Evaluating and Presenting Hitter Assessment Data

From January 17th, 2019 – Utilizing Technology to Assess Hitters

As mentioned in my post outlining the how we assess our hitters, having detailed information is great but utilizing it in a training environment is the key.  As we look at a player’s assessment and organize and evaluate the data, we try to create a picture that provides players with the most important info in the simplest form possible.  Overloading young (or any) hitters with a bunch of specific data about their spin axis or rotational acceleration may very well cause paralysis by analysis and detract from them learning to master simple movements and approaches.  However, coaches knowing that a player top-spins a lot of balls and that his ability to rotate is under the typical range for his age level will allow us to program specific drills in order to attack those deficiencies.

In addition, we have been diligent about keeping all of our hitter’s data organized by age and playing level, so comparing a hitter’s info to that of his peers at our facility is another key part of how we inform our hitters.  In our experience, knowing where you stand in relation to your peers, as well as having information about what it takes to play at the next level serves as a powerful form of motivation. This article outlines some of the main things we look to evaluate from a hitter’s initial assessment data.

Raw Numbers Testing Progress and Level Comparison

When we sit a player down for his assessment meeting, we start with looking at the raw information that our evaluation tools have shown us.  Here is a quick breakdown of each metric we have on our report sheet

  • Height and weight: tracking how the hitter is growing and putting on weight
  • Exit Velocity: peak, average and consistency of batted ball speed
  • Launch angle: average and standard deviation of the batted ball angle
  • Peak distance: the farthest ball the hitter hit
  • Average direction: the average direction in which the hitter hits
  • Average spin rate: a good look at how well the hitter squares the ball up
  • Peak and average bat speed: the fastest the hitter swung the bat, and his overall average bat speed
  • Attack angle: average and standard deviation of horizontal angle through the zone
  • Power: peak and average power from Blast sensor, measured in kW
  • Time to contact: average of how quickly the hitter the gets from start of swing to contact
  • Blast Factor: Blast Motion’s overall swing score


It is important for us to understand the peak potential of each player in order to gauge what their ceiling is and how their overall performance relates.  As players mature, train, and guide their focus in the correct direction, peak numbers should go up over time. In this manner, it is important to know that a player’s potential is growing.

Averages and Consistencies

While peak numbers are important in understanding potential, averages and consistencies are probably more important in understanding how players can perform relative to that potential.  Averages are a broad view of how each metric plays over the course of the assessment, while consistency measures how close the average is to the peak. In addition we use standard deviations in some cases to understand consistency.  The consistency of exit velocity can be taken by dividing the average by the peak, because the player’s peak EV is a the absolute desired outcome. The percentage shows us a “grade” of how they make hard contact. Launch angle is a situation where we use a standard deviation, because there is no single optimal launch angle.  If a player has an average 15 degree LA, but the standard deviation is 15, that means he hits a ball at 15 degrees, then 30, then 15, then 0. (Line drive, fly ball, line drive, groundball) This compared to a player with a standard deviation of 5 (15, 20, 15, 10), who would be much more consistent.

With all of these specific metrics measured for the hitter, we can then compare their performance to their previous assessments as well as compare to the average metrics of players at their current playing level, the next playing level, and players their age.  Comparing to previous tests gives us the context of progress made through training, comparing to their peers gives players an idea of where they stand at their current age or level, and looking at the metrics from the next level shows players where they need to improve to get to where they want to go.  All three can serve as a strong source of motivation for players, and give both player and coach a guide to the next training cycle. For the player who is in their first test, all of these numbers simply serve as a starting point.

In addition to the raw batted ball and swing metrics listed above, we can give our players an in depth look at how those balls profile through a more “real life” lense in a more traditional language.  

  • Batted Ball Types:  Percentage breakdown of the different types of balls they hit.
    • Ground balls = <6 degrees
    • Line drives = 6-24 degrees
    • Fly balls = 25-49 degrees
    • Pop ups = 50+ degrees
  • Optimally hit balls:  Percentage breakdown of the four main things we can describe as optimal.
    • Hard hits = balls hit within top 10% of max exit velocity
    • Line drives = balls hit between 6 and 24 degrees
    • Hard hit line drives = balls within top 10% of max EV hit at 6-24 degrees
    • Deep balls = balls hit within 10% of player’s max distance

Balls by field: Percentage breakdown of balls to the pull side, middle of the field, and opposite field.  Rapsodo’s exit direction allows us to sort this data.

For the vast majority of our hitters, our focus is on increasing the percentages of hard hit balls, line drives, and hard hit line drives.  Deep balls are only cited as a focal point if the player’s deep balls are going to do consistent damage at their level. With an understanding of the frequency that these outcomes take place, we are then able to look at the specifics on each of those outcomes and dive a little bit deeper.

The first graph shows each type of batted ball and three specific metrics, Exit velocity, launch angle and attack angle.  We can look at which types of balls have the highest exit velocity, which gives us an idea of where their swing tends to trend.  If the hardest hit balls are too low or too high, we can prioritize making that change. If they are right on, we can place our focus elsewhere.  In addition, we can see if there are large variances in their attack angles in each of these batted ball types, which can give us an understanding of why the contact may be what it is.

