to restrict the dataset to players whose performance in seasons where they participate in the Derby is closer to their average performance—that is, to restrict the dataset to the top players. If there is less of a drop-off among the top players, then regression to the mean is a likely explanation. So we considered the same comparisons with players who participated in the Derby more than once; players selected more than once have higher average statistics, and so we would expect a smaller drop-off if regression to the mean is the best explanation.

ANALYSIS 2: ON REPEAT PARTICIPANTS IN THE HOME RUN DERBY

Here, we make the same comparisons using the same statistics on the smaller data set of players who participated in the Home Run Derby more than once.

Comparison 2.1: Pre-Derby to Post-Derby, for Seasons Where Player Did Participate

Again, these differences are statistically significant (OPS: P < .01, and HR %: P < .03), but the differences are much smaller than in the full dataset. The postDerby values are statistically significantly better than the values for all participants, and pre-Derby OPS is nearly so (OPS, pre: .05 < P < .06; HR %, pre: 0.25 < P < 0.30; OPS, post: P < .001; HR %, post: P <.04), so the assumption that repeat participation picks out the better players is generally supported by these values.

Comparison 2.2: Pre-Derby to Post-Derby, for Seasons Where Player Did Not Participate

As in the first section, these differences are not statistically significant, so their performance is similar from first half to second half in seasons where they did not participate.

Comparison 2.3: Pre-Derby to Post-Derby, All Seasons

Again, these differences are not statistically significant; in fact, they are almost indistinguishable.

Comparison 2.4: Post-Derby Participation versus Pre-Derby and versus Typical Season

Note: It may appear that differences do not add up exactly due to round-off effects.

Here we see, as anticipated, a smaller difference between the pre-Derby and post-Derby statistics than we saw in the full data set, and a difference that is very similar to what we saw in the full data set when compared to their typical season statistics. All of these differences are statistically significant (versus first-half OPS: P < .001 and HR %: P < .0001; versus secondhalf OPS: P < .001 and HR %: P < .0001; 1st column is from comparison 2.1).

In this dataset, however, there was one other statistical measure that provided an additional insight. Here, we consider the BABIP (batting average on balls in play). Most hitters, and most pitchers (measured against) have a long-term batting average of about .300 on balls put in play (that is. excluding strikeouts and home runs), and any significant deviation from this is most likely an indication of good or bad luck. In comparison 2.1, there was a notable decrease in BABIP (from .308 to .301) in this dataset, so almost half of the drop-off in OPS from the first half to the second half can be attributed to a decrease in luck at the plate (.014 of the .032—the .007 difference is doubled because BABIP will contribute to both OPS and SLG). If we remove the entire .014 from the OPS, the difference in OPS in comparison 1.1 is no longer statistically significant. The difference in HR percentage remains, however, since home runs do not contribute in any way to BABIP. None of the other data sets have a BABIP difference bigger than .003.

This second analysis provides some indication that the differences we saw in the first analysis are a simple regression to a mean: In players whose mean is closer to the league lead, we have noticeably less decline from the first half to the second half in years when they participated in the Home Run Derby.

ANALYSIS 3: ON COMPARABLE SECOND-HALF STATISTICS

A third approach would be to try to build a dataset that removes the variable of actually participating in the Home Run Derby. Participation in the Home Run Derby is based on first-half statistics, so we decided to start with seasons with comparable second-half statistics and then compare these to the first half of the same season. If a drop-off occurs from the second half of these seasons to the first half, it cannot be due to any kind of curse, since the effect comes before the supposed cause.

To build this dataset, we looked at each player who participated in a Derby. We replaced the seasons that the player participated in the Derby with comparable seasons as follows:

If a player was selected to participate in the Derby in a season which had his best first-half OPS and HR-percentage statistics, then we replaced that season with the season where he had his best second-half OPS and HR-percentage statistics. For example, Danny Tartabull was selected to the Derby in 1991, in a season where his OPS was 14.0 percent above the average of his OPS values in the first half of his nine full seasons in professional baseball through 1990, and his HR percentage was 50.2 percent above his average, which we added to get a total “first-half score” of 64.2 for this season. This was the best first half score of his career. However, his second-half statistics in 1991 were not as good: He was 11.5 percent above his second-half average in OPS but 11.4 percent below average in HR percentage for a second-half score of 0.1. In 1987, he had a second half that was 11.8 percent above average in OPS and 29.2 percent above in HR percentage, giving a second-half score of 41.0, which was the best second-half score of his career, so we replaced his 1991 season with his 1987 season in this new dataset.

Similarly, Joe Carter participated in 1991, 1992 and 1996, which had his best, fifth-best, and second-best first-half scores respectively, and so we replaced these with 1989, 1994, and 1986, which were his best, second-best, and fifth-best second-half scores. In this process, we did not consider any seasons before 1985, since that was the first season the Derby took place, and again we only considered seasons where the player had a minimum of 450 plate appearances. In some cases, the season selected was the same as the one where the player participated in the Derby, if the rankings were the same.

This dataset should give us an effective estimate of the amount of regression to the mean we should expect after the Home Run Derby.

Comparison 3.1: Second Half to First Half, for Seasons Comparable to Those Where Player Did Participate, Using All Derby Participants

Comparison 3.2: Home Run Derby Curse versus Estimated Regression to the Mean

Note: It may appear that differences do not add up exactly due to round-off effects.

The differences here are essentially identical to those we saw in comparison 1.1—in fact, the averages in comparison 3.1 are almost identical to those we saw in comparison 1.1. In other words, the statistics we saw in the Home Run Derby curse are essentially the same as when there was no Home Run Derby played. This provides very strong evidence that the Home Run Derby curse is simply an expected statistical variation.

The comparisons to their typical season will also be essentially identical, since the values in comparison 3.1 are so close to those in comparison 1.1.

CONCLUSION

Home Run Derby curse, fact or fiction? We have no choice but to conclude that it’s fiction. If we consider all the ways that the statistics should behave if there is no curse, we find that they consistently match that model. Certainly, some players will have a decline in power-hitting statistics from the first half of the season to the second after participating in the Derby, but it is clear from the analysis that this would have occurred for those players regardless of whether they chose to participate or not.

JOSEPH McCOLLUM is assistant professor of quantitative business analysis in the school of business, Siena College, where he teaches math primarily to future teachers. He has published in pure mathematics and random-walk theory.

MARCUS JAICLIN, assistant professor of mathematics at Westfield State University, is coauthoring a book on the application of statistics to measure performance in sports and wellness.

Notes

1 Mark Feinsand, “A-Rod to Skip HR Derby, Claims It Tampers with Swing,” New York Daily News, 30 June 2008.

2 Dave Cameron, “The Mysterious Curse of the Home Run Derby,” Wall Street Journal, 13 July 2009.

3 “The HR Derby Curse Is Real!” mlb.com, https://fantasy411.mlblogs.com/archives/2008/07/the_hr_derby_curse_ is_real.html

4 Derek Carty, “Do Hitters Decline After the Home Run Derby?” Hardball Times, 13 July 2009.

Asking himself these questions,1 Voros McCracken, a paralegal who participated in a Rotisserie league in his spare time, went on to develop the concept of DIPS, defense-independent pitching statistics. Posting to the Usenet group rec.sports.baseball on November 18, 1999, almost eleven years ago to the day we are writing this, he described the “pitching evaluation tool” he was kicking around in his head and asked for some feedback. “I call it ‘Defensive Independent Pitching’ and what it does is evaluate a pitcher base[d] strictly on the statistics his defense has no ability to affect.”2

EARLY PITCHING STATISTICS

The early history of pitching and pitching statistics has been told often. Alan Schwarz in The Numbers Game does the job well.3 Originally, the pitcher’s job was to serve the ball over the plate so the batter could hit it. The idea that his job was to make the ball hard to hit was slow to take hold. In his biographical article on Jim Creighton, “the greatest pitcher of his day,” John Thorn notes that

the 1850s did produce some pitchers who tried to deceive batters with “headwork”—which meant changing arcs and speeds, and sometimes bowling wide ones until the frustrated batter lunged at a pitch. (The latter tactic produced such incredible, documented pitch totals as that in the second Atlantic–Excelsior game of 1860, when the Atlantics’ Matty O’Brien threw 325 pitches in nine innings, Creighton 280 in seven.) On balance, however, the pioneer pitcher and batter were collaborators in putting the ball in play rather than the mortal adversaries they have been ever since. Creighton added an illegal but imperceptible wrist snap to his swooping low release.4

In 1912, when the practice of pulling starting pitchers had begun to grow more common, John Heydler, National League president, dropped “earned runs per game” in favor of a new statistic, “earned-run average,” which joined G, IP, W, L, win percentage, SO, BB, and H in the list of pitching stats that, a century later, are still the most familiar and mainstream, the ones most likely to appear next to a pitcher’s name on the scoreboard.

WINS, LOSSES, AND ERA QUESTIONED

When wins, losses, and ERA became the primary measuring stick for pitchers, observers started to notice how much variation from year to year there was in the top-ten lists in wins and ERA.

As early as 1944, Ted Oliver, in his self-published Kings of the Mound: A Pitcher’s Rating Manual, described a formula, Weighted Pitcher’s Rating, used to assess the pitcher’s wins and losses relative to his team’s wins and losses.5

In the late 1970s, Bill James started tracking pitcher run support.

In 1992, Michael Wolverton, a Stanford computer-science graduate, developed SNWL, support-neutral won–lost. SNWL assigns to a pitcher a number, a fraction of a win or a loss, that’s calculated from his innings pitched and runs allowed. Around this time, in the 1990s, Keith Woolner, then a software developer with Oracle, invented Composite Opponent Pitcher rating, which tracked a pitcher’s “strength of schedule,” or the difficulty of his opponents.6

But none of these metrics addressed the real issue involved in the effort to evaluate pitchers solely on their wins and losses. The outcome of the game is the product of runs scored as well as of runs prevented. Let’s assume that 50 percent of a game’s outcome is run prevention. How much of that is the pitcher’s responsibility?

Doesn’t ERA solve all the problems that this question poses? Not entirely. Here’s Michael Wolverton, writing at Baseball Prospectus, on the limitations of ERA:7

I’ve done it! I’ve solved the problem of removing the corrupting influence of fielding on pitchers’ runs allowed. We simply pay a sportswriter to sit in the press box, munch Cheetos, and decide which safeties would have been outs with normal fielding effort. Whenever one of these “errors” occurs, we reconstruct the inning—not the game, mind you, just the inning—pretending as if the error never happened. Count up the runs that would have scored in this hypothetical reconstructed inning, and you have a revised run total for the pitcher. Things get a lot more complicated for relievers and team totals, and we’ll broaden the ‘plays that should have been made’ definition a little bit, but you get the idea.

The problem is that the distinction between an earned run and an unearned run is based on errors and passed balls, which are largely subjective decisions made by official scorers. Moreover, if an error is made when there are two outs and then the pitcher goes on to put runners on base and give up runs, all the runs are counted as unearned. Then there are routine double plays not turned and missed plays that an average fielder might have made but that aren’t scored as errors—even though the fielders are at fault, all the runs the fielders give up are charged to the pitcher. Consider also that, after a pitcher has left a game, his ERA will still rise if a reliever allows the inherited runners to score, while the reliever’s ERA remains unscathed.

OTHER STATISTICS

In the original Rotisserie league of the 1980s, batters were tracked for batting average, home runs, RBIs, and stolen bases. Pitchers were tracked by wins, ERA, saves, and—the innovation of Dan Okrent, the godfather of fantasy baseball—a baserunners-allowed ratio, which we now know as WHIP (walks plus hits per inning pitched).8

Component ERA (ERC) was invented by Bill James and introduced in 2000 in Stats All-Time Major League Handbook.9 To get ERC, first you have to calculate a Pitcher’s Total Base Estimate (PTB), which reflects a pitcher’s hits allowed, home runs allowed, unintentional walks, and hit batsmen. The PTB is then figured into a formula that includes walks, hits, hit batsmen, batters faced, and innings pitched.10

WHIP and ERC for individual pitchers are more consistent—they vary less from year to year—than do ERA or winning percentage but still have built into them the assumption that hits are entirely the pitcher’s responsibility.

VOROS McCRACKEN

Voros McCracken joined a Rotisserie league in 1999 and began following sabermetric websites, where it was generally recognized that ERA was not a pure measure of pitching but reflected to some extent the fielding behind the pitcher. McCracken was frustrated that sabermetricians mostly threw up their hands at the prospect of trying to distinguish pitching effectiveness from fielding. “This seemed like a stupid approach to the problem, to give up,” McCracken said, and he set out to solve the problem logically.

He divided pitching stats into two categories: events (singles, doubles, triples, sacrifice flies, groundball and fly-ball outs) that the defense behind him contributed to and those events (strikeouts, walks, home runs, hit by pitches) that it did not. Using Excel software and applying some of what he learned in a statistics course at Butler, he went to work analyzing the data.11

Stripping the pitcher’s performance down into its component parts—strikeouts, walks, home runs, and hits—McCracken discovered that there was a high year-to-year correlation between a pitcher’s strikeout rates (r = 0.792) and walk rates (r = 0.681), medium correlation for home-run rates (r = 0.505), and very low correlation (r = 0.153) in BABIP (batting average on balls in play). (McCracken was using the symbol $H instead of BABIP; what we now call BABIP has been known as HPBP [hits per ball in play] and in-play average [IPAvg] as well as $H. In this article we will use the acronym BABIP.)

Individual pitchers might jump from top to bottom of the league in BABIP in consecutive years, or from bottom to top. The graph below illustrates the volatility of BABIP for individual pitchers. While for the whole league BABIP remained close to constant, rising and falling only gently over the course of Nolan Ryan’s career, his personal BABIP was constantly spiking and plummeting. On the whole, his BABIP was below league average—some years, dramatically below it—but in eight different seasons, distributed widely across his 27-year MLB career, he was either at or above (though, when above, usually only slightly) the league average.

Graph 1. Nolan Ryan’s BABIP versus MLB BABIP

The seasons McCracken looked at specifically for pitcher performance were 1998 and 1999. In broad terms: McCracken’s DIPS calculations were designed to determine what a pitcher’s stats would have been if he pitched in an average ballpark with an average defense and, most important, had average luck when it came to balls in play.12 The original formulas McCracken used for balls kept out of play and hits per ball in play were

• Balls kept out of play = (HR + BB + HBP + SO) / TBF
• Hits per ball in play = (H – HR) / (Outs + H – SO – HR)

He found the pitcher had control over the balls kept out of play but not over the hits per ball in play.13 He concluded that “you can better predict a pitcher’s hits per balls in play from the rate of the rest of the pitcher’s team than from the pitcher’s own rate,” which suggests that the hits surrendered by a pitcher may be more a reflection of team defense and park than of pitching ability.14

McCracken posted his query on this subject to the Usenet group in 1999 and fourteen months later, in January 2001, found a receptive audience for his article “Pitchers and Defense: How Much Control Do Hurlers Have?” which was posted online at Baseball Prospectus.15 Shortly thereafter, Rob Neyer of ESPN briefly discussed it.16 According to McCracken, “All hell broke loose,” as he received 1,700 e-mails in two days,17 from sabermetricians who took varying degrees of exception to McCracken’s assertion that “there is little if any difference among major league pitchers in their ability to prevent hits on balls in play.”18 Craig R. Wright and Bill James wrote in to Neyer with reservations about McCracken’s theory,19 beginning the long and ongoing discussion within the sabermetric community over whether pitchers have control over hits on balls in play and, if they do, how much. James changed his mind after further research. From the 2001 edition of The New Bill James Historical Abstract:

1. Like most things, McCracken’s argument can be taken too literally. A pitcher does have some input into the hits/innings ratio behind him, other than that which is reflected in the homerun and strikeout column.
2. With that qualification, I am quite certain that McCracken is correct.
3. This knowledge is significant, very useful.
4. I feel stupid for not having realized it 30 years ago. 20

McCracken’s work caught the attention of Paul DePodesta, assistant general manager of the Oakland A’s. After reading the article, “the first thing I thought of,” he said, “was Chad Bradford.” Bradford, a submarinestyle right-handed pitcher, was posting ERAs below

• for the AAA affiliate for the Chicago White His unorthodox delivery led traditional scouts to believe he was never going to be an effective bigleague pitcher. Bradford’s walk rate, strikeout rate, and home runs allowed made his statistics look even better than his microscopic ERAs. General manager Billy Beane pulled off a steal of a trade to acquire Bradford, who would become one of the most dominant setup men for the A’s in the period 2001–4.21

Meanwhile, McCracken, who finished in first place in his fantasy league for three years, was sifting through his inbox in August 2002 when he noticed a message from the Boston Red Sox. “Would you be interested in working for us?”22

STUDIES PROVING McCRACKEN WRONG

McCracken’s work got people thinking about pitching performance with fielding factored out. The thinking manifested itself in forms ranging from insults directed at McCracken’s work and sanity to thoughtful and thorough research by those looking to prove or disprove his idea. The two leading responses to McCracken’s work came in July 2003 from Tom Tippett at Diamond Mind Baseball and in February 2004 from Mitchel Lichtman at Baseball Think Factory.

Part of what most made Tom Tippett’s work compelling was that he drew his data from a much longer period, 1913 through 2002, than did McCracken, who initially looked at only two seasons, 1998 and 1999. Tippett drew three main conclusions.

• Pitchers do influence BABIP.
• A pitcher shows statistically significant BABIP consistency across the length of his career.
• Small influence over BABIP (much smaller than influence over strikeouts and walks) is still significant because such a large percentage of balls are put into play.

