Juiced Ball Economics by Matt Malkus August 12, 2019 Look, another article about the juiced ball! I know, I know. At this point, the narrative of the juiced ball has been written from many angles. (For anyone reading this who is somehow not familiar with that narrative, Jay Jaffe’s piece from June is replete with graphs, tables, and external links.) As fans, this narrative is interesting, as it contextualizes the product we see on the field. It feels like there are more home runs — hey, there are more home runs! It’s human nature to wonder why. Baseball writers have tough jobs, and they need something to write about. Many baseball writers have tried to tackle the “why” to satisfy both reader curiosity and their editor’s article quota. While this narrative is interesting for fans, for teams, it’s of massive importance financially. Teams have payroll budgets, and presumably, some of those teams will have room in those budgets for free agents this offseason. Teams also have players under contract who are eligible for arbitration, on whom the team must place valuations in advance of submitting a figure to arbitrators or deciding to non-tender the player. In short, teams have financial decisions to make, and they rely on all the information at their disposal to make them. Wasted dollars represent opportunity cost more than anything, in a league where advantages are razor thin and random variance plays such a key role in success or failure from year to year. The “juiced” ball, then, represents a potentially large bit of noise for teams looking to isolate the signal. While Rob Manfred has repeatedly denied an intentional change to the ball, you’d have to think that the league is at least considering some counter-measures, including intentionally “de-juicing” the ball, to return home run rates to historical norms. Teams that are looking ahead to the 2020 season for budgeting and talent evaluation must do so with such a change in mind, as one possible future state of the world. The relevant question for teams then is this: What players have benefited the most from the juiced ball? If a player’s true talent level at the plate would result in 10 home runs per season at historical norms, how many home runs do the changes to the baseball result in that player hitting in the current environment? Are those gains larger for players who already demonstrated some power and are now, in an illusory way, showing more of it? The answers to such questions may drive player evaluation for teams facing uncertainty about what future league-wide home run rates might be. One simple way to approach this is to look at the distribution of HR/PA rates. Since 2019 is still ongoing, I’ve looked at data from the first half of each recent season, and I restricted qualifying hitters to 200 PA. I’ve included years back to 2014, mostly to demonstrate how remarkably similar 2014 and 2015 were, and the subsequent changes post-2015. So home runs are up across the spectrum, from light-hitting middle infielders to all-or-nothing mashers. This is not very exciting or interesting – we already knew home runs were up! Big deal. B what we’re really interested in is the distribution of home runs across the player pool relative to the league average, or alternatively, relative to replacement level. It’s hard to say what “replacement level” means when trying to isolate a single skillset (hitting home runs), so we’ll use the league average here. League-average HR/PA rates for the first half of each season in the sample are shown below. HR/PA, 1st Half Year 1st Half HR/PA 2014 2.3314% 2015 2.5233% 2016 3.0380% 2017 3.4169% 2018 2.9790% 2019 3.5809% We can then take each player-season and compare the difference in that player’s HR/PA rate to the league average, as a percentage of the average. The first graph is a bit noisy but (hopefully) does a decent job of demonstrating 2015 as a representation of historical norms; the graph below plots the distribution of percent difference from league average home run rate for 2019 versus 2015 without the intervening years. When presented this way, the data paints a picture of a more homogeneous universe of baseball players compared to just four years ago. Home runs are up, yes, but they are particularly up in the lower half of the distribution. These are players who would have been content with their five home runs per year, slick defense, and above-average contact skills, but they are now providing their share of pop from the bottom third of the batting order. Meanwhile, prolific home run hitters — those in the top quartile — are now less prolific as compared to their peers. The ball is still helping them hit homers too; it’s just that the gap has closed substantially between the “haves” and the “have-nots.” And while there is likely some displacement at work here — teams are less willing to give an ever-more-valuable roster spot to a light-hitting middle infielder like Erick Aybar in the age of expanding bullpens and openers — the timeframe is short enough to show that individual players have benefited, so this isn’t just teams rostering a different blend of skillsets than before. Notable HR/PA Increases, 2015 vs. 2019 Player 2015 1st Half HR/PA 2015 Percentile 2019 1st Half HR/PA 2019 Percentile Dee Gordon 0.2646% 3.29% 1.1628% 4.42% Jose Iglesias 0.3534% 4.12% 1.7123% 10.84% Andrelton Simmons 0.8547% 11.93% 1.7391% 11.65% Elvis Andrus 0.8287% 11.52% 2.2792% 18.07% Jean Segura 0.9868% 18.11% 2.8169% 28.11% What does this mean for teams and their valuation models? As an example, let’s say you have an arbitration-eligible player at 3% HR/PA in 2019. In a full season with 600 PA, that player would hit 18 homers, which is a pretty respectable number in a vacuum. However, a player who was similarly competent relative to the league would have hit just 11 homers in the pre-juiced ball era, assuming they remain at roughly the same percentile of the HR/PA distribution. Arbitrators have historically awarded arbitration salaries based on basic counting statistics, rather than more advanced measures which take run environment into consideration. The baseball, certainly, contributes to the run environment, but the player has the advantage of using arbitration salary comps from previous, less homer-happy years to justify a higher salary, despite that home run total representing a merely above-average player instead of a great one. Notable First Year Arbitration Eligible Players Player 2019 1st Half HR/PA 2019 Percentile 2019 Season HR Pace 2015 Season HR Pace Adam Frazier 1.1799% 4.82% 7 3 Giovanny Urshela 2.8226% 28.92% 17 10 Willy Adames 3.0030% 32.93% 18 11 Omar Narvaez 4.8780% 71.49% 29 21 Max Muncy 6.1453% 89.56% 37 29 Finally, there is free agency. With free agency moving at a glacial pace in the past two offseasons and tensions rising between labor and ownership, any intent to counteract the current home run rates made public prior to the new year would sow yet another doubt in the minds of executives who are more risk-averse than ever in the free agent market. How this will play out remains to be seen, but between optimizing the product on the field for maximum entertainment value, maintaining the sanctity of baseball’s vaunted record books, and the economic impact of changing equipment as fundamental to the sport as the ball itself, Rob Manfred and MLB have quite an array of factors to consider.