Over the past 10 years the advancement of new technology has produced a myriad of new cutting-edge baseball statistics and Major League Baseball (MLB) has allowed this big data to take over the league. This tsunami of new data and metrics has been referred to as “revolutionary”. But in reality, these data-driven analytics and the over-reliance upon them have catalyzed the gradual de-evolution of hitting within the MLB and beyond.
This data driven approach in baseball now prioritizes factors such as “launch angle”, “backspin”, and “exit velocity”. Do you think Hank Aaron worked on launch angle, backspin or even exit velocity? Simple answer, no. This didn’t enter the minds of the game’s greatest hitters until 2015.
In 2015, Statcast analytics became available in all major league stadiums and the baseball industry proclaimed these new analytics would “fundamentally revolutionize” hitting and the league. But in hindsight, it is clear that this new big data has only served to weaken the game overall. Baseball now spends so much time fascinated with the countless analytics available that it has diminished the art of hitting.
While MLB’s analytics “revolution” has verifiably led to more home runs being hit, as more and more players are forced to tailor their hitting style to the metrics directly, it has killed almost every other offensive stat that matters. Today’s hitting training is almost exclusively based on analytics. Players today are judged predominantly on “launch angle,” “exit velocity,” “batted ball spin,” and fly balls vs. ground balls, all of which is an unprecedented amount of information that leads directly to “analysis paralysis.”
As a direct result, batters are being trained to artificially manipulate their mechanics to increase these four metrics because all four metrics are geared toward home-run production. This entire line of thinking has diminished the game of baseball by making hitters one-dimensional. In tandem with this, this analytical approach to hitting has also directly contributed to why pitchers have found such phenomenal success over the past decade. Before 2015, each batter would bring their unique and distinct style to the plate, but now, they all come sporting the same priorities. Batters either swing for the fences or strike out, making it much easier for pitchers to exploit.
Just because a specific desirable outcome can be quantified with analytics, like a home run, it doesn’t mean a player should re-invent their mechanics to achieve it. It has become painfully apparent that analytics have replaced common sense in baseball over the past decade, and it is to the sport’s detriment. This over-reliance on tech-driven analytics, teams have allowed this machine mind that understands less about the sport than humans do to dictate how we play the game. Data should not be the sole decision maker, which baseball now does. It should be used as one piece of the puzzle to help humans make the right decisions.
The “Moneyball” analytical revolution showed us one important thing: The number one concern offensively for a team needs to be scoring runs in order to win games. While there are countless stats for hitting, at the end of the day it comes down to this: “Is a team getting men on base and are they scoring runs?” Look at the cause and effect and see how today’s one dimensional “going deep” hitting training has affected the players and the game itself.
The 2019 MLB season featured the most home runs hit in a single season, with 1,083 more home runs hit versus the 2000 MLB season (before the analytics revolution). Yet, despite this fact, there were 1,505 more runs scored in 2000 than in 2019. Even with over 1,000 more home runs hit, the 2019 season fell over 1,500 runs short of the 2000 season.
This issue has only grown more comically exacerbated over time. In 2023, only 175 more home runs were hit than in the 2000 season, yet a whopping 2,539 more runs were scored in 2000.
Over this same time frame, the number of runs scored per home run has also decreased. Batting averages have plummeted, and both OBP and OPS have tanked. The most staggering stat is the number of strikeouts. In the 2000 season, there were 31,356 total strikeouts. In 2023, there was an over 30% increase, resulting in 41,826 strikeouts.
As an example, Tony Gwynn, who played before the “revolution”, worked on one thing; making solid contact. In his 20 year career, he has one of the highest career batting averages of all time at .338. In those 20 years he only struck out 434 times. Plus, he walked almost twice as much as he struck out. In contrast, Josh Donaldson, a “revolution” era player who worked on launch angle, played 15 years and was touted as a “power hitter”. He was very vocal about the need to hit fly balls. Yet, in those 15 years he hit 30 or more home runs in only 4 of those 15 years. He hit a career 279 HR’s which equals 18.6 HR’s per season. His career batting average was .260 and struck out 1221 times – which is almost twice as many times as he walked. Donaldson played 5 years less than Gwynn but struckout close to three times more than Gywnn and Donaldson had a much lower career batting average. He was an “elevate to celebrate” player. Those aren’t numbers worth celebrating.
This over-prioritization of garnering home runs has come at the cost – more strikeouts, lower batting averages, less players getting on base and less runs being scored.
Baseball has lost its balance. While understanding data is crucial, the current “data-driven” approach prioritizes achieving specific metrics like launch angle over fundamental hitting mechanics and a team-oriented strategy. This rigid narrowed focus ignores the fact that hitting success hinges on pitch type, location, and a hitter’s ability to adapt. It also removes the human element, which hinders a player’s natural movement and timing. Ultimately, this emphasis on power-hitting and individual statistics detracts from the true essence of the game: working together to win through smart baserunning and timely hits, not just home runs.
Analysis from fangraphs.com: “It’s no surprise that line drives are much more likely to become hits when compared to ground balls and fly balls. But what will surprise most, fly balls are the most likely to be turned into an out. Furthermore, the stats show that walks actually have a bigger impact on scoring than fly balls.” It’s time to refocus on making solid contact. Metrics like exit velocity and contact rate offer a clearer picture of a hitter’s success than chasing spin rates or unrealistic launch angles.
Prioritizing solid contact over launch angle or batted ball spin rate will lead to more productive at-bats with fewer pop outs, fly outs, ground outs and strikeouts. By embracing a data-informed approach that prioritizes solid contact and smart baserunning, will score more runs and baseball can rediscover the beauty of strategy and teamwork that has made the game so special for generations. To work with a coach who understands the data and practicality approach, book a slot to work with Coach Matt in person or virtually.