Tippett observed that McCracken may have been misled by the bad BABIP numbers that Greg Maddux, Randy Johnson, and Pedro Martinez had in the 1999 season. Most seasons they posted BABIP numbers lower (better) than the league average. Also of note: Six of the top 35 pitchers in career BABIP were knuckleballers (Charlie Hough was the best overall), and soft-tossing lefties like Jamie Moyer had low BABIPs despite low strikeout rates. (In Moyer’s case, he made up for the low strikeout rate with an exceptionally low walk rate.) Successful pitchers with low strikeout rates and high BABIPs—Tommy John is an example—led Tippett to suggest further research on the ability of pitchers to induce double-play groundballs.23

Mitchel Lichtman’s sample was from the twelve-year period 1992–2003. In his article on DIPS at Baseball Think Factory, he analyzed different kinds of BIP (balls in play) and defined six categories:

• infield line drives
• outfield line drives
• infield pop flies
• outfield pop flies
• outfield fly balls
• non-bunt groundballs

He calculated the percentage of BIP that each of these categories represented, the BABIP for each category, and the year-to-year correlations for each of those. Lichtman found that, while McCracken was correct in that a pitcher does not have much control over his overall BABIP, he does have considerable control over individual components such as groundball and fly-ball rates. Additionally, he found that park factor and defense exert considerable influence over year-to-year correlations.24

Further work by various writers at Baseball Prospectus led to additional conclusions:25

• Major league pitchers have a better BABIP than minor league pitchers who never made it to the big leagues.
• The ability to induce infield pop-ups is a repeatable skill by major league pitchers.
• Pitchers have considerable control over whether the ball is hit on the ground or in the air. Groundballs are significantly less likely to go for extra-base hits but do go through more often for singles.
• Pitchers have less control (as opposed to no control) over hits than over walks, strikeouts, and home runs.
• Run average (RA), simply RA = R/IP * 9, has a greater yearto-year correlation than ERA.

Additionally, Erik Allen, Arvin Hsu, and Tom Tango used regression analysis to break down the responsibility of what determines the outcome of a batted ball:26

• Luck, 44 percent
• Pitcher, 28 percent
• Fielding, 17 percent
• Park, 11 percent

Tom Tango further elaborated this on his website, where he discussed the concept of DRS, the defensive responsibility spectrum, which lists the categories of recorded events in a baseball game.27 The events on the far left are 100 percent the responsibility of the pitcher. Events on the far right are 100 percent the responsibility of the fielders. Everything else is listed in between.

Defensive Responsibility Spectrum
HBP, balk, pickoff, SO, BB, HR, WP, SB, CS, 2B, 3B, 1B, batting outs, PB, running outs

Bill James too has begun to look at pitching in a new light. At one time he was resigned to thinking that the predictability of pitching performance was low. In

The Bill James Handbook 2010, his revised view of the matter involves the difference between what he calls elemental stats and summary stats. Elemental stats for pitchers include strikeouts, innings, and walks. These are the components that make up summary stats such as ERA. Because it’s complex, reflecting several elemental stats as well as fielding and park factor, ERA is, like a pitcher’s won–lost record, hard to predict. Accurate prediction of a pitcher’s elemental stats increases the accuracy of his predicted summary stats.28 The Hardball Times has run several studies using batted-ball data from Baseball Info Solutions. Several important conclusions were drawn by David Gassko in “Do Players Control Batted Balls? (Part Two)” in The Hardball Times 2007 Annual. Gassko concluded that pitchers show some consistency, though not much, in home runs allowed per outfield fly ball allowed. THT studies suggested that outfield fly balls allowed are more consistent year to year than are home runs allowed per outfield fly balls allowed.29

NEW METRICS

Since McCracken’s article in 2001, many metrics have been developed in an effort to better evaluate a pitcher’s performance and to project his future performance. How is an earned run truly “earned” against a pitcher? The thought process of sabermetricians on this subject had changed. Runs, Dayn Perry explains, “are more like molecules than atoms. They’re compounds made up of singles, doubles, triples, home runs, walks, errors, stolen bases, baserunning, sacrifices, balks, hit batsmen, strikes, balls, fouls into the stands, and so on. To evaluate how a pitcher is doing his job, we need to focus on how well he masters the game at an atomic level.”30

Defense-independent pitching statistics can be divided into two basic categories: those that use only what are widely considered to be entirely defenseindependent statistics (strikeouts, walks, hit batters, balks) and those that include batted-ball data (groundball and fly-ball rates, and so on.). The second group claims a preponderance of the newer metrics, because sabermetricians increasingly agree that pitchers have some control over BABIP, although how much is still a point of contention.

Batted-Ball Data Not Required

McCracken’s DIPS formulas and FIP (fieldingindependent pitching), a stat based on Bill James’s Component ERA, are the only widely used DIPS statistics that do not require batted-ball data (groundballs, fly balls, and line drives).

McCracken’s DIPS ERA (Version 1.0). The only individualplayer stats that McCracken used to calculate DIPS ERA were batters faced, home runs, walks, intentional walks, strikeouts, and hit batsmen. His methodology for arriving at DIPS ERA was long and complicated. He took the raw total of walks and divided it by BFP – HBP – IBB to get a new walk total. He took the strikeouts and divided them by BFP – HBP – BB. The home-run total was divided by BFP – HBP – TBB – SO. McCracken then used park factor and league (American or National) adjustments to arrive at new (DIPS) walk, strikeout, and home-run totals. He used league average rates for singles, doubles, triples, and innings pitched. Again, McCracken assumes that the pitcher had average luck, pitched in an average park, and had an average defense. Using Jim Furtado’s Extrapolated Runs formula shown below, which applies certain values to specific events, a number of expected runs (XR) is calculated from the adjusted values for 1B, 2B, 3B, HR, TBB, HBP, and total hits and from the unchanged values for batters faced:

(1B * .50) + (2B * .72) + (3B * 1.04) + (HR * 1.44) + ((TBB + HBP) * .33) – ((BFP – H – TBB – HBP) * .098)

This XR total is multiplied by 0.9297 (because, in McCracken’s data, 92.97 percent of all runs were earned) to obtain DIPS ER. Like the standard ERA formula, DIPS ER is divided by the DIPS IP and multiplied by 9 to obtain ERA—in this case, DIPS ERA.31

DIPS ERA, Version 2.0. In January 2002, Hardball Times ran McCracken’s article “DIPS Version 2.0.”32 He made some improvements to his original formula, slightly simplifying it and accounting for the small differences he found in pitcher BABIP among specific groups of pitchers: knuckleballers and left-handers. The revised formula required the same elemental stats—batters faced, home runs, walks, intentional walks, strikeouts, and hit batsmen. It also required park factors but not league averages; McCracken simply took the league-average values and replaced them with constants. In addition to adjusting for strikeouts and home runs, he made BABIP adjustments for knuckleball pitchers and left-handers—he discovered that knuckleball pitchers had a lower BABIP by .010 and that the average BABIP of left-handed pitchers was lower than that of right-handers by .002.33 The difference in pitcher handedness was statistically significant, but McCracken was not sure why it was important.34 He used a different formula to arrive at DIPS ER (dER), dropping the XR formula entirely and creating his own new formula:35

dER = (dH – dHR) * .49674 + dHR * 1.294375 + (dBB – dIBB) * .3325 + dIBB * .0864336 + dSO * (– .084691) + dHP * .3077 + (BFP – dHP – dBB – dSO – dH) * (– .082927)

DIPS 2.0 is the main McCracken formula that is still used to compare the effectiveness of DIPS against other pitching metrics that will be discussed later in this article. The formula is still posted on ESPN.com, without the adjustments for parks, knuckleball pitchers, and lefthanded pitchers.36 McCracken also investigated the ratio of groundballs to fly balls, worried that the distinction between a fly ball and a line drive is imprecise and subjective, and expressed the hope that more data on batted-ball types would become readily available.37

DICE (Defense-Independent Component ERA) and FieldingIndependent Pitching (FIP). After DIPS ERA, the first improvement on ERA in the defense-independent direction was DICE, or defense-independent component ERA, introduced by Clay Dreslough at Baseball Mogul in 2000. It was based on Bill James’s ERC (component ERA) but was modified to leave out hits. The formula

3 + (3 * (BB + HBP) + 13 * HR – 2 * K) / IP

was designed for ease of use and at the time was one of the best predictors of next-year performance available.38 For whatever reason, this formula never caught on and would be reintroduced a couple of years later.

Currently, the most widely used metric that involves exclusively defense-independent statistics is FIP, fielding-independent pitching. Popularized by Tom Tango, FIP is similar to DICE but has taken hold in the sabermetric community and is more widely used.39 Formulas for FIP vary slightly. The version

C + (13 * HR + 3 * BB – 2 * K) / IP

is common. (Sometimes HBP are added to walks, and sometimes intentional walks are subtracted from walks.) The constant C, usually in the vicinity of 3.20, is used to adjust FIP to the league average ERA, making the final number more recognizable and accessible at a glance. In some cases, the constant is adjusted differently; for instance, at some websites the constant is higher for AL pitchers than for NL pitchers, since AL pitchers, who face designated hitters, typically have higher ERAs. Some versions of FIP are scaled in context with RA as opposed to ERA.

Batted-Ball Data Required

Batted-ball type has been found to have even more predictive value than FIP. Further research has suggested that, although a pitcher has significant control over walks, hit batsmen, and strikeouts, his control over home runs is more volatile and is highly influenced by his home-park factor.

tRA. Like DIPS ERA, tRA requires not just one single formula but a lengthy step-by-step process. Created by Matthew Carruth and Graham MacAree at StatCorner.com, tRA involves every action a pitcher is responsible for—groundballs, popups, outfield fly balls, line drives, home runs, strikeouts, walks, and hit by pitches. The idea is that, for every one of these events, there is an expected-out value and an expected-run value. Here are expected-run and expected-out values for 2008:41

Table 1

What do the numbers in table 1 mean? The out value is the probability of an out occurring in a given situation. On a walk, hit by pitch, or home run, the out value is zero because an out never occurs. On a strikeout, the out value is 1, because a strikeout always results in an out (except in those rare cases when the runner takes first when strike three is a passed ball). Obviously, the probability of getting out on an infield fly ball is high, and the batted ball that it’s hardest to make an out on is the line drive.

The run value is based on the run expectancy matrix, or 24-states matrix. The run expectancy matrix is a chart, 8-by-3, that shows the expected (average) number of runs that are scored in an inning during a given state (e.g., runners on first and second, one out). The given state is made up of two parts: the number of outs, and which bases are occupied.42

Table 2

After this matrix is generated, the difference in runs can be applied using this formula:

play_run_value = runs_scored + (run_expectancy_ after – run_expectancy_before)

The run value in the chart would be plugged in for “play_run_value” in the formula. Strikeouts and infield fly balls actually have a negative run value, since they decrease a team’s chances of scoring. Conversely, home runs have an expected run value greater than 1, not only because a home run will drive in any runners on base but also because, even on a solo home run, it is still possible that more runs can score in the inning, as the batter who hit the home run didn’t make an out. After park factors are applied, each of these numbers will be multiplied by the pitcher’s individual frequencies of each statistic in table 1 (strikeouts, walks, hit by pitch, line drives, groundballs, outfield fly balls, infield fly balls, home runs) and by the number of total batters he faced, and the result will be expected runs (in a neutral park with an average defense). From the outs table above, his expected outs can also be determined. These two numbers are then entered into the following formula to get tRA:43

tRA = expected_runs / expected_outs * 27

The tRA stat is by far the most complicated pitching stat to compute. It requires examination of playby-play data for every single player and constant assessment of the 24-states matrix. Its value should not be ignored, however, as an in-season prediction tool, as tRA has proven to help predict ERA in-season. In its classical form, the tRA value is keyed to the runsallowed scale, although it is often converted to the ERA scale.44

LIPS, Luck-Independent Pitching Statistics. David Gassko in 2005 introduced LIPS, or luck-independent pitching statistics, as DIPS 3.0. Year to year, LIPS correlates better with ERA than FIP does. Gassko uses walks, strikeouts, hit batsmen, infield flies, outfield flies, and ground balls, as opposed to McCracken’s walks, strikeouts, hit batsmen, and home runs.45

Since then, Gassko has refined the metric in an effort to make it entirely independent of defense, park, and luck. He replaces a pitcher’s line-drive rate (known to be random) with the league-average linedrive rate and adjusts the pitcher’s other batted-ball rates (known to be consistent for an individual pitcher) accordingly. These transformed batted-ball rates get multiplied by the league-average outcome rates for each possible outcome (single, double, etc.). “If an average NL pitcher allows 0.21 singles per ground ball,” Gassko writes, “we calculate that [a pitcher who is expected to give up 42 groundballs] will allow 0.21*42 = 8.8 ground ball singles.” This process is repeated for each batted-ball type and each pitching outcome to fill a complete line of result-based statistics (single, double, triple, home run, base on error).

All these numbers, along with strikeouts, walks, and hit by pitches, get park-adjusted, and the resulting values get inputted into David Smyth’s BaseRuns formula,46 outputting an expected runs-allowed value. This number is then adjusted back to the original biased park factors in order to have the final number represent the pitcher’s luck-independent ERA at his own park. Finally, Gassko uses groundball rates to estimate unearned runs, subtracting those from total LIPS runs allowed to give a true ERA.47

QERA, QuikERA. QERA, or QuikERA, was developed by Nate Silver, the inventor of the PECOTA preseason projections, at Baseball Prospectus in 2006. The formula

(2.69 – .66 * (GB / BIP) + 3.88 * (BB / PA) – 3.4 * (K / PA)) ^ 2

was designed to account for interdependent relationships between a pitcher’s groundball rate, walk rate, and strikeout rate. QuikERA, according to Silver,

estimates what a pitcher’s ERA should be based solely on his strikeout rate, walk rate, and GB/FB ratio. These three components—K rate, BB rate, GB/FB—stabilize very quickly, and they have the strongest predictive relationship with a pitcher’s ERA going forward. What’s more, they are not very dependent on park effects, allowing us to make reasonable comparisons of pitchers across different teams note that everything ends up expressed in terms of percentages: strikeouts per opponent plate appearance, walks per opponent plate appearance, and groundballs as a percentage of all balls hit into play.48

The intent of this formula was to adjust for the issues prevalent in FIP and xFIP. Another important feature of this formula is that it takes the ratio of walks and strikeouts per plate appearance instead of per inning. Why is this important? Think about it this way. The number of innings a pitcher pitches is equal to the number of outs times three. The innings a pitcher pitches might be longer innings because of poor defense. QERA allows us to see a pitcher’s true rates of strikeouts and walks. McCracken understood this as well, but Silver, with QERA, spells out this concept more clearly than he did.

SIERA, Skill Interactive ERA. In a five-part series at Baseball Prospectus in February 2010, Matt Swartz and Eric Seidman introduced SIERA as an improvement over QERA. The formula for SIERA is

6.145 – 16.986 * (SO / PA) + 11.434 * (BB / PA) – 1.858 * ((GB – FB – PU) / PA) + 7.653 * ((SO / PA) ^ 2) +/– 6.664 * (((GB – FB – PU) / PA) ^ 2) + 10.130 * (SO/PA) * ((GB – FB – PU) / PA) – 5.195 * (BB / PA) * ((GB – FB – PU) / PA), where +/– is a negative sign when (GB – FB – PU) / PA is positive, and where +/– is a positive sign when (GB – FB – PU) / PA is negative.49

Why such a long formula? When they algebraically factored out all of the individual components of Silver’s QERA formula and analyzed the effect of each component, Swartz and Seidman discovered that, while there is an interdependent relationship between strikeout and groundball rates and between walk and groundball rates, there is no real interdependency between walks and strikeouts. They also changed all instances of GB/BIP to (GB – FB – PU) / PA, since GB/BIP was not considered a repeatable pitcher skill. When doing regression analysis to predict the next season’s ERA, they found that SIERA predicted the next season’s park-adjusted ERA better than did QERA, tRA, FIP, xFIP, or ERA. However, SIERA was not as strong as FIP or tRA at predicting in-season ERA changes, but it did better than QERA or xFIP. Also, the adjustments in SIERA proved to be much better estimates for some pitchers with extremely high rates of groundballs to total balls in play, such as Brandon Webb and Joel Pineiro, and for pitchers, such as Johan Santana, who strike out a lot of batters.50

LIMITATIONS

The biggest issue with DIPS statistics is the subjectivity in the batted-ball data. This is also a problem with some of the defensive metrics, such as UZR and Defensive Runs Saved, that rely on batted-ball metrics from either MLBAM or Baseball Info Solutions (BIS). What is the issue?

As Colin Wyers pointed out on Hardball Times and Baseball Prospectus, for the scorers who from their seats in the press box chart batted-ball data, he found “a modest correlation between the height of the press box and the line-drive rate reported.” This leads to some discrepancies, as Baseball Prospectus and Retrosheet use Gameday/MLBAM data, and FanGraphs uses BIS data. As of now, it is difficult to objectively define the difference between a fly ball and line drive or even between either of those and what BIS designates as “fliners.”51 BIS has tried to minimize the bias by randomly assigning their video scouts to different parks. At least two video scouts view the same ball. In 2009, they improved on their accuracy on all balls in play by adding objective batted-ball timer data, which is a measure of the interval between the time the ball leaves the bat and when it lands on the ground or in a fielder’s glove. The time intervals help the analyst make the distinctions between a fly ball, a fliner, and a line drive more objective.52

USES OF DIPS

The most widespread use of DIPS today is in the fantasy-league community, where in articles on sites such as FanGraphs.com pitchers are analyzed in terms of FIP, xFIP, and tRA more often than in terms of the more conventional metrics—ERA, wins, WHIP, and so on. DIPS tend to give fantasy-leaguers an edge over their competitors.

