For ERA and pitches thrown, all estimates were statistically significant. Each pitch in the preceding game was associated with an increase of a pitcher's ERA by approximately 0.007 in the following game. Although the relationship is nonlinear, the graph reveals that the curvature of the function is so slight that a linear approximation is appropriate for practical purposes. Each pitch averaged in the previous 5 games was associated with an increase of a pitcher's ERA by 0.014, and each pitch averaged in the preceding 10 games was associated with an increase of a pitcher's ERA by 0.022.
For strikeouts and pitches thrown, the estimates were linear, small, and not statistically significant. Each pitch in the preceding game was associated with a decrease of a pitcher's strikeout rate by 0.0008. Each 1-pitch increase in the 5- and 10-game averages was associated with a strikeout rate lowered by 0.0011 and 0.0027, respectively. At the average strikeout rate for the sample of 6.1 strikeouts per 9 innings pitched, a 1-pitch increase in the preceding game, 5-game average, and 10-game average lowered the strikeout rate by 0.13, 0.18, and 0.44%, respectively.
For home runs and pitches thrown, all the estimates were statistically significant. A 1-pitch increase in the preceding game was associated with a 0.0013 increase of home runs allowed (a 1% change at the average). A 1-pitch increase in the 5- and 10-game averages was associated with an increase of the home run rate by 0.002 (1.6%, estimated at the 101st pitch) and 0.0025 (2%), respectively.
For walks and pitches thrown, the estimated impact was nonlinear, statistically significant, and was the opposite of the expected effect. Each pitch in the preceding game was associated with a walk rate decreased by 0.0024 (0.66%) at the 101st pitch. The 101st pitch for the preceding 5- and 10-game average pitches thrown was associated with a lowered walk rate by 0.0038 (1%) and 0.006 (1.67%).
Table 2 reports the overall impact of previous pitches thrown on ERA and by 3 age cohorts: 25–34 years (10 years centered on the estimated peak age for pitchers as estimated by Bradbury ), <25 years, and >34 years. The top half of the table lists the impact of each additional pitch thrown on ERA, and the bottom half lists the number of pitches needed to raise a pitcher's ERA by 0.25. Younger pitchers were no more sensitive to high pitch performances than those of the middle age cohort. Older pitchers suffered much less than younger pitchers did from pitches thrown in the previous game; however, older pitchers suffered more from increased cumulative pitching loads than their younger counterparts did.
The estimated impact of the days of rest on ERA was small and insignificant, with each rest day associated with an improvement of 0.015. Based on this estimate, skipping a pitcher in a 5-man rotation—giving him 4 additional days of rest—lowered his ERA by 0.06. Also, rest days were not strongly correlated with performance components. The relationship with strikeouts was not statistically significant. Each rest day was associated with a home run rate lowered by 0.012 (0.98%), and the estimate that included pitches thrown in the previous 10 games was not statistically significant. The estimated impact of rest days on walks was to increase the walk rate by 0.032, approximately 0.08% at the average walk rate. As with pitches thrown, the estimated effect was statistically significant and counterintuitive.
The finding that pitches thrown were negatively correlated with future performance should be interpreted with caution. Although the estimated effect was statistically significant, it was small. The findings are consistent with the results of Escamilla et al. (5), who examined the change in pitching mechanics over the course of simulated games using a sample of collegiate baseball pitchers. The researchers found that the pitching mechanics of pitchers who threw between 105 and 135 pitches for 7–9 innings were “remarkably similar,” and the results did not support the idea that pitching more increased shoulder and elbow forces and torques, which Anz et al. (1) found to be positively correlated with injury. The value is within the upper range of pitches thrown that major-league starting pitchers are typically allowed to do. According to the estimates reported in this study, the ERA difference in a game following 105 pitches vs. 135 pitches was approximately 0.19—a small effect of 0.33% at the sample average.
