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Steve Nagy

Blast Motion Correlations

Updated: Nov 2, 2020

Below is a correlation matrix I put together to determine if any Blast metrics had a relationship, either positively or negatively. Prior to putting this together, I thought it would be valuable to know two main things; 1) If we focus on improving one of the metrics, will that have a negative effect to another? 2) Would it be possible to "kill two birds with one stone" and improve two metrics by implementing drills and focusing on just one?


Below is the correlation matrix.


If you have a difficult time seeing the numbers, know that the darker the shade of blue or red, the higher the correlation. The darkest shade of blue being a perfect positive correlation and the darkest shade of red being a perfect negative correlation. It is important to note that the p-values are not included, which basically means that without those values, we cannot say for certain that a metric increasing or decreasing caused the increase or decrease in another. In order to be confident about this matrix, p-values need to be below .05, which means you have 95% confidence in your data. Additionally, in order for there to be a correlation worth looking into further, there should be an absolute value of at least .5, meaning greater than .5 or less than -.5. These potentially significant values are circled. A correlation of 0 means the metrics have no relation to each other.


I am going to ignore the values for the Plane Score, Connection Score and Rotation Score because they are just based off the other metrics and our coaches would never say to "let's focus on the plane score." We would focus on On-Plane Efficiency instead. The same can be said for Peak Hand Speed and Power. I feel Time to Contact is important, but we typically do not focus on it because the measurement is so small and carries many decimal places that do not show up on the app. I went into a little more detail about what metrics we do look at in the hitter development post.


Early Connection vs. On Plane Efficiency


If nothing else, this section is what you should take away from this post. Due to Early Connection and On Plane Efficiency having a moderately strong negative correlation of -.53, we further evaluated how these two metrics moved together. We found that some players had correlations much stronger than that, and others much weaker. For the ones that had low On Plane Efficiency, we looked directly to what their Early Connection scores were. Typically players with high Early Connection (above 100) have low On Plane Efficiency. The relationship is depicted below is for a single player whose correlation coefficient was -.63.



This particular player had a drastically high Early Connection and low On Plane Efficiency. We determined that the best way to improve his plane would be to improve his Early Connection. On the chart below, notice how Early Connection and On Plane Efficiency move in opposite directions. As Early Connection decreases, On Plane Efficiency increases and vice versa.

In terms of why this is the case, the relationship makes a lot of sense. If a hitter's bat is too vertical when they initially start their downswing, entering the swing plane early and staying on that plane will be very difficult to do. One of the great parts about this realization is that it once again proves how there is more than one way to make an adjustment. While we had heard of specific drills to improve both of these metrics, understanding that improving one might help improve the other presented the opportunity to focus on one metric and those drills rather than both. Instead of focusing on something during the swing, we can focus on the beginning on the swing.

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