DIPS have caught on with some MLB players, including Zack Greinke and Brian Bannister of the Kansas City Royals. “My favorite [stat],” Greinke says, “besides facing individual batters, is FIP, which is kind of like walks to strikeouts and home runs given up. So I try to get ahead of the count without leaving it run down the middle in a person’s power zone, get ahead in the count. That helps me not walk guys, and then, when I get two strikes, I try to strike guys out. And that’s how I try to pitch, to keep my FIP as low as possible.”53

Bannister knew that his BABIP of .264 in 2007 was unusually low. “It’s tough,” he said,

because I’m a student of it, and all last year [2007] I was well aware I was among the league leaders in it. But what do you do? Just because you’re continuing to get outs, do you say, ‘Oh, this shouldn’t be happening’? I realize very well that I could regress to the mean One thing sabermetrics and statistics have allowed me to do is relax. I know the odds. I know percentages. I know that three out of every 10 batted balls should go for hits, and I deal with it. It’s helped me be a better player.54

ANALYSIS

DIPS are designed to separate out defense and, more important, luck from measures of pitching performance. Beyond the obvious, “luck” includes timing and the order of events in an inning. For example, if a pitcher’s results in one inning occur in this order— walk, strikeout, groundout, home run, strikeout—his runs allowed in the inning are different from an inning where the order is home run, strikeout, walk, strikeout, groundout. Even though the pitcher tallied the same results, the sequence changes his runs allowed from two in the first case to one in the second.55

Some of these metrics are simple and so userfriendly, like FIP and xFIP, which require only a few numbers and no park adjustments. QERA and SIERA are slightly more complicated but easy enough to calculate with a formula on an Excel sheet (and then making a park adjustment at the end for SIERA). Other metrics are more involved.

Some metrics paint a clearer picture of what is truly happening within a season, such as FIP, xFIP, and tRA. These are widely accepted for forecasting future ERA within a season and are frequently used by writers at such sites as Hardball Times and FanGraphs. LIPS and SIERA are more useful for preseason player predictions, for forecasting ERA for the upcoming season.

When McCracken released DIPS 2.0, he was “hoping this is the beginning of a discussion and not the end of it.”56 His most important achievement to the sabermetric community was to get fans and front offices to think differently about how to separate pitching from defense. It was not that he had a PhD in mathematics and could perform complex statistical analysis or that he was smarter than everyone else in the sabermetric community. It was that he calmly sought to answer a question that was important but deemed unanswerable. For what he was trying to do (gain an edge in his fantasy baseball league), he didn’t feel it was worthwhile to come up with another metric to reevaluate pitcher won–lost record. In the process, he surprised even himself by discovering the lack of year-to-year correlation in hits. ”I did everything,” he wrote, “within my power to come to a different conclusion than the one I did.”57

We don’t know what dimension of the game will be significantly elucidated by innovative statistical analysis next. Defense? Baserunning? Relief pitching? Clutch hitting? Who will discover it? Somebody trying to answer an “unanswerable” question, crunching numbers and perusing the likes of Hardball Times, FanGraphs, Baseball Prospectus, and, yes, even The Baseball Research Journal, looking to build on whatever work has already been done.

DAN BASCO is a graduate student and teaching assistant in the statistics department at the University of Akron.

MICHAEL DAVIES is a student at Sidwell Friends School in Washington, D.C.

Notes

1. Michael Lewis, Moneyball (New York: Norton, 2003), 237–38.
2. Alan Schwarz, The Numbers Game: Baseball’s Lifelong Fascination with Statistics (New York: Thomas Dunne Books, 2004), 201–11; sports.baseball, 18 November 1999, http://groups.google.com/group/rec.sport.baseball.analysis/msg/b450fe58c05a5a82
3. Schwarz, The Numbers Game, 14–18, 25–31.
4. John Thorn, “Jim Creighton,” Baseball Biography Project, http://bioproj.sabr.org/.
5. Gabriel Costa, Michael R. Huber, and John T. Saccoman, Practicing Sabermetrics: Putting the Science of Baseball Statistics to Work (Jefferson, N.C.: McFarland, 2009), 101–2.
6. Schwarz, The Numbers Game, 174-76.
7. Jonah Keri, , Baseball Between the Numbers: Why Everything You Know About the Game is Wrong (New York: Basic Books, 2006), 88.
8. Schwarz, The Numbers Game, 174–76.
9. Bill James, Don Zminda, and Neil Munro, Stats All-Time Major League Handbook (Skokie, : STATS Publishing, 2000).
10. Baseball Info Solutions and Bill James, Bill James Handbook 2010 (Skokie, Ill.: ACTA Sports, 2009), 498.

22. Schwarz, The Numbers Game, 210–11.
23. Voros McCracken, “Defense Independent Pitching Stats,” futilityinfielder.com/dips.html.
24. Schwarz, The Numbers Game, 211–12.
25. Voros McCracken, “Pitching and Defense: How Much Control Do Hurlers Have?” 23 January 2001, baseballprospectus.com/article.php? articleid=878.
26. Ibid.
27. Rob Neyer, ESPN.com, 31 January 2001, http://a.espncdn.com/mlb/s/2001/0115/1017090.html.
28. Schwarz, The Numbers Game, 213.
29. McCracken, “Pitching and Defense: How Much Control Do Hurlers Have?”
30. Neyer, com, 31 January 2001.
31. Quoted by Lewis in Moneyball, 239–40.
32. Ibid., 241–43.
33. Schwarz, The Numbers Game, 213.
34. Tom “Can Pitchers Prevent Hits on Balls in Play?” 21 July 2003, Diamond Mind, http://www.diamond-mind.com/.
35. Mitchel Lichtman, “DIPS Revisited,” 29 February 2004, Baseball Think Factory.
36. Keri, ed., Baseball Between the Numbers, 57, 91–94.
37. Ibid., 92.
38. Tom Tango, “Defensive Responsibility Spectrum (DRS): Breaking Up the Fielders from the Pitchers,” http://www.tangotiger.net/drspectrum.html.
39. Baseball Info Solutions and Bill James, The Bill James Handbook, 2010, 477–83.
40. David Gassko, “Do Players Control Batted Balls? (Part Two),” The Hardball Times Baseball Annual, 2007 (Skokie, : ACTA Sports, 2006), 158–60.
41. Dayn Perry, “When Does a Pitcher Earn an Earned Run,” in Baseball Between the Numbers, Jonah Keri (New York: Basic Books, 2007), 90.
42. McCracken, “Defense Independent Pitching.”
43. Voros McCracken, “DIPS Version 0,” Baseball Think Factory, 25 January 2002.
44. Voros McCracken, “Defense Independent Pitching Stats, Version 0 Formula,” 17 January 2002, Baseball Think Factory.
45. McCracken, “DIPS Version 0.”
46. McCracken, “Defense Independent Pitching Stats, Version 0 Formula.”
47. MLB Statistics Glossary, 1 June 2007, ESPN.com.
48. McCracken, “Defense Independent Pitching Stats, Version 0 Formula.”
49. “DICE: A new pitching Defense Independent Component ERA,” 19 July 2000, http://www.sportsmogul.com/content/dice.htm.
50. Tom Tango, “Defensive Responsibility Spectrum (DRS): Breaking Up the Fielders from the Pitchers,” http://www.tangotiger.net/drspectrum.html.
51. Dave Studeman, “I’m Batty for Baseball Stats,” 10 May 2005, Hardball Times.
52. Graham MacAree, StatCorner—About tRA, 2009, http://www.statcorner.com/tRAabout.html.
53. Tom Tango, Mitchel G. Lichtman, and Andrew E. Dolphin, The Book: Playing the Percentages in Baseball (Washington, D.C.: Potomac Books, 2007), 19.
54. MacAree, StatCorner—About tRA.”
55. Matt Swartz and Eric Seidman, “Introducing SIERA, Part 4,” 11 February 2010, Baseball Prospectus.
56. David Gassko, “Batted Balls and DIPS,” 30 August 2005, Hardball Times.
57. Brandon Heipp, “A Promising New Run Estimator: Base Runs,” http://gosu02.tripod.com/id8.html.
58. David Gassko, “Explaining LIPS,” 16 June 2009, Hardball Times.
59. Nate Silver, “Lies, Damned Lies: Playoff Hurlers,” 27 September 2006, Baseball Prospectus.
60. Matt Swartz and Eric Seidman, “Introducing SIERA, Part 5,” 12 February 2010, Baseball Prospectus.
61. Matt Swartz and Eric Seidman, “Introducing SIERA, Part 1,” 8 February 2010, Baseball Prospectus.
62. Colin Wyers, “Manufactured Runs: Thawing Out Frozen Ropes,” 13 April 2010, Baseball Prospectus.
63. The Fielding Bible Awards / Plus/Minus / Frequently Asked Questions about Plus/Minus and Runs Saved, fieldingbible.com/.
64. Dick Kaegel, “Subtle Tweaks Elevate Greinke’s Game: Improved Changeup, Focus Lead to Cy Young Season,” 18 November 2009, MLB.com.
65. Jeff Passan “Royals’ Bannister Unafraid to Do the Math,” 8 March 2010, http://sports.yahoo.com/.
66. Colin Wyers, “How Well Can We Predict ERA?” 18 June 2009, Hardball Times.
67. McCracken, “DIPS Version 0.”
68. McCracken, “Pitching and Defense: How Much Control Do Hurlers Have?”

There are many baseball theories. Some theories— for example, that control is the most important part of pitching—have merit. But some are wrong. Case in point: Players used to say that Bob Feller’s fastball rose, but physics has proven that it couldn’t, that it was physically impossible. 

One common baseball theory is that taller pitchers are more durable and just intrinsically better than shorter pitchers. In this article I investigate whether that notion is true. I examined this theory by using a number of statistical techniques, including linear regressions and chi-square tests. For all linear regressions, transformations and nonlinear regressions were done but failed to substantially improve the r-squares. For an explanation of how the statistics were analyzed you can read the appendix at the end of the article. 

In my analysis, I examined only players who were good enough to be drafted. As a result, the most this paper can say is that, when it comes to players who are good enough to be drafted in the Rule 4 amateur draft, the correlation between height and a player’s effectiveness or durability is not statistically significant. It is possible, regardless of the findings of this article, that there is a correlation between height and a player’s effectiveness or durability at lower levels, but I do not address the issue here, because of insufficient data and confounding variables, such as social pressures that convince shorter people to play positions other than pitcher. 

The idea that taller pitchers are more effective and durable is ingrained in baseball. For example, Whitey Ford signed with the Yankees after they offered him more than the Dodgers did, who “told me they thought I was too small anyway,” Ford recalled many years later.1 At first glance, the theory makes intuitive sense. Taller pitchers are more intimidating, throw on a greater downhill plane, and release the ball closer to the plate. You would think that someone taller would be able to throw harder since they have longer arms and their greater size should enable them to be better able to withstand the punishment of pitching. 

However, if you start to think about these assumptions, many of them just don’t hold up. While Randy Johnson was incredibly intimidating at 6-foot-10, the same can be said for Pedro Martinez at 5-foot-11. While longer arms, acting as levers, are certainly helpful in throwing hard, having a quick arm is just as important, if not more so. When it comes to durability, each pitcher is throwing his hardest, so his muscles are working at their hardest. Jon Rauch is not trying less hard to throw his 92-mph fastball than Francisco Rodriguez is trying when he throws his fastball at 92 mph. “We’re not selling jeans here,” as Billy Beane, responding to scouts who said that Jeremy Brown had a bad body, is quoted in Moneyball. Under this thinking height should not have a significant impact on a pitcher’s effectiveness or durability. 

Pitching Effectiveness

The first question to be studied is whether height has an effect on major-league pitchers’ effectiveness. Taking the years 1990 through 2007, I looked at starting pitchers who qualified for the earned-run-average title for one season or more and at relief pitchers who pitched in 45 or more games (or the equivalent in a strike-shortened season) while starting fewer than ten games. 

As you can see in table 1, the data show no evidence of a statistically significant correlation, for starting pitchers, between height (in inches) and any of the customary measures of pitching effectiveness. These include strikeouts per nine innings, walks per nine innings, strikeouts per walk, home runs per nine innings, WHIP (walks plus hits divided by innings pitched), and earned run average. The highest r-square was .5 percent for a nonlinear regression for strikeouts per nine innings pitched. An r-square of .5 percent is extraordinarily small. It means that height has little ability to predict the number of strikeouts per nine innings a pitcher would throw. In addition, the p-values are all very high, the lowest being .14—almost three times greater than the maximum p-value indicating statistical significance. 

Table 2 shows that there is also no correlation between height and effectiveness for relief pitchers. The highest r-square is .3 percent, which is simply too small for the line to have predictive powers. The p-values are also well above the .05 limit, too high to be statistically significant. As a result, it can be said that the statistics do not show a correlation between pitching height and effectiveness for an established major-league pitcher. 

In sum, the data indicate that height is essentially irrelevant when a pitcher is good enough to become an established major-league pitcher. 

At this point we can say out loud what our eyes say when we watch Tim Lincecum or Greg Maddux. Height does not matter for major-league pitchers because only the truly talented make it to the major leagues in the first place. 

Making it to the Majors 

What should be important to major-league franchises is finding players who have the talent to become major-league pitchers. If taller minor-league pitchers are more effective, then it makes sense to scout taller pitchers. There is the belief that taller, leaner young pitchers are more “projectable”—more likely to throw harder as they get older—than their shorter counterparts. For example, Joel Zumaya was drafted in the eleventh round in 2002 despite topping out only in the upper 80s, because he had a “projectable” body. If the theories about pitchers’ heights are correct, one would expect drafted pitchers who are taller, both starters and relievers, to be more likely to make it to higher levels in the minor leagues and to become established major-league pitchers. Looking at the Rule 4 amateur draft from 1985 through 2002, we actually find no correlation between the two variables (table 3). The p-value of .21 is well above the maximum of .05 for showing a statistically significant correlation between height and professional advancement. The evidence, therefore, said that there is no correlation between height and making it to the majors—or to Triple A, or to Double A, and so on—as a pitcher. 

The data for three subcategories were then examined for the likelihood of becoming 

• an established major-league pitcher, 
• an established major-league starting pitcher, 
• an established major-league relief pitcher. 

The study applied the same criteria as were used for evaluating pitching effectiveness. The p-values were .61 for an established pitcher, .52 for an established relief pitcher, and .005 for an established starting pitcher. As a result, it can be said that there was insufficient evidence to show a correlation between height and becoming an established major-league pitcher in general (whether a starter or a reliever) but that there was enough evidence to show a correlation between height and becoming specifically an established major-league starting pitcher. While drafted shorter players are just as likely to become established major-league relief pitchers and established major-league pitchers in general, taller pitchers are more likely to become established major-league starting pitchers. 

Table 1. Established Major-League Starting Pitchers, 1990–2007

Table 2. Established Major-League Relief Pitchers, 1990–2007

Introduction

Recently for the Journal of Quantitative Analysis in Sports I wrote an article where I looked carefully at the streaky patterns of hitters during the 2005 season.2 After I wrote this, I vowed never again to write about streakiness. But after reading the recent article by Trent McCotter in The Baseball Research Journal, I had to break my vow. McCotter’s interesting look at streaky hitting and the statements made in the article deserve some explanation and comments. Also, he describes an attractive method for assessing streakiness and it is straightforward to apply his statistical approach to identify extreme hitting streaks in recent seasons. Using this methodology, I find some “great streaks” during the 2004 through 2008 baseball seasons. 

Comments on BRJ Article by McCotter

In the BRJ article, McCotter wishes to construct a test of the common hypothesis that the individual batting outcomes of a particular player during a season represent independent, identically distributed trials. (We’ll call this the “IID assumption” or the “IID model.”) Essentially this hypothesis says that the batting outcomes are similar to flips of a coin where the chance of a hit on a single at-bat is equal to the batter’s “true” batting average. 

To test this hypothesis, the author looks at the pattern of game hitting streaks of all players for the seasons 1957 through 2006. Suppose we collect the game-to-game hitting records of Mickey Mantle during the 1961 season. We record all his hitting streaks for this season—maybe he started with a hitting streak of one game, a second hitting streak of three games, a third hitting streak of four games, and so on. If the IID assumption is true, then the pattern of hitting streaks for Mantle is simply a by-product of chance variation. If we randomly rearranged his game-to-game hitting statistics, then that wouldn’t change the pattern of streaks. The general question is whether Mickey Mantle’s observed pattern of hitting streaks (and the streak patterns for other players) is consistent with the random patterns from a model with the IID assumption. 

The author performs a computationally-intensive simulation of the patterns of hitting streaks for all players and seasons for the period 1957–2006. For each player’s game log for a season (for all 50 seasons), he randomly arranges the batting lines. Then he computes the lengths of all hitting streaks for all players for all seasons. Then he repeats this simulation process for a total of 10,000 iterations. When he is done, one has an empirical distribution of the lengths of hitting streaks under the IID assumption, and one can see if the actual lengths of streaks are consistent with this distribution. 

The conclusions of the paper can be summarized by two tables that show that the actual number of long hitting streaks (of length 5 and greater) are consistently larger than the mean number of long streaks predicted from the IID model. Moreover, the differences are highly statistically significant. The author concludes by saying: 

This study seems to provide some strong evidence that players’ games are not independent, identically distributed trials, as statisticians have assumed all these years, and it may even provide evidence that things like hot hands are a part of baseball streaks. . . . 

From the overwhelming evidence of the permutations, it appears that, when the same math formulas used for coin tosses are used for hitting streaks, the probabilities they yield are incorrect. 

Much of the article is devoted to a discussion of this conclusion, giving some possible explanations for the presence of long streaks.

Generally I’m fine with the statistical methodology used in the paper. As I’ll illustrate later, the permutation test procedure is an attractive method for testing the IID assumption and the results described in the article are interesting. But I am concerned about some of the author’s statements and conclusions about this analysis. 

First, the author seems to make the implicit assumption that all statisticians believe in the IID assumption. The IID assumption is an example of a statistical model that we may use to fit baseball data. Any model we apply is actually wrong—that is, the real process behaves in a much more sophisticated manner than the model suggests. For example, take the standard IID assumption that individual at-bats are coin-tossing outcomes with a constant probability of hitting success p. Do I believe this is true? Of course not. I believe that the hitting talent of a player goes through many changes during the season and it depends on many other variables such as the quality of the pitcher, the game situation, whether the game is at home, etc. So if the IID model is wrong, why do we use it? Well, the IID model has been shown to be useful in understanding the variation of baseball data. One thing that I have found remarkable in my baseball research is that good simple models (like the IID model) are really helpful in predicting future baseball outcomes. 

