As the 2021 season begins, the Chicago White Sox are gearing up for one of their most competitive seasons in recent memory. Over the last two offseasons, they acquired some much-needed veterans in Dallas Keuchel, Lance Lynn, Yasmani Grandal, and Liam Hendriks. However, the bulk of their team comes from their near-unrivaled young talent. This year, they’ll have former/current star prospects Lucas Giolito, Luis Robert, Michael Kopech, Garrett Crochet, and Nick Madrigal getting sufficient major league service time.
Among the firepower in their young depth, Madrigal stands alone in his skillset. His tools echo the sentiments of a bygone era in Major League Baseball. He’s the antithesis of the booming power and great walk rates that are dominating evaluators’ checklists more and more in the modern era. In his 2020 season, he posted a .340/.376/.369 slash line for a 112 wRC+, and .332 wOBA (.314 xwOBA) in 109 PA. Due to his stunningly low strikeout and walk rates of 6.4 and 3.7, respectively, 95 of his 109 PA ended in batted ball events (BBE). Coupled with a dreadful .029 ISO, his 112 wRC+ seems completely unsustainable.
Despite the small sample, it matched up strikingly well with the profile that evaluators had given him: a small but rowdy hitter who’ll almost always find the ball on the bat without much lift. That’s not exactly the profile that fans would expect teams to gamble on with the fourth overall pick in the MLB draft. And yet, here the White Sox are with Madrigal as their starting second baseman among a powerhouse of imposing names.
Madrigal’s perplexing talent presents a fascinating quandary. It’s strikingly uncommon to witness a player have both an unprecedented hit tool and unprecedentedly poor batted ball quality with the added expectation of it continuing. However, with the ubiquity of data analysis, we can discover so much about the intricacies of player talent. And Madrigal, despite not being one of its darlings, is no different.
The concept of quantifying a player’s hit tool is a bit novel in the data analysis community. While we have Barrel%, Exit Velocity, and HardHit% for analyzing a player’s power, we have far fewer metrics for their hit tool. However, one of Baseball Savant’s quality of contact measurers, Flares/Burners%, sports an adequate, positive correlation to AVG. Madrigal’s teammate, Tim Anderson, ranked among the leaders in his breakout, batting title-winning 2019 season. Madrigal fared well in the stat last season, finishing 22nd with a percentage of 29.2 among every hitter with a minimum of 90 BBE.
Madrigal’s Flares/Burners% provided a satisfying conclusion on its own, but it struck me as underwhelming for a player as unique as he is. It seemed implausible that a hitter could amass a .340 AVG without any barrels, solid contact, and a Flares/Burners% that didn’t break new ground. Motivated to uncover more yet uncertain where to look, the adage of a strong hit tool rang through my head: hitting the ball to all fields.
To examine this possibility, I took advantage of Baseball Savant’s hit coordinates, which track every BBE on a two-dimensional plane. Every mapped event in 2020, when plotted, uncoincidentally forms the shape of a baseball diamond.
For this experiment, I focused on the standard deviation of the x-coordinates (hc_x). Essentially, a wider distribution would mean that a hitter has a huge range across the field for their BBE and vice versa for a tighter distribution. Theoretically, being able to hit the ball to all fields—and thus controlling a wide coordinate distribution—should result in a higher batting average.
The results were promising. Indeed, a wide distribution of hc_x did sport a positive correlation to batting average on contact (BAcon). BAcon works better than AVG in this scenario because the standard deviation of hc_x and BAcon aren’t affected by K%, BB%, HBP%, etc. like AVG is. When comparing a data frame from 2019, the two variables had a Pearson correlation coefficient (r) of 0.386.
There were some cases from this research that warranted a case study of their own. Freddie Freeman—who posted career highs in wOBA and xwOBA in 2020—had the third-highest distribution of hc_x at 47.7 among every hitter with at least 90 BBE. He also had one of the tightest distribution of launch angles at 23.6, which also fares well for AVG.
