### The Issue With Pitch Counts

As past baseball research discovered the connection between high pitch counts and increase in injuries to pitchers and loss of effectiveness, more and more attention has been paid to tracking the pitch counts of pitchers across all levels of baseball. Any baseball fan, casual or hardcore, would be hard pressed to watch a baseball game being telecast without some mention being made of how many pitches have been thrown by a particular player with one hundred pitches being the benchmark for when many people think the manager should start thinking about taking the pitcher out of the game. While tracking pitch counts does represent some progress in following the game of baseball, no longer is it enough and it is time for everyone, who considers himself or herself to be a baseball aficionado, to start paying more attention to how many pitches are thrown per inning.

Total pitch counts, like other counting statistics, are set up to deceive. Simply knowing that a pitcher threw 112 pitches tells nothing. We still need to know how the pitcher arrived at that number of pitches. Did the pitcher throw a complete game or did his manager foolishly allow him to throw 112 pitches in only five innings? Furthermore, we are unable to make any sort of educated guess at how well the pitcher pitched. However, if we had known how many pitches per inning had been thrown, no chapters would be missing from the story we could tell.

In order to illustrate how much more important pitches per inning are than total pitch counts, I took, for the 2007 season, the five pitchers with the most starts from each of the thirty baseball franchises and ran correlations that allowed me to discover how closely tied pitchers per inning and total pitch counts are to batting average, on-base percentage, slugging average, gross product average (OBP*1.8+SLG/4), fielding independent ERA, strikeouts per nine innings, walks per nine innings, and home runs per nine innings. When there were two pitchers for a team that had the same number of starts, I used the statistics for the pitcher with more innings as a starter.

Overall, the correlations were overwhelmingly stronger for pitches per inning pitched to the aforementioned eight statistics than they were for total pitch counts. Of the eight baseball statistics I used for comparison, total pitch counts only had a stronger correlation for the category of home runs per nine innings (.187 to .148); that was also the closest any of the correlations were to each other. Decisively would be the operative word to describe the victory pitches per inning had over total pitch counts.

Individually, it was much of the same story. Of the 150 pitchers I looked at, only ten (Randy Wolf, Jorge Sosa, Miguel Batista, Justin Germano, Kyle Kendrick, Vicente Padilla, Daisuke Matsuzaka, Gil Meche, Brian Bannister, Nate Robertson, and Matt Garza) had five or more of the eight statistics that were more strongly correlated with pitch counts than pitches per inning.

As the average of 16.1 pitches thrown per inning for the 150 pitchers demonstrates and any pitcher will also tell you, pitchers are only conditioned to throw a certain number of pitches in a row. That number is usually somewhere between 13-16 pitches and with each successive pitch thrown, the pitcher will lose effectiveness and will most likely be more prone to injury. Since all of the correlations for pitches per inning are positive, the more pitches thrown per inning, the worse the pitcher becomes.

Armed with this knowledge, a baseball enthusiast will be able to predict how well, or poorly as the case may be, a pitcher is going to do when he throws a high number of pitches (17 and above) inning after inning. Also, if a pitcher inexplicably suffers a decline in performance, look first at his pitches per inning to see if he is struggling more to get runners out. More than likely, he is. Total pitch counts have had their day and now it is time to make room for pitches per inning.

Correlations are as follows with pitches per inning first and total pitches second: batting average (.579 to -.417); on-base percentage (.671 to -.372); slugging percentage (.517 to -.407); gross product average (.631 to -.416); fielding independent ERA (.609 to -.363); strikeouts per nine innings (.148 to .187); walks per nine innings (.756 to -.217); home runs per nine innings (.419 to -.282).

Total pitch counts, like other counting statistics, are set up to deceive. Simply knowing that a pitcher threw 112 pitches tells nothing. We still need to know how the pitcher arrived at that number of pitches. Did the pitcher throw a complete game or did his manager foolishly allow him to throw 112 pitches in only five innings? Furthermore, we are unable to make any sort of educated guess at how well the pitcher pitched. However, if we had known how many pitches per inning had been thrown, no chapters would be missing from the story we could tell.

In order to illustrate how much more important pitches per inning are than total pitch counts, I took, for the 2007 season, the five pitchers with the most starts from each of the thirty baseball franchises and ran correlations that allowed me to discover how closely tied pitchers per inning and total pitch counts are to batting average, on-base percentage, slugging average, gross product average (OBP*1.8+SLG/4), fielding independent ERA, strikeouts per nine innings, walks per nine innings, and home runs per nine innings. When there were two pitchers for a team that had the same number of starts, I used the statistics for the pitcher with more innings as a starter.

Overall, the correlations were overwhelmingly stronger for pitches per inning pitched to the aforementioned eight statistics than they were for total pitch counts. Of the eight baseball statistics I used for comparison, total pitch counts only had a stronger correlation for the category of home runs per nine innings (.187 to .148); that was also the closest any of the correlations were to each other. Decisively would be the operative word to describe the victory pitches per inning had over total pitch counts.

Individually, it was much of the same story. Of the 150 pitchers I looked at, only ten (Randy Wolf, Jorge Sosa, Miguel Batista, Justin Germano, Kyle Kendrick, Vicente Padilla, Daisuke Matsuzaka, Gil Meche, Brian Bannister, Nate Robertson, and Matt Garza) had five or more of the eight statistics that were more strongly correlated with pitch counts than pitches per inning.

As the average of 16.1 pitches thrown per inning for the 150 pitchers demonstrates and any pitcher will also tell you, pitchers are only conditioned to throw a certain number of pitches in a row. That number is usually somewhere between 13-16 pitches and with each successive pitch thrown, the pitcher will lose effectiveness and will most likely be more prone to injury. Since all of the correlations for pitches per inning are positive, the more pitches thrown per inning, the worse the pitcher becomes.

Armed with this knowledge, a baseball enthusiast will be able to predict how well, or poorly as the case may be, a pitcher is going to do when he throws a high number of pitches (17 and above) inning after inning. Also, if a pitcher inexplicably suffers a decline in performance, look first at his pitches per inning to see if he is struggling more to get runners out. More than likely, he is. Total pitch counts have had their day and now it is time to make room for pitches per inning.

Correlations are as follows with pitches per inning first and total pitches second: batting average (.579 to -.417); on-base percentage (.671 to -.372); slugging percentage (.517 to -.407); gross product average (.631 to -.416); fielding independent ERA (.609 to -.363); strikeouts per nine innings (.148 to .187); walks per nine innings (.756 to -.217); home runs per nine innings (.419 to -.282).

Labels: MLB

## 1 Comments:

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