Second, the author gives the impression that this statistical analysis gives evidence for the hot hand effect in baseball. Suppose you reject the IID assumption—what does this mean? It could mean that there is a dependence structure in the batting sequence. That is, one’s performance in one at-bat is helpful in predicting the performance in successive atbats. But there is a second possible explanation. Maybe the outcomes are independent, but the chance of getting a hit changes across the season. Either explanation, a dependence pattern or a change in hitting probability, would explain the presence of long streaks. Also these two characteristics are confounded and it is difficult statistically to isolate their effects. So it is wrong to say that long streaks imply a dependence pattern in the hitting sequences. People love to believe in the hot hand and I’m concerned that this paper adds fuel to their hot-hand belief. 

Last, what is the practical significance of the results? To find these streaky effects, the author had to consider all hitting sequences in 50 seasons of baseball data. This is a ton of data—the author was likely considering streaks present in over 30,000 player seasons! But we live in the context of a single season and these results really don’t say that the IID assumption is inappropriate for understanding the lengths of hitting streaks for a single season. I suspect that in the context of a single season, these streaky effects are relatively small and can safely be ignored. The author is concerned about the difficulty of devising a more accurate modeling method since he has shown that the IID assumption is incorrect. But that’s okay, since statisticians don’t need “exact” models. If the streak effect is “real” but small in size, then I’ll continue to use the IID model since I believe it is an attractive approximate model that works. 

Is There Evidence of Long Streaks for the Past Five Seasons?

After reading this paper, it seemed natural to explore the presence of long streaks in the context of a single season. McCotter demonstrated that there was a streakiness effect, but didn’t measure the size of this effect. If the streakiness effect was substantial, then I would think it should manifest itself in a single season. 

So I replicated the author’s analysis for each of the five recent baseball seasons from 2004 through 2008. I’ll carefully outline what I did for the 2004 season which may help explain the author’s method in the BRJ article.

-Using play-by-play files from Retrosheet, I collected the game-to-game hitting data (number of hits and number of at-bats) for all 959 players who had at least one official at-bat in the 2004 season.

-For each player’s game log, I collected the lengths of all hitting streaks. For example, for the 2004 John McDonald, I record if he got a hit (Y) or not (N) for each of the 40 games he had an official at-bat in the season. (See table 1.)

In the 2008 edition of The Baseball Research Journal, I published an article showing evidence that hitting streaks in baseball occur significantly more frequently than they would occur if hitting was random from game to game. I used the random permutation method to determine whether the number of hitting streaks (of lengths 5+, 10+, 15+, and 20+ games) matched what an IID (independent and identically-distributed) model would look like. It turned out that it did not. Later, in the November, 2008 issue of By the Numbers, Jim Albert analyzed the seasons from 2004 to 2008 using the same method that I used, but taking the seasons individually. Jim found high pvalues for most numbers; that is, the number of streaks in real life wasn’t significantly higher than a random permutation would produce. 

I have two issues with Jim’s analysis and results. First, his results still show a tendency for there to be more hitting streaks in real-life than we’d “expect” using a random- permutation method—even at the single-season level. Out of the 20 matched-pairs that Jim generated (five years of data, with four different lengths of hitting streak for each year), 15 of those pairs had a higher value for the “real-life” streak total than for the average over the permutations. And the other 5 (where the real-life total was less than the average over the permutations) were pretty close to being even. So I’d say that—even at the single-season level—there is evidence that hitting streaks of pretty much every length are more likely to occur in real life than if the games were randomly permuted. 

Second, even if Albert’s results didn’t show a tendency for there to be more streaks in real life than over a random permutation, I’d still have a major qualm with his method of trying to show that there is little difference between streak totals in real life versus the permutations. The qualm is that Albert split the 50 years of data that I used into single seasons and then said that there wasn’t much significance at a singleseason level. But that would be the case with almost every study. The entire purpose of conglomerating 50 seasons’ worth of data is to find trends that might not be as obvious at a single-season level (although, per point 1 above, I think there actually is evidence that shows some significance at the single-season level).

If we look at each season individually and say that maybe there’s a slight trend toward more hitting streaks, that wouldn’t mean much; but if almost every season showed the exact same trend, then it would be very meaningful. In other words, the entire purpose of larger sample sizes is to smoke out trends that might not be apparent on an individual sample-by-sample basis; but if almost every sample tends to show the same pattern, then we probably have something significant going on. Of course it makes sense that—in any given season—there might not be that much evidence of a trend; the trend only becomes obvious when viewed from afar, when all the seasons are added together and their similar patterns become magnified. 

Note

A version of this article appeared in By the Numbers 19, no. 3 (August 2009): 1.

Jim Albert Responds

Sabermetrics research consists of posing a good question, collecting the relevant data, and exploring the data to answer the question. In the study of streakiness, there are different questions one can pose. McCotter asks the question: Can batting results (Hit or Out) be represented by a model where individual outcomes are independent and identically distributed (the IID model)? Another question would be: Is there evidence of significant streaky hitting ability among baseball players? A third question would be: Can we classify hitters into the two types “streaky” and “non-streaky”? 

Most baseball fans and statisticians know the answer to McCotter’s question. Batting results for a single player are not independent and identically distributed. So what is the point of McCotter’s analysis that shows, on the basis of 50 years of data, that batting outcomes don’t follow the IID model? Actually, his analysis says little since we already knew that the IID assumption is false. 

I think it makes much more sense to ask a more interesting question where the answer is uncertain. If batters possess an ability to be streaky, what is the size of this streaky effect, and can we describe the characteristics of hitters who are “truly streaky”? To begin to answer this question, I believe that one has to check if there is an unusual streaky pattern of performance for individual seasons. If a pattern of unusual streakiness of hitters is not obvious for individual seasons, then it would seem that the size of the streaky effect is small. In my analysis of the seasons 2004 through 2008, I found that the streaky patterns were consistent with the IID model for two of the five seasons. This tells me that the size of the true streaky effects is generally small, and that conclusion is consistent with my earlier research on streakiness. It is difficult to find players who are consistently streaky from season to season, and so it is hard to separate players into the “streaky” and “non-streaky” groups. 

Statisticians are not concerned about “exact” models. Instead they wish to find approximate models that are useful in understanding the main features of a dataset. The IID model is wrong as McCotter finds, but that’s okay. Since the true streaky effects appear to be small in magnitude, one can make excellent predictions about observed streaky behavior from the IID model. For example, I believe the IID model would provide good predictions of the number of hitting streaks that exceed 10 games during the 2010 season. As I have said before, I think it is remarkable how good simple models like the IID models can be in predicting patterns of baseball hitting performance.  

Trent McCotter Responds

I’ll briefly respond to Jim Albert’s rebuttal. First, nobody “knew that the IID assumption was false” until my article was published in The Baseball Research Journal. Perhaps some of us suspected it, but it was not something “known” or assumed. In fact, it was the exact opposite: every single article that has tried to calculate probabilities of streaks in baseball relied on the IID assumption to be TRUE. If we all knew that it was false, then there sure were a lot of people who decided to write papers based on an assumption they already knew was wrong. Confirming that games are not randomly distributed is a big deal: after reading my paper, Steve Strogatz (a well-known lecturer and ‘stats guru’ at Cornell) canceled a huge simulation project he was running on 56-game hitting streaks. Why? If we can’t use standard probability assumptions, then we just can’t calculate probabilities. At least not meaningful ones. 

Second, I agree that the effect of this “false assumption” seems small at a single-season level. But when we look at a 50-year stretch, we see that there have been many more hitting streaks than there should have been. We have seen 43 percent more twenty-game hitting streaks—and 171 percent more thirty-game hitting streaks—than we should have. Surely these differences are not “small in magnitude” and can be ignored, as Albert proposes. That the effect is small on a single-season level doesn’t mean that the effect is trivial; it just means it’s not monumental. Long hitting streaks are rare. We can’t measure them on a season-by-season basis. We must measure them over decades. 

Baseball is a game of inches: Small changes can make a big difference. And the shift caused by this false assumption about how games are distributed is not something we can ignore when we calculate probabilities of streaks in baseball. 

TRENT McCOTTER is a law student at the University of North Carolina at Chapel Hill.

“Strike Three: Umpires’ Demand for Discrimination” is by Christopher A. Parsons, Johan Sulaeman, Michael C. Yates, and Daniel S. Hamermesh. Hamermesh is the most famous of the four authors and the one quoted most often in the press reports, so I’ll refer to the paper as “the Hamermesh Study.” It’s available for free online.1 Based on the results of the study, the authors (and the journalists who reported on the study) make various claims about the effects of umpire bias:

• “Specifically, an umpire will . . . call a pitch a strike about 1 percent more often if he and the pitcher are of the same race.”2
• “A reasonable estimate is that a team enjoying 162 straight games of [umpire bias] advantage would win maybe one or two extra games.”3
• “The data revealed that the bias benefits mostly white pitchers.”4

I don’t believe these claims are justified. A closer look at the study does show some evidence for the existence of same-race bias among umpires but does not show how much bias there is or where the bias lies. I believe that the quantitative conclusions quoted above are based solely on the implicit assumptions in the study, assumptions the authors may not even realize they made. 

The Hamermesh Study

The authors collected pitch-by-pitch data for every regular-season game in MLB from 2004 through 2006. They classified every pitcher and every umpire into one of four groups: white, Hispanic, black, or Asian. Then, for every umpire-decided pitch (a called strike or a ball) in the sample, they noted the race of both the pitcher and the umpire. (The authors correctly write “race/ethnicity” on the grounds that Hispanic is not a “race,” but I’ll just say “race” to keep things simple.)

Here’s the data from their table that summarizes the results. (I’m leaving out Asian pitchers because there were no corresponding Asian umpires.)

Table 1. Percentage of Pitches Called Strikes, 2004–2006

Table 2. Percentage of Pitches Called Strikes, 2004–2006 Low-Attendance Games

Bob Motley umpired in the Negro American League from 1947 through 1958. The only surviving umpire from the Negro Leagues, he tells of his experience in “Ruling Over Monarchs, Giants and Stars: Umpiring in the Negro Leagues and Beyond” (Champaign, Ill.: Sports Publishing, 2007), which he coauthored with his son Byron Motley, and from which the following article is excerpted. The authors would like to thank Tony Yoseloff and the Yoseloff Foundation for the Yoseloff/SABR Baseball Research Grant that helped make the book and this article possible.

• Related video: Watch the SABR Negro League Legends panel discussion with Bob Motley, Robert Paige, and Larry Lester from 2012 MLB All-Star FanFest (YouTube)

People didn’t like the umpire back in the days of the Negro Leagues, and they still don’t really like umpires today. Some things never change! 

It was pretty common in the Negro Leagues, that if the catcher didn’t like the way an umpire was calling balls and strikes, he would purposely let a pitch go by and let it smack the umpire right in the facemask. That happened to me at least a half a dozen times. 

Of course the catcher would apologize profusely, trying to act as if he had just misjudged the ball, but it was always obvious he had done it deliberately. Of course after he’d pull this stunt, I’d eject him. One time after throwing out Memphis Red Sox catcher Casey Jones for doing this, Buster Haywood had the nerve to come out to question why I was tossing his catcher. So just to get his ire up for asking such an insane question, I tossed out his pitcher too! 

When you get hit in the throat, chin, forehead or face (even wearing a mask) by a 90- or 95-mile-anhour fastball, believe me, you know you’ve been hit. It stings much worse than a foul-tipped ball because it’s a direct hit. Sometimes the ball would be thrown so hard it would actually get stuck in the mask. Once a ball came through my mask, just nipping on my cheekbone. Thank God the front part of the mask bore the brunt of the impact before it slipped inside. 

Back in those days, players would do anything to try to upset the umpire. A good number of the times they would get away with it. Sometimes when a baserunner was sliding into the bag, if he knew he was going to be thrown out he would slide wide and barrel right into the umpire and spike him, just out of spite. Oh, the players did horrible things to us umpires. But we were troupers and brushed it off and kept right on going. 

If you think the players in the Negro Leagues were a handful to deal with, they were a cakewalk compared to the fans. Fans were relentless and showed no mercy on umpires. 

The fans loved razzing the umpires, even on routine plays. One minute they’d applaud you for making a good call (especially if you put a little extra zip in your hip), but they would turn on you in a second if you made a call they didn’t like. 

In a few of the cities, like Birmingham, Indianapolis, and Cincinnati, the fans had a little song they chanted that was a crowd favorite, “Kill the umpire, Kill the umpire!” It was so common and popular among the fans that I expected to someday turn on the radio and hear Count Basie’s band or somebody else make a real version of the song. The chant got crowds so worked up into a frenzy that it was almost hard to hear yourself think. The organist always added to the madness by pounding out a weird-sounding dirge that got the entire stadium chanting, growling, and tomahawking in unison. It was weird! It was unnerving at first, but I quickly realized that it was just all in the fun of the game experience for most fans. Others, however, took it to be a literal declaration! 

Once in Birmingham, our umpire crew came out of the stadium after a game only to find that the car we were riding in had been turned upside down by disgruntled fans. Blaming us for the loss of their Black Barons, the fans decided to take their angst out on us umpires. 

In all honesty, I was never really fearful of fans, but I always knew to keep my wits about myself in dealing with them just in case. For instance, when exiting a stadium after a home team had lost, if someone approached me and asked, “Hey, weren’t you one of the umpires?” I’d calmly answer back, “No, I’m a spectator like you.” A couple of times I even added, “If you see that bastard, let me know, ’cause I’m looking for him too!” I learned quickly how to adapt to every situation. 

As umpires in the Negro Leagues we also learned to never hold a long conversation with a fan. When I did affirm that “yes, I am an umpire,” I always kept walking (with facemask in hand) and never slowed down to engage someone in a lengthy conversation, even if their team had won, just in case they’d flash back to a previous game or call and decided to turn on you. As umpires we had to be thinking and aware all the time. 

One thing about Negro League fans, they never blamed their team for a loss, it was always the umpire. A player could have bobbled a ball or made an errant throw and the fans would blame the umpire. A pitcher might give up hit after hit or a batter might strike out time after time, swinging nonetheless, but guess who’d get the blame? The fans would always find something that had happened in the game, no matter how badly their team may have got beaten, and find fault with the umpire. As sickening as it sometimes was, I was always impressed by their dedication. 

Several times when crowds were really pissed off about a loss, the umpire crew would have to wait for the entire stadium and parking lot to clear before we’d exit. We didn’t want to take any chances. 

In one particular game at my beloved Blues Stadium, in front of my now adopted hometown folks of Kansas City, I found out just how intense the wrath of Negro League fans could get. 

I think I’ve blocked out the exact scenario that led up to the particular incident, but it’s the only time I was actually afraid of the fans. All I remember is that, on the last out of the game, fifteen thousand Monarchs fans decided to blame Bob Motley for the team’s loss. All of a sudden a sea of Coca-Cola bottles started sailing past my head like bazookas being fired from Uzis. Bottles came out of the stands like it was raining. A couple actually hit me and some of the other players who didn’t have a chance to run off to the safety of their dugouts, thankfully without breaking and injuring any of us. As we stood around the field stunned at what was happening, Buck O’Neil and Oscar Charleston ran from their respective dugouts and told me to start walking toward second base, where it was harder for the bottles to reach. The bottles kept coming by the dozens from all directions, and within minutes the field was littered with them! Fearing an out-and-out riot, Buck and Charleston escorted me all the way to the center-field wall and we made an escape. How the three of us scaled that wall and they got me to safety is still a mystery to me, but we did. 

True to the spirit of Negro League competition, the next week all was forgiven and everybody acted as if nothing had ever happened. 

To me, the Negro League fans were the greatest fans in the world. They were devoted, passionate, fanatical, crazed, and raucous. In short, they loved their baseball. They enjoyed every aspect of the game— from getting dressed up in their finest attire, to the tailgating-like picnics, to the carnival-like atmosphere of pregame activities such as concerts, beauty contests, and other activities that different teams provided as entertainment, to the games themselves. People came out to enjoy a full day of fun at the ballpark. 

The concessions at a Negro League game usually consisted of the standard popcorn, peanuts, Cracker Jacks, hot dogs, candy, and soft drinks, which were served in bottles. At Martin Stadium in Memphis they even went a step further, serving chitterlings in a cup, which I always enjoyed, arriving early to make sure I got filled up before a game. 

No alcohol was served at Negro League games to my knowledge. Those who wanted to indulge in spirits during a game had to sneak in their favorite booze. You would see people all over the ballpark with different styles of flasks—disguised as transistor radios, cameras, and binoculars—and sipping away and indulging in their favorite adult beverage. 

To demonstrate just how serious the fans took their baseball: On Sundays, all over the country where there was a Negro League game scheduled, preachers cut their sermons short because they knew that, come 11, 11:30 at the latest, the entire congregation was going to start filtering out, making their mass exodus to the ballfield for the noon game. This tradition had gone on for years and continued in the Negro American League well into the mid-1950s. 

To underscore the importance of black baseball during this time: You must realize that, before the height of the Negro Leagues, black Americans had very few heroes we could identify with. As far as sports figures were concerned, there were only a handful— Joe Louis, Jack Johnson, and Jesse Owens. There were also few political leaders, fewer successful black businessmen or -women, and even fewer professionals such as lawyers, doctors, or dentists. So, ballplayers and musicians, along with clergymen and schoolteachers, were the role models for most black Americans. That is why, even today, sports and entertainment are a big part of black culture and will probably always be. They are entrenched in our culture. 