The second graph we look at is for the player’s optimally hit balls.  This shows the average exit velocities, launch angles and attack angles of balls hit meeting these criteria.  We can again see about the type of contact a player makes by looking at the average launch angle of their hard hit balls.  In addition, this is where we can get a really good idea of a preferred attack angle for each player by looking at attack angle average on hard hit line drives.  We very often use this as the player’s “target attack angle”, which works well for them as an measured internal guideline during training.

The third graph we look at is the exit velocities, launch angles and attack angles by field.  This gives us a great look into how well a player hits a ball to certain parts of the ballpark, and how their average attack angles correlate with those balls.  Understanding these trends gives us a great way to program different external focuses into a player’s training, like forcing them to hit the ball lower to the opposite field or pull the ball in the air.  The attack angle info allows us to use a Blast sensor in training to give them an internally focused goal (swing at target attack angle) to try and accomplish an external task (pull ball in the air).

The last graphic we look at is the spray chart that Rapsodo produces, which gives some context as to how far and which direction balls are being hit.  This is nicely color coded based on batted ball type can be an eye opener for some guys who think they are hitting “cage bombs” but in reality are hitting mid-outfield fly ball outs.  This is a very simple way for hitters to visually evaluate the quality of their assessment round.

Strike Zone Performance

In addition to batted ball metrics, Rapsodo also provides us with information on where each ball is contacted with the strike zone (or outside of it).  This information paired with the batted ball info and our swing metrics gives us great insight into how each player performs inside the zone. We can break down metrics in a more general way (up, middle, down & in, middle, out) as well as get even more granular by looking at each of the nine zones specifically.  This information allows us to have hitters work on their weak zones in training, as well as highlighting their strengths and being able to build an approach around them. We can also use zone performance information with our uHIT pitch decision program, because knowing where they succeed in their swing allows players to work on hunting their pitch in an informed way.  

Presenting the Information to Hitters

As was mentioned before, dumping all of this information on players at once is not advisable, and starting simple and working our way deeper into the information is the approach we try and take.  In each section of our report sheet, there is an “evaluation” line where the coach can look at the data, and pull out the key points and summarize into a few short sentences. When we sit down with a hitter we start by giving them that brief breakdown, and then allow them to ask more specific questions if they want.  Many hitters will just take the basic evaluation and trust what we have shown them, while others want to look through the metrics more specifically. This is where knowing our guys well comes into play, and making sure they are getting a full understanding of themselves as a hitter while not getting “numbers obsessed” is the goal here.

We also give the hitter a baseline on his performance using the uHIT pitch decision program, as we will utilize this software on a daily basis and we can specifically target and work to improve upon these numbers as well.  uHIT gives us a player’s accuracy and reaction time for both strike and pitch recognition competitions, and we created the AR Number (Accuracy/Reaction Time) as a way to gauge a player’s performance as the two relate.  Ideally we want the accuracy to be as high as possible, with the reaction time as low as possible, creating a larger AR number.  

Blast and Rapsodo provide us with a host of additional metrics on top of the ones listed above, that can provide us with further insight into player’s batted balls and swings.  As a general rule, we keep these amongst the coaches, and use them in player’s programming when we see fit. Again it is very easy to dump all of the provided information on the hitter, but by withholding some of it we try and protect ourselves from doing so.  Occasionally we see something major and share some of these extra metrics with hitters, but this is done on a case by case and need basis.

Analyzing Video

The final part of our assessment evaluation is looking at video of the hitter, which tends to be one of the most important pieces of the puzzle as we get going into training.  As a general statement, most of the issues we see in the batted ball and swing data come from a movement/swing defienciency that we can see when looking at video.  We are able to slow this video down for each hitter and really dive into what we see they need to improve upon mechanically in order to get better results.  In our experience, young hitters are very visual in their learning style, and looking at the video allows them to grasp concepts that we will discuss in order to put them into action in our training.  

For new hitters, we spend a lot of time really breaking down what we are looking for in a swing, using major league hitters as examples in order to convey specific swing principles.  This is extremely important for us to lay a foundation for a training by giving the hitter an understanding of what a swing should look like.  For returning hitters who have gone through a training cycle with us, we encourage them to analyze their own swings at this time, drawing on focuses from the last training cycle and comparing to video from their initial assessment.  This gives the hitter ownership of his progress and a deeper understanding of the principles and the continued steps that need to be taken to improve.  

Moving Forward into Training

As we finish up going through the assessment process with each hitter, we leave them with a few basic metrics that we use frequently in our training sessions.  The following metrics provide players with context as we work through swings and competitions in the small group and individual settings.

  • Target attack angle: The average attack angle,usually from hard hit line drives.  This gives our hitters a general number to work towards when we use Blast sensors in training
  • Hard hit number: Simply 90% of their peak exit velocity.  Takes the guesswork out of whether or not they really hit a ball well
  • Average power:  This gives us a bseline of how “on time” a hitter is, and we can use this number as a gauge in training
  • Launch angle range: The target range that we want our guys working based on the assessment data.  This is usually inthe 10-20 range, but guys with a bit more pop can work higher.

This concludes the very imporatant evaluation and presentation portion of our hitter assessment, in the next post I will talk about simple ways we work to use this data on an everyday basis with our hitters, followed by some of the trends we have seen with our hitters as we have compiled the data over the course of the winter months.  

Ryan Serena
Rogue Baseball