There are many types of hitters that have had success in baseball history. There are hitters with light-tower power like Giancarlo Stanton and players with exceptional bat control like Tony Gwynn or Ichiro Suzuki. Not many people can hit the ball as hard as Giancarlo Stanton, so many coaches and advisors instruct their players to focus on hitting the ball hard consistently instead of maximizing their power output. Is this good advice? Is it possible that consistent hard contact can overcome a player’s power deficiency?
To answer this question, I collected batted ball data from the 2019 and 2020 seasons from Baseball Savant and found each batter’s maximum exit velocity. I am working under the assumption that a player’s maximum exit velocity is a suitable facsimile for raw power. I then tabulated how many times a player’s exit velocity was within 90% of his maximum exit velocity and divided it by the batted balls put in play that registered an exit velocity reading. I call this new stat exit velocity efficiency. I chose the 90% threshold, because the lowest maximum exit velocity readings in the Majors for qualified hitters is around 100 MPH and I believe that 90 MPH is the lowest reasonable threshold for what qualifies as a hard-hit baseball. Next, I limited the dataset to include players that have had over 100 batted ball events combined between the 2019 and 2020 seasons. This left me with 449 Major Leaguers to analyze.
The first thing I wanted to do was compare a player’s exit velocity efficiency and his maximum exit velocity to a performance metric to help determine which statistic has a stronger relationship with hitting performance. I believe that wOBACON is the best option for a performance metric, because it focuses solely on balls in play. I am choosing to ignore other factors like plate discipline and contact rate for simplicity, but these are important aspects of hitting that I will explore later.
These scatter plots show that there is a far stronger relationship between maximum exit velocity and wOBACON than there is between exit velocity efficiency and wOBACON. The former has a Pearson correlation coefficient of 0.55 and the latter has a 0.03 Pearson correlation coefficient indicating almost no relationship at all.
Why is the relationship so low for exit velocity efficiency? It is because players with exceptional raw power do not need to consistently hit balls over 90% of their maximum exit velocity to be effective. Someone who can hit the ball over 118 MPH, like Aaron Judge, have a far greater margin for error for their batted balls than someone like Billy Hamilton who has difficulty reaching 100 MPH. Since exit velocity efficiency is based on each player’s individual maximum exit velocity, it makes sense that players with different maximum exit velocities and similar exit velocity efficiencies would have vastly different batted ball results.
For example, Mookie Betts and Tony Kemp both have an exit velocity efficiency of 33%, but Mookie Betts has a maximum exit velocity of 109.3 MPH compared to Tony Kemp’s 101.4 MPH. Kemp’s wOBACON registers a .299 while Betts has a more robust .428. This is all just a long way of saying that exit velocity efficiency on its own does not have a strong correlation with batted ball success.
Even though maximum exit velocity has a strong relationship with wOBACON, there are still several players that do not possess elite power that are highly effective hitters and there are some hitters who have power but are not the most productive hitters. A great hitter needs to have both power and efficiency, but one usually comes at the expense of the other. What is the best ratio to maximize a player’s performance? Is there a way to identify and classify these players to help them realize what style of hitting works best for them?
K-Means Clustering
I decided to use a machine learning technique called k-means clustering to group the players by their maximum exit velocity and efficient exit velocity readings to determine which hitting approach produces the best results on average. I found that there are five distinct groups of hitters and each group’s mean performance can be found in the table below along with the cluster plot and a review of each group’s results.
Group 5 – Great Power, Below Average Efficiency
This is the most successful group on average and they represent players with the most power. They trade some exit velocity efficiency for power, but their power helps overcome their lack of efficiency in general. This group has the highest wOBACON, wOBA, and wRC+ on average, but a density plot will provide more information as to the distribution of talent. Since each group’s order of success is the same regardless of which offensive metric being chosen, I will be using wRC+ for each density plot moving forward. The metric is easier to interpret and it incorporates more aspects of hitting than batted ball outcomes alone.
There appears to be some risk in this group with many players performing below the mean value. It seems that the extraordinary hitters are propping up the group’s wRC+ average, but there are plenty of players that have issues making consistent contact dragging down their overall value. Players like Mike Zunino and Gregory Polanco have good wOBACON numbers, but their swing and miss issues are too much to overcome to be considered good hitters.
Group 2 – Good Power, Good Efficiency
This group represents the players that do not have top of the scale power but make up for it by being more efficient in their contact quality. The top performers in this cohort are players that can combine their contact abilities with exceptional plate discipline like Juan Soto and Freddie Freeman.
This group has a higher distribution of good hitters, but they do not have the top tier talents to raise the mean wRC+ that the previous group did. This group may not have as much upside, but the floor appears to be a bit higher than the Group 5 hitters.
Group 4 – Great Efficiency, Just Enough Power
Group 4 has a much lower maximum exit velocity than the previous two groups, but they are by far the most efficient group. The hitters that have success in this group are players like Alex Bregman and Anthony Rendon. Bregman and Rendon consistently elevate the ball and limit their swings and misses. Therefore, their profile is effective even though they have a lack of raw power.
This is the first distribution chart where the peak is below 100 wRC+ and it shows how difficult it is to be a great hitter without big raw power. It is still possible, but the margin for error is much finer.
Group 1 – Good Power, Below Average Efficiency
This group is the first to have a below average wRC+ collectively. They also may be the most frustrating. Group 1 is full of players that have comparable raw power to Group 2, but not Group 2’s efficiency.
Group 1 may be the most frustrating, but they are also the most tantalizing. Group 1 hitters have the raw tools necessary for success and it is possible that with more seasoning and a refined approach they could improve their efficiency and become more like the hitters in Group 2.
Group 3 – Good Efficiency, Not Enough Power
This final group is littered with players that rely more on their defense and versatility than their bat to provide value to their club. Players like catchers, middle infielders, and fourth outfielders. Group 3 has the lowest wRC+ and it seems that most of these players lack the physical strength needed to be considered an elite hitter.
This group may have the worst results overall, but all hope is not lost for this type of hitter. Jeff McNeil, Tim Anderson, and Marcus Semien have all recorded a WRC+ over 120 over the last two seasons, so it is possible to succeed with this profile.
Conclusion
My cluster analysis shows that it is possible to be a successful Major League hitter as a member of any group, but it is clearly beneficial to have the ability to hit the ball hard. Both raw power and efficiency are essential to hitters, but if I had to choose which is more important to a hitter’s success, I would choose raw power. Consistent contact is useful, but if a player’s raw power does not meet a certain threshold there is little chance that he will be a productive Major League hitter.
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