Unlike today in the sports community, it was rare that you heard a fan badmouth a Negro League player, especially one of their hometown guys. Fans were loyal to the bitter end, no matter who was on the roster. Even if a player jumped ship and moved over to another team, fans for the most part held each player in high regard, even the opposing team. 

Interestingly enough, women were more fanatical about the game than men. They came in droves and were always dressed to kill in their sundresses, flowery hats, and high-heeled shoes. In the days preceding a big Sunday game, beauty shops would give discounts to women so they could get their hair done and ready for the big day. During the week you might see a woman’s hair looking pretty nappy, but come Saturday before the game, you’d walk down 18th and Vine in Kansas City, or Main and McCall in Memphis, and you could practically smell the hair burning from the hot combs and curling irons that beauticians were using getting those “’do’s” done! 

Yes, the women were dedicated supporters. I’ve been called “you no-good so-and-so umpire” or “you blind bat” by more women from the stands than a male spectator would ever have thought about doing. Women loved their hometown teams. A buddy of mine told me once about catching the fury of a group of women in the old Blue Room tavern in Kansas City, for badmouthing the Monarchs after a game. They jumped and beat him, not brutally, but enough that he never said another negative word about the Monarchs in public again.

BOB MOTLEY, the only living Negro Leagues umpire, lives in Kansas City, Missouri.

BYRON MOTLEY, the son of Bob Motley, is a historian of the Negro Leagues.

From today’s perspective in the current age of the Internet, as we look back at a time when the rise of that age (or at least its angle of ascent) was not at all clear, it seems like a bizarrely fortuitous set of coincidences:

• In 1994, the initials of big-time baseball (Major League Baseball=MLB) and the initials of one of big-time baseball’s longtime, big-time outside law firms (Morgan, Lewis and Bockius=MLB) were the same (and still are);
• In 1994, it was the law firm that had the foresight, or luck, to move relatively early to register the Internet domain name “mlb.com.”

And then . . .

• Several years later, in 2000, when Major League Baseball started to aggressively market itself on the Internet, Morgan Lewis and Bockius was, for a variety of reasons described below, willing to part with com for a song, or perhaps even less.

At the time of its consummation, the mlb.com transaction got a lot of attention in the news media, as well it might.3 Because by 2000, it was obvious that the Internet was big business, and transactions in Internet domain names were sufficiently common and significant to inspire government regulation of that market.4 But even in the new and booming and volatile domain-name market, the mlb.com deal qualified as unusual in at least two respects. The deal also illustrates the difficulty of placing a value on a favor, at least between lawyer and client, in the context of the business of baseball.

THE PRICE

First, the price. Morgan, Lewis and Bockius (“Morgan Lewis” for short) reportedly gave, not sold, “mlb.com” to Major League Baseball (“MLB” for short). According to The American Lawyer, a leading magazine covering the legal profession, “After the league announced that it wanted to make a brand out of its initials, a la the National Basketball Association, Morgan, Lewis turned over its registered domain name, MLB.com, to the league—free of charge, of course.”5

It is possible, but unlikely, that The American Lawyer got the story wrong. The magazine did not cite a source for its report, and the exact terms of the deal are beyond our reach because it was a “confidential transfer agreement.”6 As the Philadelphia Inquirer explained at the time, “While domain transfers typically are cash transactions, the parties in this case would not reveal terms—or even give a ballpark figure, if cash was involved.”7 Nevertheless, a few media outlets (none of which cited a source or gave a dollar figure) did report that Morgan Lewis was asked by MLB to “sell” mlb.com,8 and commentators willing to assert in print (again without a source or dollar figure) that Morgan Lewis did in fact extract compensation from MLB were in even shorter supply.9

Most news stories, however, implied it was a gift, or at least not a sale. They reported—without mentioning a sale or a price—that Morgan Lewis “surrendered mlb.com to Major League Baseball,”10 or that “Morgan Lewis would transfer the mlb.com domain name to Major League Baseball,”11 or that MLB “secured” it courtesy of Morgan Lewis, or that Morgan Lewis “relinquish[ed]” it to MLB,12 or something of the sort.13

In any event, based on the available news stories— and they are just about all we have to go on—it appears that MLB probably got something quite valuable for nothing, or at least for a price it has gone to the trouble to keep secret for a decade. How valuable? By the late 1990s, a short and commercially identifiable Internet domain name could be, and often was, worth a small fortune.14 Indeed, in a domain-name lawsuit involving the National Football League and a couple of its teams, the presiding federal judge described the situation in 2000 as follows:

[I]t cannot seriously be disputed that domain names have become a valuable commodity in today’s economy. In the battle to obtain as many website “hits” as possible, companies have paid hundreds of thousands, and sometimes millions, of dollars for domain names that consumers will remember and use when browsing the Internet.15

Law firms, including Morgan Lewis, are for-profit enterprises. Why might such an enterprise give away such a valuable asset?

THE CONNECTIONS

The answer springs pretty obviously from the second unusual feature of the mlb.com-to-MLB deal: the fortuitous connections between the original owner (Morgan Lewis) of the valuable domain name and the entity (MLB) seeking to acquire that name. Those connections—which added up to a long and fruitful if sometimes rocky relationship, described in some detail below—probably made the sweetheart mlb.com deal possible. In other words, giving up mlb.com might well have been a small price for Morgan Lewis to pay if it meant preserving and perpetuating a valuable relationship between the firm and MLB.

But the story of the connections leads to one last question: In September 2000, was all the history between MLB and Morgan Lewis, combined with the prospect of more collaboration in the future, really enough to justify Morgan Lewis’s decision to turn over mlb.com to MLB?

Connections, 1978–1994

In September 2000, when the mlb.com deal was consummated, Morgan Lewis could boast of connections to baseball dating back at least to 1978, when Michael Fremuth, a young lawyer working at the firm, moonlighted as a pitcher for the Alexandria Dukes of the Carolina League.16 The firm’s legal work involving baseball began no later than 1981, when it was defense counsel in Dudley Sports Co. v. Berry, a case in Florida state court in which a boy and his parents sued the manufacturer and distributor of a pitching machine after the boy was injured in an accident involving the machine.17

By the mid-1980s, Morgan Lewis’s baseball involvement went directly and deeply to MLB itself. The firm, which had then and has today a reputation as one of the strongest management-side law firms specializing in labor-management relations, was receiving some publicity for its work representing teams at salary arbitration hearings.18 But it was in October 1987 that the first of the two most important moments in the firm’s relationship with MLB occurred. Murray Chass wrote about it at length in the New York Times:

In what could be a significant change on the labor front, baseball management has made a change in its legal lineup.

For more years than Tommy John has pitched in the major leagues, Willkie Farr and Gallagher [a very big and very prominent New York–based international law firm19] has been the law firm that handled the owners’ labor matters, sometimes to the detriment of the owners. The most noted legal-labor blunder occurred in 1975 when the owners were advised not to negotiate a settlement of the Messersmith–McNally grievance, but to let the arbitrator rule and then have his decision overthrown in court if the ruling went against them. However, the decision of Peter Seitz was upheld in court, and the free agency that followed became far more costly to the owners than it might have been.

Willkie Farr does not specialize in labor law, and some owners think that has hurt them in their dealings with the union. Now, after many years, the Player Relations Committee, of which Rona [MLB spokesman Barry] is executive director, has hired a Washington firm, Morgan, Lewis and Bockius, which represents management in labor relations.

“There are a number of labor lawyers there with great labor law expertise,” Rona said. “Willkie Farr will continue to operate in corporate and general law and tax areas, where their strength and expertise lie.”20

For most of the next decade, Morgan Lewis lawyers were important figures in a range of matters involving labor–management relations in the major leagues,21 including especially the negotiation of collective bargaining agreements with the players’ union, the Major League Baseball Players Association (MLBPA), during the early and mid-1990s.22

Mlb.com, 1994. And then, in 1994, in an exercise of real and remarkable techno-marketing savvy (generally speaking, no one thinks of lawyers as savvy technomarketers, not even lawyers themselves),23 Morgan Lewis registered the domain name “mlb.com.” This display of Web-based foresightedness happened a decade after the firm had begun working closely with the major leagues and seven years after it had been hired as what amounted to MLB’s chief outside labor-relations counsel. Which makes one thing clear: MLB did not hire Morgan Lewis just in order to acquire mlb.com from the firm. A conventional client–lawyer relationship long predated the Internet connection.

Moreover, neither side seemed to have a strong desire to move mlb.com from the law firm to its client at the time. Indeed, in an interview in 2000, an MLB spokesman recalled, “I think we knew they had [the domain name] early on, but we didn’t think much about it because the Internet was not a big thing back then.” Conversely, a Morgan Lewis official recalled that, “[f]rom the beginning, Major League Baseball had an interest in using the mlb.com name. And in the early years we weren’t interested in considering that because we had just started the Web site.”24

Connections, 1994–2000

In baseball, 1994 was something of a high-water mark for Morgan Lewis. Firm partner Charles O’Connor, who had represented MLB during the 1990 spring-training lockout, was again serving as counsel to MLB’s labor-relations arm, the MLB Player Relations Committee, as it negotiated with the MLBPA for a new collective bargaining agreement to replace the one that had expired at the end of 1993.25 It was those negotiations that eventually triggered the 1994–95 baseball strike. O’Connor and several of his colleagues at the firm played prominent roles not only in the contract negotiations but also in the related litigation in 1995, including the famous Silverman v. Major League Baseball Player Relations Committee case before then Judge (now Supreme Court Justice) Sonia Sotomayor in New York federal court.26

Silverman was the second (and far less beneficial) of the two most important moments in the firm’s relationship with MLB. Unfortunately for O’Connor and Morgan Lewis, management lost in Silverman.27 The firm was portrayed in the media as one of the goats— or perhaps scapegoats (often in the company of MLB labor-relations executive Richard Ravitch)—of the debacle.28 The reportage in the Philadelphia Inquirer was impressively thorough and well written, but the basic angle taken on the role of MLB’s lawyers was not atypical of newspaper coverage in general at the time:

Bill Buckner let a ground ball roll between his legs.

Jim Fregosi let Mitch Williams pitch to Joe Carter.

Oh, those agonizing, enduring errors of baseball lore.

And now another has been added. Only this time, the guys in pinstripes who blundered were not ballplayers but lawyers—the ones representing the owners in their dealings with the union.

Faulty strategy is what the judges in the Second U.S. Circuit Court of Appeals called it. The lawyer at last week’s hearing in New York, Frank Casey [of Morgan Lewis], got the umpire treatment from the judges, who interrupted his presentation with sarcastic retorts and accused him of “going around in circles” and trying to confuse the court with double-talk.29

In the aftermath of Silverman, it probably came as a surprise to no one that MLB hired a new lawyer— Randy Levine, who had been serving as commissioner of labor relations for New York City—to take the lead when negotiations with the MLBPA resumed in earnest in late 1995 and early 1996.30 (Levine is now president of the New York Yankees.31) And in another unsurprising move a few years later, both the American League and the National League retained Levine’s old employer, Proskauer Rose Goetz and Mendelsohn (another very big and very prominent New York–based international law firm).32 Proskauer Rose partner Howard Ganz33 served as lead outside counsel in labor disputes that were by 1999 beginning to boil over between the leagues and the umpires’ union, the Major League Umpires Association.34

These moves might have suggested that MLB’s confidence in Morgan Lewis had been shaken,35 but other moves indicated that faith in the firm had not been utterly destroyed. For the balance of the 1990s, Morgan Lewis continued to do some labor-law work for the big leagues,36 including work on the postSilverman 1995–96 collective bargaining with the MLBPA.37 In addition, in 1998 MLB commissioner Bud Selig hired two Morgan Lewis partners, Frank Coonelly and Robert Manfred, to serve as in-house labor-relations counsel at MLB,38 creating between the firm and the big leagues a long-term connection that remains in place today.39

Mlb.com, 2000. And so, by 2000, MLB and Morgan Lewis had been through the wars together. The client had done its part: MLB had been a steady and valuable Morgan Lewis client for more than a decade and had continued to send business to Morgan Lewis even after the uncomfortable period in 1994 and 1995 when the firm spectacularly failed to carry the day for the team owners at the bargaining table or in court. And the lawyers had done their part: Morgan Lewis lawyers had stood up in court, and then in the media spotlight, to take the heat for the team owners’ (and the firm’s) commitment to what turned out to be an unpopular and unsuccessful bargaining position in the 1994–95 round of contract negotiations with the MLBPA.40 And the firm had seemingly performed satisfactorily in other capacities as labor counsel to MLB both before and since that difficult time.

It was against this mixed background of deep disappointment and continuing collaboration that MLB began pressing Morgan Lewis to relinquish the mlb.com domain name. In the past, Morgan Lewis’s control of mlb.com had not been much of an issue. As recently as early 1999, an official at MLB had “indicated that the organization was satisfied with the current arrangement” under which Morgan Lewis used mlb.com and included on the firm’s website a link to MLB’s web-site at www.majorleaguebaseball.com.41 By December 1999, however, MLB wanted very much to control mlb.com, and it was negotiating with Morgan Lewis for a transfer.

What was Morgan Lewis to do? Ironically, this was the very firm whose “great labor law expertise,” including its experience in negotiations with organized labor,42 had made it such a good choice for MLB back in 1987 when the firm was hired to replace Willkie Farr and Gallagher as counsel to the MLB Player Relations Committee.43 But negotiating with its client in 2000 over the transfer of mlb.com as it had negotiated with the MLBPA on behalf of that client over a new collective bargaining agreement in 1994-1995 might not be a good idea.

Holding out for a good price from MLB might well alienate the client. And it was a client that was building a substantial in-house legal operation (including two former Morgan Lewis lawyers) and showing a willingness, perhaps even a preference, for competitively high-powered outside counsel from another firm (Proskauer Rose and its star sports labor law partner, Howard Ganz). In other words, MLB might be willing to pay Morgan Lewis well for “mlb.com” if pressed to do so. But if the firm actually did demand payment, MLB not only probably would, but also easily could, promptly walk away from its long relationship with the firm.

Of course, if MLB was already well on its way to walking away from Morgan Lewis and likely to continue on its way, what did Morgan Lewis have to lose?

First, the firm would almost certainly lose any chance of holding on to any MLB work, let alone winning back any of what it had lost to other firms or the in-house operation. Second, trying to extract top dollar from a client for an asset that had been acquired by the firm for little money but had fortuitously turned to be of great value to that client was not likely to inspire warm feelings of confidence toward Morgan Lewis among its other clients and prospective clients.

Finally, as the abbreviations used in this article for “Major League Baseball” (MLB) and “Morgan, Lewis and Bockius LLP” (Morgan Lewis) suggest, the transfer of “mlb.com” to MLB and the switch to using “morganlewis.com” by Morgan Lewis fit well with the brand-marketing strategies of both organizations.44 Thus, because Morgan Lewis was not going to be using mlb.com itself, the firm had little or nothing to gain from the domain name other than whatever money it could extract from MLB for it.

In the end, as The American Lawyer put it, “Morgan, Lewis and Bockius made the best of a tricky situation with one of its sexiest clients, Major League Baseball.”45 The deal was done on September 6, 2000.

Connections Since 2000

Without knowing what price MLB would have paid for mlb.com, and without access to the confidential MLB-Morgan Lewis agreement, it is impossible to say with any confidence whether Morgan Lewis did the right thing by (apparently) giving away that valuable domain name. But a look at what has happened to the MLB-Morgan Lewis relationship since then (or at least at the parts in the public record) might provide some basis for ruminating about what kind of value Morgan Lewis ended up getting for mlb.com.

To Morgan Lewis, the mlb.com deal must have seemed at first to be an excellent investment, and then perhaps a fruitless one, and then, for the time being at least, a pretty good one.

The months following the September 2000 transfer of mlb.com were a good time for Morgan Lewis’s baseball practice. The firm began to play a prominent part on behalf of MLB in the important and well-publicized labor relations conflicts between the big leagues and the umpires.46 And there was other work as well,47 including an amicus brief for the Office of the Commissioner of Baseball filed in the Supreme Court of the United States in the case of Major League Baseball Players Association v. Garvey.48

In 2002, however, when the time came for MLB and the MLBPA to negotiate a collective bargaining agreement to succeed the one agreed to after the 1994-1995 strike, Morgan Lewis was not invited. Howard Ganz of Proskauer Rose was.49 The American Lawyer interpreted this development as an indicator of just how much value the mlb.com deal could have for Morgan Lewis:

The gift [of mlb.com] won Morgan, Lewis some goodwill. But it didn’t permanently win over Major League Baseball (or, should we say, MLB). That became clear recently, when the commissioner’s office bypassed Morgan, Lewis and tapped New York’s Proskauer Rose to handle the most important piece of work to come along in a half-decade, this winter’s labor negotiations with the Major League Baseball Players Association. The stakes are big. A failure to hammer out a new collective bargaining agreement could lead to a strike or lockout at the beginning of the 2002 season.50

While the loss of its prestigious seat at the MLB-MLBPA bargaining table was surely hard to take, that did not mark the end or even the beginning of the end of Morgan Lewis’s work for MLB. For much of the past decade, the firm has represented MLB in litigation relating to its conflicts with the umpires.51 In recent years MLB has also enlisted Morgan Lewis to represent the Major League Baseball Players Benefit Plan in federal court in Ohio52 and to lobby the administration of President George W. Bush to permit Cuba to participate in the World Baseball Classic.53 Given the confidential nature of much legal work, there is no telling (from the outside) what other sorts of work Morgan Lewis may have done or might be doing for MLB.54

So, in the fifteen-plus years since Morgan Lewis originally registered the mlb.com Internet domain name (and since the 1994–95 MLB–MLBPA meltdown that cost baseball and its fans one World Series and parts of two seasons), the law firm and its big-league client have continued to work together. For the last ten-plus of those years, MLB has had (1) the probably free benefit of Morgan Lewis’s mlb.com as well as (2) the certainly-not-free benefit of the good work of the firm’s labor lawyers. In return, Morgan Lewis has enjoyed the income and prestige of having MLB as a client. Would this particular lawyer–client relationship have persisted for so long, and in the face of such intense ups and downs and competitive pressures, if MLB had not received both kinds of benefits? You make the call.