Murray et al. (11) also looked at the performances of major-league baseball pitchers; however, the focus of the study was to examine the impact of pitching on fatigue within a single game. The researchers used video observations of several physical markers to compare pitchers in their first and last innings of play in a game and identified kinematic and kinetic changes that were consistent with fatigue. However, alternative explanations for the changes could not be ruled out, and there was no follow-up on the future impact on performance. The findings of this study do not support or contradict those of Murray et al.
Although the estimates reported in this study indicate that there is a clear relationship between pitches thrown and overall performance, the relationships between pitches thrown and the performance components differ. The strongest effect occurred with home runs—each pitch was associated with an increased home run rate of between 1 and 2%. The weakest effect occurred with strikeouts—each pitch was associated with a decreased strikeout rate of between 0.13 and 0.44%, and the estimates were not statistically significant. The counterintuitive relationship between pitches thrown and walks is difficult to explain. In summary, the analysis of the performance components indicates that high pitch counts are likely to impact pitchers' run prevention ability through giving up home runs, as opposed to reducing strikeouts or increasing walks.
As a regressor, age was not associated with changes in performance after controlling for the other factors in the regression equations. However, when the sample was separated into age cohorts, there was a clear difference in responses to pitches thrown, among age groups. Older pitchers were more sensitive to cumulative pitches thrown than younger pitchers were; however, that older pitchers were less sensitive to pitches thrown in the preceding game is interesting. This response is consistent with the results of the past studies that found older athletes using experience to counteract diminishing physical skills. For example, Baker et al. (2) found evidence of golfers using strategy to substitute for decreased driving distance to remain competitive. Among baseball players, Bradbury (4) identified differences in aging functions across skills that were consistent with players improving strike-zone judgment to compensate for diminished hitting and pitching skills. If such compensation is occurring, then veteran pitchers may be able to exploit their knowledge of the game to pitch effectively following a high pitch game even though their physical stamina has decreased. However, further research is needed to examine this hypothesis.
Alhough days of rest did not appear to affect the performance of pitchers, it is likely that rest days are important for maintaining performance; otherwise, teams would not give pitchers any rest days. Less than 0.5% of the pitchers in the sample pitched with <3 days of rest; therefore, it would be unwise to extrapolate the estimates to predict the impact of rest days below that threshold. The results of this study indicate that additional days of rest beyond the normal do not appear to have a strong impact on performance. This finding is consistent with that of Potteiger et al. (14), which found that after 3 days of rest, markers of muscle damage returned to baseline levels.
It is our hope that future researchers will examine the usefulness of pitch counts as a predictor of performance and injury more precisely than we have identified here. Researchers should draw upon the vast amounts of sports data that are becoming increasingly available to them to examine factors relating to performance and injury. In addition, future studies should examine the direct impact of pitching loads on injury.
This analysis of 1,058 pitchers across 22 seasons found that pitching performance is affected by the number pitches thrown in the previous games; however, the magnitude of the effect is small. It takes a rather large change in pitches thrown to have even a modest effect on performance; therefore, the guidance offered by pitch counts and pitch-count restrictions may be limited. Pitchers and coaches should be mindful of potential overuse, but occasional high- or low-pitch games likely have only a minor effect on future performance. The longer the high- or low-pitch counts are maintained, the greater the dampening or improvement will be. Furthermore, additional days of rest beyond the ordinary appear to have little effect on performance.
One interesting finding of the study is that the estimated relationship between pitches thrown and performance was virtually linear. Even in cases wherein nonlinear estimates were found, the curvature was small. Therefore, the estimates provide simple rules of thumb that can be used to estimate the future performance consequences from pitches thrown in a game. For example, this study found that each pitch thrown in a game increased a pitcher's ERA in the following game by 0.007. Managers can use such rules to quickly weight the strategic risk of leaving a pitcher in a game versus taking him out.
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Keywords:© 2012 National Strength and Conditioning Association
athletic injuries (prevention and control); fatigue; athletic performance; adults; humans