While the results back up my hypothesis, they ultimately left me with more questions than answers. Madrigal’s distribution of hc_x was the lowest of any hitter in the sport at 31.4. This was dumbfounding, especially considering that it’d seem to hit a majority of balls to one area would allow opposing defenders to position more effectively. And yet, Madrigal wasn’t shifted once by opposing teams last season. I was, in all honesty, more lost than I’d been to begin.
As I continued to ponder that conclusion, I noticed something about Madrigal’s spray chart: a large portion of his BBE were hit to the opposite field. This is where the average of hc_x emerged as a variable of interest. This time, I was focused on hitters who averaged significant opposite-field contact. In 2020, hc_x ranged from about 0 to 250, so I split them down the middle at 125 to separate handedness. An average higher than 125 signifies pull range for left-handed hitters and an average lower signifies the same for right-handed hitters.
As expected, the hitters on each side were majority righties or lefties. Some intriguing names—righties or lefties who averaged opposite-field contact—were DJ LeMahieu, Yandy Díaz, Raimel Tapia, Luis Arraez, and, of course, Madrigal, all of whom had AVG above .300. He averaged a hc_x of 133.6 which, out of 123 hitters who averaged above 125, ranked 36th. That’s an impressive feat for a righty.
While Madrigal’s average was impressive, it fared well below Díaz and LeMahieu’s 140.6 and 140.1, respectively. So, for an additional measure, I took the percentage of a hitter’s BBE that fell into the hc_x range of 125 to 250. At the top of the list are lefties who pull a majority of their BBE, such as Kole Calhoun, Brandon Crawford, and Kyle Schwarber. Madrigal hit 63.5 percent of his BBE in this range. Not only was this the highest of any righty in the sport, but it was also the 28th highest out of 230 hitters.
Madrigal’s percentage may seem confusing given his average compared to LeMahieu and Díaz. However, it’s a testament to his aforementioned tight distribution of hc_x. The standard deviation of anything works around the average, so Madrigal having a tight distribution meant that most of his BBE were clustered in the opposite field. So, as it turns out, his tight distribution benefits him after all.
With these metrics in play, Madrigal’s .340 AVG becomes more reasonable. However, that’s not all that makes up that outstanding number. Another prominent factor towards his success is his plate discipline or lack thereof. AVG takes into account every AB, which includes strikeouts. Madrigal’s unprecedented 6.4 K% ranked the second-lowest of 310 hitters last year. A low K% allows a hitter to translate their BAcon to AVG with little difference, so Madrigal’s low K% works significantly in his favor.
Madrigal’s proficiency for opposite-field contact could contribute to him not being shifted at all last year as well. Since shifting has become more common—with the league-average Shift% last year being 34.1—it’s surprising to see a player work against that trend. And yet, Madrigal doesn’t seem to stand alone, as the aforementioned LeMahieu, Díaz, Tapia, and Arraez all had extremely low Shift%. It seems that, as a hitter can frequently hit to the opposite field and thus control their hit distribution, they’re shifted less as they can adjust to how opposing defenders play them far more effectively than normal.
Madrigal’s opposite-field contact also gives credence to the idea of sustainable xwOBA over-performance. Generally, wOBA-xwOBA has a weak correlation year-to-year, hence why extreme highs or lows are considered to be lucky or unlucky. Madrigal’s .018 wOBA-xwOBA makes sense, as balls hit to the opposite field generally have weaker exit velocities and launch angles than pulled balls. Therefore, as a player controls their opposite-field contact, they should be able to sustain an otherwise lucky xwOBA over-performance.
It’s difficult to imagine a player like Madrigal ever prospering in the modern MLB. With the data available to teams, we know that what’s beneficial to hitters – making hard contact and drawing walks – stand out as Madrigal’s primary weaknesses. Hence, it seems more and more implausible for a team to choose him as their fourth overall draft selection as the White Sox did. And yet, Madrigal has soared like Superman through Statcast’s unconventional data points, creating a surprisingly successful profile.
It’s ignorant to assume Madrigal’s weaknesses won’t hinder his offensive ceiling. It’s impossible to see immaculate numbers from a hitter with a great hit tool and terrible power. Still, Madrigal’s found his niche among the MLB’s top-notch class of players. And, as he matures into his prime, there’s no reason to believe he’s not going to take full advantage of his unique gifts.