A POSTSCRIPT IN DEFENSE OF MLB

It would be difficult to read about the process by which Major League Baseball established its Internet home at mlb.com without getting the impression that, if a journalist or commentator had been in charge of the big leagues back in the early 1990s, mlb.com would have been registered by MLB long before Morgan Lewis got to it. If MLB’s failure to register its natural domain name early really was a result of its “comparatively late [entry] in the game,” or the “minor-league . . . quality” of its “tradition”-bound approach to the Web,55 then it had some pretty diverse and fancy company, including such marketing/self-promotion slugs as Nissan Motor Co.,56 Planned Parenthood,57 Madonna (as in the music and media celebrity),58 and the White House (meaning both the operation of which the president of the United States is the boss and the National Fruit Product Company, makers of White House Apple Sauce and other delectables),59 to name just a few of the more famous Internet latecomers.

And according to Sports Illustrated, when MLB and Morgan Lewis closed the mlb.com deal in September 2000, quite a few other pillars of the sports world were still locked out of their natural homes on the Internet. The list at the time included the International Olympic Committee, the NHL’s Colorado Avalanche, and the Bears, Bills, Cowboys, and Saints of the National Football League as well as the Arizona Diamondbacks and Montreal Expos.60

As always, wisdom after the event is easy to come by.

ROSS E. DAVIES, editor in chief of the “Green Bag Almanac and Reader”, is a law professor at George Mason University.

Acknowledgments

The author thanks Paul Haas (SABR member since 1983), Robert A. James, and Mike Kelly.

Notes

1. See morganlewis.com.
2. Bonnie Ciaramella (Morgan, Lewis and Bockius LLP) and Richard Levin (for Major League Baseball), “Morgan Lewis Pitches Web Address to Major League Baseball,” press release, 6 September 2000 (bold type in original), copy on file with the author.
3. See, g., Jim Oliphant, “Morgan, Lewis Takes One for the Team,” New York Law Journal, 10 October 2000, 6; “Big Leagues’ Net Bet,” Newsweek, 2 October 2000; Michael Klein, “Major League Baseball Gains Right to ‘MLB’ Internet Address,” Philadelphia Inquirer, 9 September 2000, C1.
4. See, g., The Anticybersquatting Consumer Protection Act, S. Rep. 106–140, 106th Cong., 1st Sess., 5 August 1999; Anticybersquatting Consumer Protection Act, Pub. L. No. 106–113 (1999), codified at 15 U.S.C. § 1125(d).

5. Ashby Jones, “Tuck in the Bullpen,” American Lawyer, January 2002,
6. Jeff Blumenthal, “Morgan Lewis Decides to Play Ball with Client,” (San Francisco) Recorder, 12 September 2000,
7. Michael Klein, “Major League Baseball Gains Right to ‘MLB’ Internet Address,” Philadelphia Inquirer, 9 September 2000,
8. See, e.g., Matt Fleischer, Karen Donovan, and Victoria Slind-Flor, “The Talk of the Profession,” National Law Journal, 1 May 2000, A8; Greg Auman, “Online Reports Not Necessarily On Line,” St. Petersburg Times, 11 August 2000, 2C.
9. See, e.g., Clinton Wilder, “A New Game Plan,” TechwebNews, 9 April 2001; Mark Conrad, “MLB Gets Web Rights in MLB.com,” Mark’s Sportslaw News, www.sportslawnews.com, 5 September 2000 (accessed 7 September 2010).
10. Henry Gottlieb, Charles Toutant, Sandy Lovell, and Tim O’Brien, “Who’s On First?” New Jersey Law Journal, 25 September
11. Jeff Blumenthal, “Morgan Lewis Decides to Play Ball with Client, [San Francisco] Recorder, 12 September 2000,
12. “Big Leagues’ Net Bet,” Newsweek, 2 October 2000.
13. “On MLB’s Hit List: Web Plays, All-Star Ambushers”, Brandweek, 17 July 2000, 18; Tom Hoffarth, “It’s No Iceberg, It’s P’urgh,” [Los Angeles] Daily News, 31 July 2000; Tommy Cummings, “Underachievers Already Voted Off Packer Island,” San Francisco Chronicle, 23 August 2000,
14. See, e.g., Winn L. Rosch, “Domains: Today’s Name Game,” (Cleveland) Plain Dealer, 20 July 2000, 2C: “The value of easy-to-remember and-recognize names comes as no surprise. The big hits this year: Business.com sold for $7.5 million, loans.com for $3 million and autos.com for $2.2 million.”

15. Weber National Football League, 112 F.Supp.2d 667, 672 (N.D. Ohio 2000).
16. “A Winner,” Legal Times, 11 September 1978, 3; “Michael Fremuth Minor League Statistics and History,” Baseball-Reference.com (accessed 15 October 2010).

17. Dudley Sports v. Berry, 407 So.2d 335 (D. Ct. of Appeal of Fla., 3d Dist. 1981); see also United States v. Athlone Industries, Inc., 746 F.2d 977 (3d Cir. 1984).

18. See, g., Phil Hersh and Fred Mitchell, “Durham Is No Poor Loser: Cubs Win Arbitration, ‘Bull’ Gets $800,000,” Chicago Tribune, 21 February 1985, 1; see also, e.g., Christine Brandt, Karen Dillon, Robert Safian, and Sara Seigle, “Major League Baseball Arbitration,” American Lawyer, November 1987, 30.
19. See willkie.com.
20. Murray Chass, “Free Agency Still Key to Future Peace, New York Times, 15 October 1987, As Professor Larry Garvin of Ohio State University recently pointed out, “Bowie Kuhn was a partner at Willkie Farr handling baseball matters before he became baseball commissioner. It was with his departure as commissioner in 1984 that other law firms started getting larger pieces of the action. I don’t know whether there was a causal link here, but it would hardly be surprising.” Correspondence to the author, 10 November 2010.

21. See, g., Robert Safian, “Tom Roberts Breaks Into the Majors,” American Lawyer, May 1988, 121; “Owners Gird for Costly Collusion Settlement,” Chicago Tribune, 18 January, 1990, 3; Cusack v. Detroit Tigers Baseball Club, Inc., 956 F.2d 27 (United States Court of Appeals, Second Circuit 1992).
22. See, g., Ross Newhan, “A New Man on the Point for Owners: Charles O’Connor took over at the last minute as lead negotiator for baseball management. Will his outlook affect the outcome of the talks?” Los Angeles Times, 9 December 1989, 1; Margaret Cronin Fisk, “Names Behind the News: Batter Up: Lawyers Score In Baseball Talks,” National Law Journal, 2 April 1990, 10; Ronald Blum, “Finally, There’s a Little Light at the End of the Tunnel,” Akron Beacon Journal, 21 December 1994, C6.
23. Henry Gottlieb, Charles Toutant, Sandy Lovell, and Tim O’Brien, “Who’s On First?” New Jersey Law Journal, 25 September 2000.
24. Jeff Blumenthal, “Morgan Lewis Decides to Play Ball with Client,” (San Francisco) Recorder, 12 September 2000, 3 (quoting MLB spokesperson Richard Levin and Morgan Lewis chairman Fran Milone).
25. Julie Stoiber, “Lawyer Goes to Bat for Owners: He Represents the MajorLeague Clubs; As a Baseball Fan, He’s Eager to See the Strike Settled,” Philadelphia Inquirer, 18 January 1995,
26. See Silverman Major League Baseball Player Relations Committee, 880 F.Supp. 246 (S.D.N.Y. 1995); “Baseball Talks May Resume,” New York Times, 9 July 1995, 7.

27. See Silverman Major League Baseball Player Relations Committee, 67 F.3d 1054 (United States Court of Appeals, Second Circuit 1995); see also “New Lawyer for Owners in Appeal of Injunction,” Philadelphia Inquirer, 26 April 1995, D4; Roger I. Abrams, Legal Bases: Baseball and the Law (Philadelphia: Temple University Press, 1998), ch. 9 (reviewing the Silverman litigation and the entire course and consequences of the negotiations and related disputes from 1993 to 1996).

28. See, e.g., “Baseball Owners to Replace Labor Lawyer,” Philadelphia Inquirer, 16 April 1995, C10; “Rangers, Tettleton Agree on 1-Year Deal,” Houston Chronicle, 13 April 1995, See also, e.g., Jacques Steinberg, “Ravitch, Mayor’s Choice to Run Schools, Has Extensive Public Record,” New York Times, 17 September 1995: “Mr. [Richard] Ravitch served from 1991 until last December as the [MLB] owners’ chief labor executive and was credited with bringing the teams together on a revenue-sharing plan, in which richer teams like the Yankees would help poorer teams like the Pittsburgh Pirates. But by basing that plan on a salary cap, he earned the enmity of the players and was never able to forge a new collective bargaining agreement with them. While the [MLBPA] union blames Mr. Ravitch, in part, for bringing on the strike in summer 1994, David Sussman, the executive vice president and general counsel of the Yankees, believes he was cast unfairly as a scapegoat. Nevertheless, soon after the strike began, the owners eased Mr. Ravitch out of his lead role at the bargaining table. He resigned in December.”
29. Julie Stoiber, “Phila. Law Firm May Have Dropped the Ball for the Owners: Judges Blasted the Strategy of the Baseball Owners’ Lawyers; Will the Firm Be Benched?” Philadelphia Inquirer, 9 April 1995,
30. See David Firestone, “Labor Chief for Giuliani to Leave for Baseball Job,” New York Times, 19 September 1995.

31. Yankees Front Office, mlb.mlb.com/team/front_office.jsp?c_id=nyy (accessed 16 October 2010). Levine is also of counsel at Akin, Gump, Strauss, Hauer and Feld LLP, yet another very big and very prominent international law See www.akingump.com/rlevine/ (accessed 16 October 2010).
32. See proskauer.com (accessed 16 October 2010).
33. See proskauer.com/professionals/howard-ganz/ (accessed 16 October 2010).
34. See, g., Susan Hansen, “Proskauer on Deck for Baseball Owners?” American Lawyer, November 1995, 17; Ashby Jones, “Tuck in the Bullpen,” American Lawyer, January 2002, 18.
35. See, e.g., “Season Opens with Replacement Umps,” Rocky Mountain News, 26 April 1995, 8B: “The decision to replace Casey, made by the ruling executive council, signals what probably will be the phase-out of Morgan, Several owners were angered over losing at the injunction hearing, and some want to drop Morgan, Lewis. Oral arguments on the appeal are scheduled for May 11.”
36. See, g., Susan Hansen, “Proskauer on Deck for Baseball Owners? American Lawyer, November 1995, 17; Bowen v. Workers’ Compensation Appeals Board, 73 Cal.App.4th 15 (California Court of Appeal, Second District 1999).
37. See, g., “Smiley an All-Star as a Replacement,” Miami Herald, 9 July 1995, 7D.
38. See Appellants’ Brief and Appendix, Phillips Selig, 2007 WL 5289093 (Superior Court of Pennsylvania, 5 November 2007).
39. See MLB Official Info, MLB Executives, mlb.com/mlb/official_info/about_mlb/executives.jsp?bio=manfred_rob (accessed 7 September 2010), identifying Robert D. Manfred, Jr. as “Executive Vice President, Labor Relations and Human Resources,” and as a former “partner in the Labor and Employment Law Section of Morgan, Lewis and Bockius, LLP”). Coonelly left his position under Selig in 2007 to become president of the Pittsburgh Pirates. See Rob Biertempfel, “Bucs Hire Coonelly, President with a Plan, Pittsburgh Tribune Review, 14 September 2007; Front Office biographies, Frank Coonelly, President, pittsburgh.pirates.mlb.com/pit/ team/exec_bios/coonelly_frank.jsp (accessed 16 October 2010): “Frank Coonelly was named President of the Pittsburgh Pirates on September 13, 2007 Prior to joining the Pirates, Frank served as Senior Vice President and General Counsel of Labor in the Office of the Commissioner of Baseball . . . Coonelly practiced labor and employment law as a Partner in the Washington, D.C. office of Morgan, Lewis and Bockius before joining the Commissioner’s Office. A large part of Frank’s practice consisted of the representation of Major League Baseball as outside labor counsel. In that role, Frank assisted the Commissioner of Baseball in collective bargaining and litigation matters. He also represented several individual Clubs, including the Minnesota Twins, Chicago Cubs, Montreal Expos and Atlanta Braves, in salary arbitration matters.”

40. See Leonard Koppett, Koppett’s Concise History of Major League Baseball (New York: Carroll and Graf, 2004), 456–70.

41. Ruth Singleton, “Morgan to Lewis to Bockius: Firm’s Web Site Plays Major League Ball,” National Law Journal, 19 April 1999,
42. See Jennifer Fried, “Walking the Line: Morgan, Lewis Knows How to Bargain at the Table and Battle in the Courthouse,” American Lawyer, January 2004,
43. Murray Chass, “Free Agency Still Key to Future Peace,” New York Times, 15 October 1987,
44. Jim Oliphant, “Morgan, Lewis Takes One for the Team,” New York Law Journal, 10 October 2000, Correspondence to the author from Robert A. James, partner and board member of Pillsbury Winthrop Shaw Pittman LLP, 19 October 2010: “The marketing strategies of many large law firms have been gravitating for some time to use of the first name or names on the letterhead. Bingham, Orrick, and Paul Hastings are now promoted with shorthands rather than full names or acronyms. With their 2001 merger the Winthrop, Stimson, Putnam & Roberts and Pillsbury Madison & Sutro firms adopted pillsburywinthrop.com and discontinued use of their ‘WSPR’ and ‘PMS’ shorthands—the latter acronym having a most unfortunate connotation in the late twentieth century. The Pillsbury firm today uses the single-word Pillsbury brand, but retains the ‘pillsburylaw.com’ domain name to distinguish itself from the Pillsbury food brands.” If Morgan Lewis had similar plans in 2000 for moving from mlb.com to morganlewis.com, the firm may have been quitclaiming the sleeves off of its vest.
45. Ashby Jones, “Tuck in the Bullpen,” American Lawyer, January 2002, 18; see also Michael Klein, “Major League Baseball Gains Right to ‘MLB’ Internet Address,” Philadelphia Inquirer, 9 September 2000, C1 (“The deal . . . was complicated by the fact that the two sides had long been business partners and enjoyed attorney–client privilege: Morgan Lewis has handled much of Major League Baseball’s labor-negotiations work for a decade”); Monica Bay, “Yankee Stadium, Ringstrasse, Disney World, Dallas,” Law Technology News, November 2000,
46. See, g., Bonin v. World Umpires Association, 204 F.R.D. 67 (E.D. Pa. 2001); Defendant Office of the Commissioner of Major League Baseball’s Memorandum of Law in Support of its Motion to Dismiss, Bonin v. World Umpires Association, 2001 WL 34898519 (E.D. Pa. 2001); Gregg v. National League of Professional Baseball Clubs, 57 Fed. Appx. 123 (3d Cir. 2003); Brief of Defendants/Appellees National League of Professional Baseball Clubs, Gregg v. National League of Professional Baseball Clubs, 57 Fed. Appx. 123, 2002 WL 32818411 (3d Cir. 2002); Major League Umpires Association v. American League of Professional Baseball Clubs, 2001 WL 34894718 (E.D. Pa. 2001); Major League Umpires Association v. American League of Professional Baseball Clubs, 357 3d 272 (3d Cir. 2004); Reply Brief of Appellees/Cross-Appellants, Major League Umpires Association v. American League of Professional Baseball Clubs, 357 F.3d 272, 2002 WL 32819168 (3d Cir. 2002); Memorandum of Law in Support of Motion of Defendants to Dismiss the Complaint, Major League Umpires Association v. American League of Professional Baseball Clubs, 2003 WL 23906078 (E.D. Pa. 2003); Memorandum of Law in Opposition to the Major League Umpires Association’s Motion for Contempt of Court, Major League Umpires Association v. American League of Professional Baseball Clubs, 2005 WL 3724109 (E.D. Pa. 2005); Phillips v. Selig, 157 F.Supp.2d 419 (E.D. Pa. 2001); Brief and Appendix for Appellees, Phillips v. Selig, 959 A.2d 420, 2008 WL 2623632 (Superior Ct. Pa. 2008); Memorandum of Law in Support of the Motion of Defendants to Disqualify Patrick Campbell, Esquire and Phillips and Campbell, P.C., Major League Umpires Association v. American League of Professional Baseball Clubs, 2003 WL 23906093 (E.D. Pa. 2003); Memorandum of Law in Support of Motion for Summary Judgment of Defendants, Phillips v. Selig, 2006 WL 6048310 (Ct. Common Pleas of Pa., Phila. Cty. 2006); Complaint, Office of the Commissioner of Baseball v. Major League Umpires Association, 2002 WL 34447591 (E.D. Pa. 2002); see also Shannon P. Duffy, “Arbitrator’s Call on Most Umpires Stands: Three See Their Cases Returned for Reassessment,” Legal Intelligencer, 14 December 2001, 1.

