Perspective of Detroit Tigers Pitching Coach, Collin Murray and Boston Red Sox Hitting Coordinator, John Soteropulos
With new metrics FINALLY being introduced by Baseball Savant/Statcast such as bat speed, it makes the metric a bit more real to some that didn’t believe it was important. Is having bat speed the only important thing, no, but it’s good to have in a sport where every technological update has seemed to benefit pitchers and helped them increase velocity, overlay pitches and be surgical with off speed stuff. If you don’t believe that then you have been living under a rock the past few years!!
Suspect baseballs, juiced radar guns, pitch com, the sticky stuff (that nobody uses), and hitter hot and cold zones have played a huge role on keeping the pitchers ahead of hitters. However, hitters now have the ability to easily see pitch profiles using data to identify spin rate, vertical and horizontal break for pitches and what pitchers are trying to achieve against hitters. Data analytics has been used as a bridge to shorten that gap and train hitters against opponents and better prepare them day in and day out.
One of the best in the business at preparing hitters is Boston Red Sox Hitting Coordinator John Soteropulos, a Driveline alumni who understands metrics. So, I asked him the following question for his hitting coach perspective.
QUESTION: Has data analytics helped hitters even out the playing field in a pitcher friendly game, or has it increased the separation to keep pitchers a step ahead?
ANSWER: “I would break this answer down into 3 parts.
1. Data analytics has helped hitters identify which parts of their game are their strengths and which parts of their game they need to work on. Accurate diagnosis through objective information has allowed hitters to design and execute more targeted training environments.
2. Game representative training environments for pitchers has historically been able to replicate the game closer in their training with bullpens, trackman, rapsodo, and radar guns. In the past, hitting training mostly consisted of coaches throwing batting practice at 50mph from 30ft away. With new pitching machines getting more advanced, hitters can now train at game like velocities and intent levels. By solving the same problem in practice, hitters are now more prepared to solve the same problems in the game.
3. Data analytics has helped hitters target and improve the right areas and which areas of performance are the most important. Similar to answer number 1, by knowing what areas play the biggest part in successful performance, they can work on improving those areas in their training.”
Training environments for hitters can now mimic game like pitching using real time data and technology that can provide it.
On the flip side of hitting coaches, there are also pitching coaches that are increasing their value by preparing hitters also. How can that be?? I asked the same question to Detroit Tigers Pitching Coach Collin Murray, a data analytic master that is an expert in data visuals and using data to create a picture for pitchers and apparently hitters also.
Question: Has data analytics helped hitters even out the playing field in a pitcher friendly game or has it increased the separation to keep pitchers a step ahead?
Answer: “I’ve seen it help hitters a ton – I’ve literally done a reverse engineering session with hitters based on pitchers they’ll face and how we can use their data against them so to speak.”
If there is anyone that understands pitching metrics, it’s pitching coaches. Their ability to double as hitting coaches to prepare hitters for what they will face is a cheat code.
Organizations that are finding the best ways to make use of their data analytic savvy coaches are maximizing their growth opportunities.
To conclude, I don’t believe that hitting will ever be at the same level of pitching with data analytics, but I do believe that hitting coaches using data analytics as a learning and teaching tool will not only last longer in the game but will make the greatest impact on players.

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