47. Ashby Jones, “Tuck in the Bullpen,” American Lawyer, January 2002, 18: “For the time being, the firm is handling the league’s garden-variety ERISA and employment ‘We’re just happy that Rob and Frank are keeping us busy with other matters,’ says Steven Wall, the deputy manager of the firm’s labor and employment practice group.”
48. Motion for Leave to File Brief Amicus Curiae and Brief Amicus Curiae of the Office of the Commissioner of Baseball in Support of the Petition, Major League Baseball Players Association Garvey, 532 U.S. 504 (2001) (Harry A. Rissetto, Counsel of Record, Morgan, Lewis and Bockius LLP).
49. Liane Jackson, Play Ball: MLB Lawyers Strike a Deal, Corporate Legal Times, 1 November 2002,
50. Ashby Jones, “Tuck in the Bullpen,” American Lawyer, January 2002,
51. See note 46
52. See Answer, United States Rogers, 558 F.Supp.2d 774, 2004 WL 3124417 (N.D. Ohio 2004); see also United States v. Rogers, 558 F.Supp.2d 774 (N.D. Ohio 2008).
53. See “Looper Back with Cards for $13.5 Million, 3 Years,” Chicago Tribune, 16 December 2005, 6.
54. Cf., e.g., Rebecca A. Falk Attorney Biography, www.morganlewis.com (accessed 17 October 2010): “Recent matters include . . . Represented individuals employed by a Major League Baseball franchise in connection with the San Francisco U.S. Attorney’s Office’s investigation into steroid use and the related internal investigation conducted by the Commissioner of Baseball.”
55. Michael Klein, “Major League Baseball Gains Right to ‘MLB’ Internet Address,” Philadelphia Inquirer, 9 September 2000, C1; Clinton Wilder, “A New Game Plan,” TechwebNews, 9 April
56. See Nissan Motor v. Nissan Computer Corp., 378 F.3d 1002, 1006 (9th Cir. 2004): “This appeal raises a number of trademark issues arising out of the use by Uzi Nissan of his last name for several business enterprises since 1980, his use beginning in 1991 of ‘Nissan’ as part of the name of a North Carolina computer store he owned—Nissan Computer Corp.—and his registration in 1994 of ‘nissan.com’ as a domain name. ”
57. See Planned Parenthood Federation of America, v. Bucci, 42 U.S.P.Q. 2d 1430, 1997 WL 133313 (S.D.N.Y. 1997): “On August 28, 1996, Bucci registered the domain name ‘plannedparenthood.com.’”
58. See Madonna Ciccone v. Dan Parisi, WIPO Case No. D2000-0060, www.wipo.int/amc/en/domains/decisions/html/2000/d2000-0847.html (Oct. 12, 2000) (vis. Oct. 17, 2010): “On or about May 29, 1998, Respondent purchased the registration for the disputed domain name”.
59. See Charles C. Ruff, counsel to President Clinton, letter, to Dan Parisi, president, Infolook, Inc., news.com.com/2009-1023-207800.html? legacy=cnet (8 December 1997) (accessed 17 October 2010) “It will come as no surprise to you that the White House Counsel‘s Office is aware of your Internet Web site, ‘www.whitehouse.com,’ and that we object to your use of the names and images of the White House, the President, and the First Lady on that Web site to sell memberships in an adult video club”; discussed in “Wasting Time in Cyberspace,” by Chad D. Emerson, 34 Balt. L. Rev. 161, 186–87 and n.223 (2004).
60. See “Misdirection Plays,” Sports Illustrated, 18 September 2000.

There is beauty in finding that beneath a complex system, one so large and entrenched that it seems to operate under its own power, there is a history that is quite human. The work of a person, perhaps a small band of people, fueled by energy and sweat equity, and perhaps a dollop of obsessiveness, can create a mighty enterprise. Simon Winchester wrote a bestseller about how one man, James Murray, stood at the center of The Oxford English Dictionary. On an abstract level, one might claim that William Blackstone created the conceptual framework of the common law that still guides us. But those two are famous figures. The real fun lies in identifying those who, by sheer perseverance and drive, create mighty dreadnoughts that sail on under their own power, growing and changing, and yet remain anonymous. Two delightful examples, related on many levels, are the individuals behind the West System1 and the Macmillan Baseball Encyclopedia (MBE). 

Baseball and lawyers are intricately intertwined. This is no news to the reader of this article. The magic that pulls them together may not admit to easy characterization, but there is no denying that Stevens’s “The Common Law Origins of the Infield Fly Rule” created an enthusiastic body of commentary all on its own, or that the intricacy of the Baseball Rule Book maps easily onto the technical pyrotechnics of the Internal Revenue Code for specificity and opaqueness. Lawyers love the intricacies of the game of baseball and the collection of statistics. More congruence is found in the fact that the guiding light of modern baseball statistics and the conceptual blueprint for legal analysis share similar origins. There are human stories behind these grand enterprises.

Building the West System

The West Publishing Company was founded by two brothers: John and Horatio. John was a salesman who noticed that some of his customers, who were lawyers, were having trouble getting their hands on recent judicial decisions. West lived in Minnesota in the late nineteenth century. Courts there were required to make written copies of judicial opinions available, and the state had an official printer of decisions, but getting access to these opinions was not easy.2 The official printer was slow and not always reliable. This gave John West an idea. 

The classic Supreme Court opinion in Wheaton v. Peters had established in 1834 that judicial opinions were in the public domain. These opinions could be published by anyone who wanted to do so. Many jurisdictions had official printers for their courts’ decisions, but the office of official printer was often a sinecure. The resulting publications were incomplete and slow. John realized that one might make money by doing the sheer donkey work of going from court to court, making copies of the opinions, printing them, and distributing them.3 Remember, the West brothers had no photocopy machines, let alone digital information. What they did have was an idea and the market incentive to perform the simple, hard work. It had to be done carefully and quickly. John was not a lawyer; he was an entrepreneur.

Armed with his idea and the raw materials to carry it out, he and his brother Horatio went into business. They produced the Syllabus, a collection of Minnesota decisions. It was a huge success. It was such a winner that the brothers began the Northwestern Reporter, which included decisions from courts in surrounding states. That quickly led to the full National Reporter System. This tale has been told in detail elsewhere, but what matters here is that the root from which it all grew was simple effort and obsessive attention to detail. The West Company produced and produces a more thorough and timely product than anything seen before. 

The maraschino cherry on the chocolate sundae of the West story is the Key Number System. The West brothers realized that they should offer some organizational system for finding the judicial opinions in their Reporters. They bought a system developed by John Mallory and morphed it into the Key Number System. The Key Number System categorized opinions by classifying legal ideas. It was new and it allowed lawyers to find judicial opinions via an entirely new rubric. Several of us have contended that the Key Number System categories came to have an impact on the way lawyers think and judges write. 

As the paper-based universe of information sinks slowly in the west, and the new dawn belongs to the texting, social networking, and Boolean-searching generation of multitaskers who sit in the classes that I teach, it is fitting to note that the mighty West system was the product of the obsessive work and simple plan of human beings. 

The MacMillan Baseball Encyclopedia: The Beginning of a Magnificent Obsession 

Growing up as a baseball fanatic,4 I treasured the Macmillan Baseball Encyclopedia. As a boy contemplating it, I was filled with wonder. The MBE listed every player who ever had a cup of coffee in the majors. It was detailed and it was authoritative. For me it was an unquestioned source of information. Like the West System (of which I was ignorant in my elementary-school years), it seemed an enterprise bigger than any human, but in fact it was the product of the work of a small band of zealots—humans who were willing to invest the sweat equity in its creation. 

David Neft was a statistician who loved baseball. Growing up in the 1950s, he saw The Official Encyclopedia of Baseball as his lodestone of authority. But it was incomplete in coverage, and printed only batting averages for hitters and won–lost records for pitchers. He nurtured the dream of something better. When he went to work for Information Concepts Incorporated in 1965, he proposed the idea of a computerized baseball encyclopedia that would be complete and reliable. How Neft sold his concept to ICI and then to Macmillan is a great tale.5 The statistics were out there, but before 1920 they were not in one place, and after 1920 they were unverified. Doing the job right would mean starting over. First, the new effort would need to be certain who the players were. For that there was another compulsive information maven, Lee Allen. 

Lee Allen was the longtime historian of the Baseball Hall of Fame in Cooperstown, New York. Known as a walking encyclopedia of baseball knowledge, Allen had spent three decades collecting information on players. Allen did not care about statistics; he wanted biographical data. Though official records had been kept since 1903, there had been little quality control. Allen had supplemented these records through his own research, his own drive to be accurate and complete. He visited graveyards and pursued leads on players like a Sam Spade in search of information on the black bird. He compiled a massive library of books and materials that he took with him to Cooperstown when he assumed his position as librarian there.6 Basing their encyclopedic work on the biographies compiled by Allen, Neft, and his team went to work gathering up data. Neft hired a team of twenty-one researchers and set them to work, checking old newspapers and gathering up data. As Alan Schwarz put it: 

The staff of 21 then began its Kerouakian odyssey all over the United States, from library microfilm rooms to long lost graveyards, mortar and spades always in tow, to build the greatest book of statistics sports had ever seen.7

The hard work of slogging was supplemented by the effort of programming a computer to sort and check each item. It was the middle of the 1960s. Computers were primitive creatures and the task was not simple. It fell to Neil Armann. Armann was not a baseball fan, much like John West was not a legal scholar, but he took on the challenge of creating a computer program that would pull together and cross-check all statistics. Given that these were early days for computing, there is another great story here, but we shall tip our cap to Mr. Armann and move on. 

The first edition of the Macmillan Baseball Encyclopedia, which was published in 1969, sold an amazing 100,000 copies at $25 ($150 in the dollars of 2009). The New York Times reviewed it three times. It carried the day. Just as the West Key Number System set the accepted categories for legal thought, The Baseball Encyclopedia established the standard for statistical categories. If you look through the volume you will find seventeen categories for hitters, and nineteen for pitchers. They became the standard way of evaluating performance. In my family’s basement back in Ohio, these were the numbers that meant something to me. The Baseball Encyclopedia was authoritative and it created an authoritative classification system. I knew that if Kelly Heath had one at-bat in the major leagues, it would be in the MBE. As with the world of the West brothers, the information was there for the taking. It never occurred to me that actual people struggled to pull these sources together, they just existed. 

Once the MBE was in place, a new world was opened. Having a source of reliable information available, others began to build. In its wake, those who were devoted to baseball statistics founded the Society for American Baseball Research (SABR), which applies the tools of modern statistics and the power of computers to generate, refine, and parse new categories of information. Indeed, new statistical categories are now in vogue, but the rock upon which it was all built was the Macmillan Baseball Encyclopedia. 

Common Fate

These two great enterprises share another characteristic. They are intellectual booster rockets carrying their missions forward. And now, having served their purposes, they are falling back to earth. Each has taken us to a new level where others have built upon them. Boolean searching has largely replaced the Key Number System at the center of the search function of legal research. New digital tools, web pages, blogs and a deluge of specialty software applications have replaced The Baseball Encyclopedia. The tenth edition, published in 1996, was its last hurrah. Just as law libraries are shipping the old West Digest and National Reporter volumes to storage, or perhaps to a nearby dumpster, no one wants to buy a ten-pound reference book on baseball statistics when a website can tell you everything you need to know and more. 

Since you have read to this point, you must be a person of the old school. One who values the feel of pages and admires the heft of a ten-pound reference book. Let us take a moment, and raise a glass of fine single malt scotch to these two very human efforts to bring order out of chaos, and to the resulting books that represent the giants upon whose shoulders we now stand. Each was a masterpiece built on sweat, and each was a financial success in its day. As with so many other great authoritative tools of the twentieth century, their days are gone, but they should not be forgotten. 

ROBERT C. BERRING is Walter Perry Johnson Professor of Law at the University of California, Berkeley, School of Law.

Notes

1 This article was published originally in The 2010 Green Bag and Almanac and Reader, 318–21. The West System will stand for both the National Reporter System and the American Digest System. Though it is the former that is primarily of interest here, like Ruth and Gehrig they are forever conjoined.

2 For a short and charming description of the history of the distribution of legal information in the United States, see the text of the 2009 Opperman Lecture at Drake Law School, “Remarks of the Honorable John G. Roberts, Jr. Chief Justice of the United States,” in the fall 2008 issue of the Drake Law Review at page 1. I am an admirer of any Chief Justice who can use the term “pneumatic tube” in a lecture.

3 Marvin, History of the West Publishing Company, provides a full account of this story. This book is very hard to find. For a more easily located version of the story try “Collapse of the Structure of the Legal Research Universe: The Imperative of Digital Information,” 69 Wash. L. Rev. 9 (1994). It is my youthful attempt at telling the story, complete with edifying footnotes.

4 Growing up in northeastern Ohio, I was a Cleveland Indians fan. Since my team never won, focusing on statistics was a fine outlet for my enthusiasm. Did you know that Rocky Colavito once hit four home runs in one game? I thought not.

5 The story is well told by Alan Schwarz in The Numbers Game: Baseball’s Lifelong Fascination with Numbers (New York: St. Martin’s Griffin, 2005). Chapter 5 covers this territory but, if one loves baseball and statistics, the whole book is worth a read. It is in print in paperback.

6 Credit should also be given to John Tattersall, a shipping executive who spent his life collecting information on players from the nineteenth century. His work formed the basis of the reports on the earliest players of the game.

7 Schwarz, The Numbers Game, 95. Kerouakian is my word of the month.

For twenty-eight days after the end of the regular season, and fourteen days after the last playoff game, Brockton and Lawrence bickered publicly about a confusing welter of complaints: whether and when postponed games should be made up, who should schedule them, and which of three teams Lawrence’s star pitcher was actually under contract with. These disputes, and the heat generated by each team’s loyal newspaper, required neat diplomacy and legal tact on the part of the league’s board of directors.

In 1885 the Eastern New England League was in its inaugural season and comprised five teams: Lawrence, Brockton, Haverhill, and Newburyport, all in Massachusetts, and Portland, in Maine. The league schedule consisted of 80 games, with each team playing 20 games against each of the other four. Newburyport and Portland both played their way out of contention early in the season, and Haverhill ultimately faltered as well, leaving the way clear for the two powerhouses and bitter rivals, Brockton and Lawrence.

Brockton ended its regular season with a record of 48–31. Lawrence, with a record of 45–31, had three games remaining at the end of September: one against Portland and two against Newburyport. They needed to win all three to match Brockton.

On September 29, Lawrence defeated Portland, 9–1, on the strength of a four-hitter by John A. Flynn. After the game, Portland manager Chick Fulmer filed a protest. He claimed that the game should not count because the teams had already played each other the allotted 20 times. In response, Lawrence pointed out that one of the games, in Portland, had been agreed on as an exhibition, since it would have been the eleventh match between them in that city. For the first time, but certainly not the last, the Lawrence Daily American entered the fray:

This [protest] was undoubtedly due to the fact that Portland accidentally defeated Brockton Monday [September 28], and McGunnigle, who is a much better wire puller than ball player, laid a plan with Portland to win another game to make him safe. This seems to be the whole thing in a nutshell, the Brockton management being as brazen receivers of stolen goods as McGunnigle is a purloiner of the same. They evidently expect no difficulty in getting whatever they want in the board of directors. In this way only has Brockton gained a sight of the pennant, by fraud and downright theft, which no honest man would uphold.1

The primary object of the paper’s scorn was Bill “Gunner” McGunnigle, the 30-year-old right-hander in his first season as Brockton manager. Born and raised near Boston, he’d made his playing debut with a junior team in Brockton and had several years of experience in and around New England, as well as 54 games, 19 of which he pitched, with Buffalo of the National League in 1879–80. The “stolen goods” referred to were the championship laurels that both clubs hoped to wear.

With this issue looming in the background, Lawrence still had two games left against Newburyport. These were played the next two days, and Lawrence came away with two clutch victories. In the first game, on September 30, they beat the hosts 11–6. They then returned to Lawrence on October 1 and beat them there, 8–3. Flynn started the second match on one day of rest but struck out seven, allowed only four singles, and hit a pair of doubles himself.

The two front-runners, Lawrence and Brockton, were tied atop the leaderboard. As luck would have it, though, a pair of games between them had been called off earlier in the season.

The first disputed game was played on August 14, when the two teams met in Manchester, New Hampshire.2 The umpire did not show up, so Brockton catcher George Bignell arbitrated from behind the plate. Predictably enough, Bignell was accused of favoritism, but Lawrence managed to rack up a 6–0 lead through seven and a half innings. Brockton rallied for four runs in both the eighth and ninth innings, but three more runs for Lawrence in the top of the ninth decided the game in its favor, 9–8. The exact cause of the protest is not recorded. Presumably, Brockton claimed that the game shouldn’t have counted without the umpire. After all, they’d been deprived of their starting catcher.

The second contested outcome came on August 26, in Brockton. The Boston Globe captured what must have been the prevailing sentiment, noting that “nearly every time the Brockton and the Lawrence teams meet upon the ball field there is more or less ‘kicking’ about the decisions of the umpires.” The paper continued:

The newly appointed umpire, Mr. A. W. Stewart of Ayer, was assigned to duty here today and administered the worst “roasting” ever accorded the home team. It was evident from the beginning of the game that Mr. Stewart was not a good judge of balls and strikes and his fatal misjudgments were principally bestowed upon the home team.3

Facing a three-run deficit in the bottom of the sixth inning, Brockton’s George Tanner stepped to the plate and “knocked a ball clear over the right-field fence for a home run, but the umpire decided it was only for two bases.”4 Then, instead of returning the ball to the pitcher, Lawrence second baseman Timothy Brosnan tagged Tanner, who was not standing on the bag. Stewart promptly declared him out. “The audience protested against such a decision, and the umpire, thinking himself insulted, left the field and would not return until 35 minutes had passed. The game was then continued under protest.”5 Lawrence ended up winning, 9–3.

The validity of these two games was debated at a league meeting in September. Apparently, they were both stricken from the record and ordered to be replayed. The way the standings stood, their outcome would determine the championship.

The actions of the two clubs after the end of the officially scheduled season are, as reported by their respective mouthpiece newspapers, muddled. First, even before Lawrence’s second game with Newburyport, the Brockton Gazette reported:

No longer ago than this week, Secretary [H. S.] Bicknell of this city wrote to Manager Walter] Burnham of Lawrence, inquiring if the games could not be arranged, but up to the present time no reply whatever has been received, a fact which Manager Burnham cannot deny. . . . To sum up, Lawrence cannot tie us, and knows it well, but apparently would rather resort to chicanery than to lose the pennant. We would not.6

In response, the Lawrence Daily American claimed the exact opposite, that Burnham had contacted Bicknell and received no reply. “They [Brockton] refuse to play, knowing defeat to be inevitable. They crowed over the pennant too soon and now dread having to eat their words.”7

Despite the posturing, a directive came that same day, October 1, from league secretary Charles J. Wiggin, mandating the teams to play off the two remaining games, on October 3 in Lawrence and the following day in Brockton. The Brockton Gazette protested this arrangement:

All fair-minded people are convinced that Brockton has won the championship, and nothing can shake this conviction. Brockton has a postponed game with Newburyport, why doesn’t Wiggin order that to be played? Because he has nothing to say but what is in Lawrence’s favor. Brockton will not play these games which have been ordered by the secretary.8

It is not clear why baseball men in Brockton believed they’d already won the pennant, unless it was in hopes of having the Portland protest upheld. Also, a report in the Newburyport Germ on October 4 indicated that the Brockton team had indeed agreed to play the games, contrary to the indication in the Brockton Gazette that they would defy Wiggin’s order.9 Sure enough, though, when Lawrence arrived at its field on October 3, no Brockton players were there.

Once the home team stepped onto the field, the umpire waited a specified amount of time and then declared Lawrence the winner by forfeit, 9–0. “The greatest indignation was felt by the audience,” wrote the Lawrence Daily American, “at the shabby treatment [by] the Brockton management . . . [who know] full well that if Lawrence had been given her just dues she would now hold the pennant, which Brockton is attempting by the most bare-faced methods to steal.”10

Several minutes after the forfeit was declared, however, a telegram arrived. It read: “Manager W. W. Burnham—I cannot play, as several players refuse to go [to Lawrence], as their contracts expired yesterday. W. H. McGunnigle.” The crowd soon dispersed, “thoroughly disgusted.”11

In the following day’s Gazette, McGunningle elaborated, saying that “no one more than he desired to play the three postponed games [including the one against Newburyport]” but that league secretary Wiggin had overstepped his bounds in ordering the games played on October 3 and 4.12 First, McGunnigle argued, the two teams must be given the chance to arrange the dates themselves, according to the league constitution. For his part, the Brockton manager submitted that they play on October 8 and 9. That would give him time to reassemble his team.

That same day, however, a report in the Boston Journal said that “Capt. McGunnigle of the Brocktons has definitely decided to play no more games during the present season.” This apparent contradiction was seized on immediately by the Lawrence paper. “The two despatches given above,” it dutifully reported, “settle the whole question. There is now no doubt that McGunnigle does, and does not, want to play off the three games yet to be played.”13

The Boston Journal article contained another piece of news potentially much more damaging for Lawrence. On October 4, Brockton’s Bicknell received a telegram from American Association commissioner Wheeler C. Wickoff. In it, Wheeler claimed that Flynn, Lawrence’s star pitcher, had signed a contract with the AA’s New York Metropolitans on September 15.14 If true, this would invalidate the six games he had played for Lawrence since then, all of them victories.

With this nineteenth-century media circus in full procession, Lawrence traveled to Brockton the following day, October 5, for the second scheduled game. The Brockton players were indeed present, but the field was soaked through. The next day’s Brockton Gazette wrote, “[Umpire] Bond looked the ground ov’r, poked the earth with his umbrella, and finally announced that he could not call [i.e., officiate] the game, as the grounds were not in fit condition.”15 What followed was bizarre.

First, both towns’ papers reported that McGunnigle refused to pay Lawrence’s travel expenses on being presented with a bill, as was common practice at the time. Instead, “the men left the grounds in little groups, the Lawrence club taking a barge which was in waiting, and driving . . . to the depot, where they took the 3:20 train for Boston.”16

Neither paper revealed why McGunnigle refused to pay. He may have been miffed, however, by a nifty piece of detective work, related in the Lawrence Daily American: “Some of the Lawrences went under the grand stand [after the game was called] and found a hose covered with mud and water and having every appearance of being used to flood the grounds to prevent a game.”17 The Lawrence paper, loathe to miss out on a comedic opening, deadpanned that “the Brocktons probably intend to use their ball grounds this winter for a skating rink, flooding them with water and letting it freeze over. Saturday was a little early in the season to begin flooding [it], however.”18

The Lawrence team officially disbanded after this debacle, presumably because their contracts had expired as well. Manager Burnham wrote a terse letter to league secretary Wiggin, requesting “an early opportunity to prove these facts [i.e., McGunnigle’s refusal to pay] to the board of directors and [argue] that the Brockton Base Ball club may be expelled from the Association.”19

At the same time, Brockton leveled accusations against both Newburyport, of throwing their last two games against Lawrence, and Haverhill, “of a desire to cheat her [Brockton] out of a pennant.”20 Haverhill representatives had been present at the forfeit in Lawrence and had “denounced the trickery and meanness of McGunnigle in the loudest and most emphatic terms,” according to the Lawrence Daily American.21 Haverhill’s William H. Moody also served as league president. A multitalented man, Moody soon abandoned baseball to dedicate himself to the law and politics. In 1906, after having served as secretary of the navy and U.S. attorney general, he was named to the Supreme Court by Theodore Roosevelt.

If ever a league meeting was needed, it was on October 8, when the team presidents finally got together at the Essex House in Lawrence. The Biddeford Journal, playing the role of impartial observer, had nothing but scorn for both teams involved:

The Eastern New England League is preparing for a monkey and parrot sort of a time at its next meeting. The leading clubs, more intent upon gaining legal advantages than to meet on the ball field, have exhausted the constitutional provisions in attempts to avoid a meeting. Brockton refuses to play games when not ordered by the secretary; failed to appear at the field after agreeing to play; Lawrence went to Brockton to play when the ground was flooded, and Brockton refused to pay them for so doing; and now Lawrence asks for the expulsion of Brockton, and follows this by disbandment of the club. It seems to be a clear case of one’s afraid and the other “darsn’t”—and still the championship remains unsettled.22

Several important issues were on the docket for the meeting. First, Portland’s protested game against Lawrence on September 29, which it claimed was the twenty-first match between the two teams. Second, the contractual status of Flynn, who had been claimed not only by the Metropolitans of the AA but also by McGunnigle himself on behalf of Brockton. Third, whether or not Secretary Wiggin had overexercised his power in ordering the postponed games between Brockton and Lawrence to be played. How these disputes were resolved would go a long way toward determining the champion.

The next day, the Lawrence Daily American pronounced all problems “amicably arranged.” Concerning Flynn, there proved to have been a miscommunication among Brockton management:

Mr. Mills stated that he had protested the game because McGunnigle telegraphed him that Flynn and [Lawrence catcher George] Moolic were under contract with him [McGunnigle]. The matter of whether this was so or not was discussed and [Brockton secretary Bicknell] said they based their information on the statement of Manager Jim] Mutrie,23 of the Metropolitans, and did not claim that Brockton had any hold on Flynn. McGunnigle corrected Bicknell, saying that it was under a belief that they could hold Flynn that they telegraphed Mr. Mills as before stated.24

In light of this confusing development, Mills dropped his protest, and the men moved on to the question of whether Flynn had signed with the Metropolitans. To answer this, they summoned Flynn himself, who averred that “he had signed with no club but Lawrence, and that he had never told any person that he had.”25

In the end, and at Mills’s suggestion, all of the problems were bundled into one elegant solution. Lawrence and Brockton agreed to play a three-game series for the championship—on October 10 in Brockton, October 13 in Lawrence, and October 15 in Boston, if necessary. The clubs further agreed to “waive all protests and matters at present except the eligibility of Flynn. In case Flynn was found to have played while ineligible, the Brocktons [were] to take the pennant.”26 Lawrence re-signed its players, and the recalcitrant foes were finally ready to play ball.

On the field as in the newspapers, Lawrence and Brockton were very well matched. The former team was carried by the 21-year-old Flynn, who had joined the club for the stretch run after playing for Meriden earlier in the year (more on that later). He was the unquestioned ace of the staff and also the best hitter, with a .432 average in 44 at-bats. His batterymate was fellow Lawrence native George H. Moolic, a competent defensive catcher who went by the nickname Prunes. Other standouts included second baseman (and captain) Timothy Brosnan, first baseman Pat O’Connell, and center fielder John Kiley. The team did not hit for much power but was far above average defensively and outscored its opponents by 46 runs over the course of the season. The roster included John Tener, a young Irishman from County Tyrone, who didn’t make much of an impression during his time in Lawrence but did go on to serve as National League president from 1913 to 1918 and as governor of Pennsylvania from 1911 to 1915.

For Brockton, third baseman James “Jumbo” Davis was the centerpiece of a fearsome offense. He later went on to a fairly lengthy career with various teams in the American Association, and led that league with 19 triples in 1887. Ed Crane was another reliable hitter, and Jim Cudworth patrolled center field with grace. The main starting pitcher for Brockton was John Moriarty, and he faced Flynn in the first game of the series.

Brockton drew blood in the first inning of the opener, as first baseman Bill Hawes reached first on a muffed third strike by catcher Moolic, advanced to second on a wild throw by the same, and scored on a passed ball. In the second inning, however, Lawrence put up three runs of their own on hits by O’Connell, Brosnan, and Flynn. Also in that inning, Brockton’s Davis got into a heated argument with the umpire and stormed off the field.

The Lawrence nine continued to add runs incrementally throughout the game. They scored two in the third, one in the fifth on “Flynn’s terrific hit to extreme left field for three bases,”27 two in the sixth, and one in the seventh. Brockton scraped together three more runs, but it was not enough to prevent a 9–4 loss. Flynn allowed five hits, walked five, and struck out nine; Moriarty allowed ten hits, walked three, and struck out seven.

The second game of the series, in Lawrence, was scheduled for October 13, but rain pushed it back two days. Brockton’s loss had evidently not diminished its healthy swagger; in their Lawrence hotel guestbook, the players signed themselves in as “Champions of New England.” The Lawrence Daily American, noting this, dryly compared them to “lads of tender years, who delight to scribble their names on the walls of every conceivable place they enter.”28

When play finally began, Lawrence jumped out to an early lead, scoring two runs in the first on “an opportune hit by O’Connell.”29 In the fourth inning, Brockton answered with three runs of its own on a double by Ed Crane and a balk by Lawrence’s Flynn. In the next two innings, though, Lawrence reclaimed the lead and extended it considerably, scoring five unanswered runs, then four more in the eighth and ninth innings. O’Connell, Bill Conway, and John Burns each recorded multiple hits, Moolic had an RBI double, and Flynn allowed only five hits. Lawrence took the game by the final score of 11–4, winning the threegame series and the pennant.

Afterward, a hastily arranged parade carried the players through the town and dropped them off at the Brunswick Hotel, where they were the object of much speechifying by local bigwigs. “There was a feeling of great gratification at the result of the game expressed in the countenance of each one present, and after the repast cigars were circulated among the guests.”30 Pitcher Dick Conway was presented with a winter overcoat, “with the hope that he would accept it and continue to cherish as kindly feelings toward Lawrence people as they did towards him.” The night wore on, “songs were rendered by several present, and at a seasonable hour the party broke up with Auld Lang Syne, much pleased with the celebration in honor of securing the pennant.”31

As the revelers dined, the scribes at the Lawrence Daily American must have been fairly cackling at their desks. In a swipe at Brockton’s self-styled “Champions of New England,” the next day’s delirious headline read, “HELLO, BROCKTON! What Are You Going to Sign Yourself Now?”32 Along with the recap was a lengthy column of vindictive gloating, aimed primarily at the Brockton Gazette:

Well, Gazette, take it all back and tell your readers you don’t know a little bit about base ball anyway. It is a bitter pill, but you must take it. . . . It is dreadfully hard, but you were, as usual, just a trifle previous, to say the least, and indiscreet beyond a doubt. We pity you, indeed we do. Ta-ta.33

In fact, many different New England newspapers chimed in regularly through the dispute. After the final game, the Boston Globe opined that “the Brocktons won the championship and the Lawrences got the pennant,”34 while the Boston Post wrote:

The managers of the Brockton team may well feel heartily ashamed of themselves. . . . That they lost the pennant is entirely their own fault. Brockton, with the chances greatly in her favor, took just the one course that should have been avoided, disbanded the team and attempted to win the championship by bluff.35

A third Boston paper, the Herald, believed that “in the opinion of a large majority of the base ball public in New England . . . the Brockton club fairly and squarely won the championship on the ball field.”36 To which the Lawrence Daily American, ever judicious, replied: “In the opinion of a large majority of the base ball public in New England, the Herald base ball man has a big head.”37

Incredibly, though, the affair was not yet decided. In a new tactic, Brockton alleged that Flynn and his batterymate, Moolic, had been under contract not with the Metropolitans but with Meriden of the Southern New England League. Both men had indeed played for Meriden earlier that year and joined Lawrence on September 17, only after Meriden folded. According to the secretary of the SNEL, Meriden had disbanded on September 15. According to Meriden’s own secretary, however, that team never actually disbanded officially. A meeting of the Eastern New England League was called on October 28 to settle the dispute.38

In the meantime, some further digging by the Boston Globe showed that on August 12 the Meriden club released all of its players—with the exception of Flynn and Moolic.39 At the same time, however, Flynn was owed $200 by management, which the Lawrence Daily American believed “released him from all obligations to them long before he signed in Lawrence.”40 The SNEL secretary, however, admitted, “I don’t know any rule in our League by which contracts become invalid when salaries are not paid.” In the same telegram, he counted himself among the befuddled: “Lord only knows when the Meriden club disbanded.”41

As October turned toward November, the Brockton Gazette commented that “base ball talk is getting rather wearisome at the present time.”42 Though Brockton had a vested interest in the conversation, many New England baseball fans likely agreed. On October 28, four weeks after the last scheduled game of the season, the league board of directors finally awarded the championship—to Lawrence. At that evening’s meeting, Lawrence’s representatives—Flynn among them—provided proof that not just Meriden but the entire SENL had disbanded by August 15, if not before. League secretary Moody concurred.43 The long, hard season was over, on the field and in the boardroom.

Old habits die hard—the following day, Brockton promised an appeal. “It is ten to one,” the Boston Globe surmised, “that they will never carry out this threat, and a hundred to one that . . . the matter [will not] come before the arbitration committee.”44 Indeed, no appeal was ever filed.

The weather worsened, and, though the principal parties (or, rather, their supporters in the press) continued to snipe at one another, public interest moved elsewhere. Flynn, who had found himself in the eye of a hurricane on and off the field, signed with Chicago of the National League. Lawrence’s manager, Burnham, went to head the new Meriden franchise and was replaced by former Detroit player Frank Cox.

In 1886, the two teams would again battle in the standings, but somewhat farther down the ladder— they both finished over 20 games out of first place. This was in the newly constituted New England League. The Eastern New England League had gone out of business after one season and one of the most heated pennant races in baseball history.

JUSTIN MURPHY is a reporter for The Citizen newspaper in Auburn, New York. He also contributes to the website Seamheads.

Acknowledgments

The author would like to thank Tony Yoseloff and the Yoseloff Foundation for the Yoseloff/SABR Baseball Research Grant that helped make this article possible. Thanks also to the staff at the Lawrence History Center and Lawrence Public Library. Baseball-Reference.com was an indispensible resource for statistics.

Notes

1 Lawrence Daily American, September 30, 1885.

2 Sources disagree on the date of the game and on the identity of the umpires. One source gives the date as August 12. Another source gives the date as August 18 and identifies the umpire as Winslow [Sylvester?]. The Boston Globe of 15 August 1885 refers to the Lawrence–Brockton game of August 14.

3 Boston Globe, August 27, 1885.

4 Boston Globe, August 27, 1885.

5 Boston Globe, August 27, 1885.

6 Lawrence Daily American, October 1, 1885. Quotes from the Brockton Gazette and other regional newspapers, with the exception of the Boston Globe, come from the Lawrence Daily American, which published lengthy excerpts from competing newspapers throughout the season.

7 Lawrence Daily American, October 1, 1885.

8 Lawrence Daily American, October 2, 1885.

9 Lawrence Daily American, October 5, 1885.

10 Lawrence Daily American, October 3, 1885.

11 Lawrence Daily American, October 3, 1885.

12 Lawrence Daily American, October 5, 1885.

13 Lawrence Daily American, October 5, 1885.

14 Lawrence Daily American, October 5, 1885.

15 Lawrence Daily American, October 6, 1885.

16 Lawrence Daily American, October 6, 1885.

17 Lawrence Daily American, October 6, 1885.

18 Lawrence Daily American, October 6, 1885.

19 Lawrence Daily American, October 6, 1885.

20 Lawrence Daily American, October 6, 1885.

21 Lawrence Daily American, October 3, 1885.

22 Lawrence Daily American, October 8, 1885.

23  The manager of the Metropolitans in 1885 was James Gifford. Mutrie, who had managed them in 1883–84, moved to the New York Giants in 1885.

24 Lawrence Daily American, October 9, 1885.

25 Lawrence Daily American, October 9, 1885.

26 Lawrence Daily American, October 9, 1885.

27 Lawrence Daily American, October 10, 1885.

28 Lawrence Daily American, October 14, 1885.

29 Lawrence Daily American, October 16, 1885.

30 Lawrence Daily American, October 16, 1885.

31 Lawrence Daily American, October 16, 1885.

32 Lawrence Daily American, October 16, 1885.

33 Lawrence Daily American, October 16, 1885.

34 Lawrence Daily American, October 16, 1885.

35 Lawrence Daily American, October 16, 1885.

36 Lawrence Daily American October 17, 1885.

37 Lawrence Daily American October 17, 1885.

38 Lawrence Daily American, October 20, 1885.

39 Lawrence Daily American, October 26, 1885.

40 Lawrence Daily American, October 26, 1885.

41 Lawrence Daily American, October 26, 1885.

42 Lawrence Daily American, October 1, 1885.

43 Lawrence Daily American, October 29, 1885.

44 Lawrence Daily American, October 30, 1885.