The Association Between Pitch Accuracy and Batter Outcomes in Major League Baseball

Authors: Benjamin E. Napoli,¹ Daniel A. Napoli,¹ Anthony M. Napoli MD MHL¹, Timmy R Lin PhD¹, Macall S. Robertson JD, Jason Machan PhD,¹ Janette Baird PhD¹

¹Department of Emergency Medicine, Alpert Medical School of Brown University

Editor’s Note: This article’s formatting was corrected on July 8, 2025. All tables, figures, and appendices are now present in the article.

Abstract

Purpose: Pitch speed is considered synonymous with pitching success. In years past, the accuracy of a pitch was paramount but in recent years this has been deprioritized as compared with pitch speed. Over the years, batters have adapted to higher pitching speeds so pitch strategy and placement may be more important.  Our hypothesis was that pitching accuracy associated with intended pitch location would be a significant factor in pitching success in Major League Baseball (MLB).  

Methods: To study this, we studied multiple facets of a pitch, including pitch accuracy, to assess the association between pitch accuracy and batter outcome in over 1000 at bats in over 20 randomly selected games during the 2022 MLB season.  Our primary goal was to determine if there was an association between pitch accuracy, after controlling for confounders, and batting average against (BAA) and slugging percentage (SLG). 

Results: We found that at bats in which the last pitch hit the intended spot reduced batter success by greater than 50%.  Higher pitching speed was not associated with success partly because it was associated with lower accuracy. If a pitch was accurate, after adjusting for other variables, it was 3.28 times more likely to be successful. 

Conclusions: This study demonstrates that pitching accuracy is a highly important skill in determining the success of pitchers, beyond that of other traditional pitching features.  Future studies to automate this work and integrate machine learning and predictive modeling could be used to optimize pitcher success or identify the most accurate pitchers.

Applications in Sport: This study demonstrates that pitching accuracy is a critical determinant of success in Major League Baseball (MLB), with accurate pitches reducing batter success rates, including batting average and slugging percentage, by over 50%. While pitch speed has traditionally been prioritized, this research highlights that accuracy has a far greater impact on outcomes, as accurate pitches are more than three times as likely to succeed. These findings challenge the current emphasis on velocity, suggesting that focusing on accuracy could optimize performance and reduce injury risks for pitchers.

Introduction:

In recent years, hitting and pitching analytics have been used extensively to study talent and study what makes a successful pitcher or hitter. For pitchers, these features can include pitch movement, pitcher mechanics,(Manzi et al., 2022) pitch selection, pitch types, and spin rate.(Whiteside et al., 2016)  While pitch speed has continued to increase(Cooper, 2020) and batters have adjusted, these other features become increasingly important.  An ideal pitcher would have peak velocity and accuracy but having both is not easy to obtain.(Venkadesan & Mahadevan, 2017) 

Pitch accuracy in common baseball parlance is often referred to as whether the pitcher “hits his spot.”  Hitting or missing the spot refers to the intended pitch location indicated by the catcher.  Before each pitch, catchers set their glove for the intended pitch location.  While there are some observational studies of pitch accuracy over different levels of baseball,(Kawamura et al., 2017) in the modern era there is no published study to indicate just how much of an effect accurate pitching has on batter performance.

Our hypothesis was that a significant difference in hitter outcomes will exist between pitchers who “hit his spot” (are within 6 inches of the intended pitch location) and those who do not.  A secondary outcome of our study was to examine whether pitch accuracy had a greater association with batter outcome than pitch selection, location, or speed.

Methods:

This was a retrospective study of 17 randomly selected games during the 2022 Major League Baseball (MLB) Season.  Investigators used a pre-specified Google Form (Mountain View, CA) with all key pitcher, pitch, and batter outcomes identified.  The investigators documented the outcome of the last pitch of each at bat.  This is consistent with current MLB methods of determining measures like batting average against (BAA) as it is the only pitch in the at bat in which the batter is forced to make a decision that will result in an at bat outcome. BAA and Slugging Percentage (SLG) were calculated using standardly accepted methodology (BAA = H/AB; SLG = (1B + 2Bx2 + 3Bx3 + HRx4)/AB).

An a priori sample size estimate based upon an estimated effect size of a 20-point decrease in BAA indicated a need to study approximately 1700 at bats.  An interim analysis of effect was planned at 500 and 1000 at bats. One game from each MLB team’s 2022 season was randomly selected until the study was complete.  Data abstractors were blind to the study results.  Data collection included pitcher handedness, pitch speed, intended pitch location, pitch type, and outcome.  As is customary for measuring BAA, only the last pitch of an at bat was used in this study.  

Our primary outcome was to demonstrate that a significant difference will exist between accurate pitches, “hit his spot” (estimated to be within 6 inches of the intended pitch location) and inaccurate pitches (“missed his spot”).  The secondary outcomes were to study if pitch speed, pitch selection, or pitch location had an impact on pitcher success.  Statistical analysis was done using SAS 9.4 (Cary, N.C.). We report on median with interquartile range (IQR) and proportions with 95% confidence intervals (95% CI).  Direct comparisons of unadjusted data were completed using a Chi-square test for proportions while a logistic regression was used to adjust for all variables associated with pitching accuracy.  A definitions table can be found in the Appendix due to the number of abbreviated outcomes.   

Results:

Primary Outcome:

The results of the interim analysis at 1000 at bats demonstrated a significant effect of pitch accuracy on BAA and SLG.   Of these 1000 at bats, represented by 17 randomly selected MLB games, the pitching accuracy was 45.3% (95% CI: 42.2% – 48.4%) and median pitch speed was 91 (IQR: 85 – 94) miles per hour.  The top three pitch types thrown were the fastball (31.8%), sinker (21.4%), and slider (19.5%) [Table 1].  Nearly 66% of pitches targeted low in the zone [Table 2]. Overall outcome (BAA and SLG) as it relates to pitch accuracy can be found in Table 3. 

Unadjusted analysis for the primary outcome of BAA and SLG demonstrated pitch accuracy was a significant predictor of pitcher success.  At bats ending in a pitch that hit the intended spot reduced batter success by greater than 50%; accurate pitches resulted in a BAA and SLG of 0.166 and 0.343 vs. 0.262 and 0.558 for inaccurate pitches, p<0.01.   If a pitcher hits his spot, after adjusting for other variables, he was 3.28 times more likely to be successful. No other variable was significantly associated with the pitcher success in the adjusted model (Table 4).

Table 3: Pitch Accuracy and Batter Outcome

*See Appendix for index of abbreviations

Secondary Outcome

There was no relationship between pitch speed and accuracy though pitchers who threw in the 80’s miles per hour (mph) appeared more likely to be accurate than those in the 90’s mph [Figure 1]. There was no statistically significant difference in pitch accuracy and BAA or SLG between left-handed pitchers and right BAA and SLG as they relate to pitch type and pitch location can be found in Tables 5 and 6, respectively.

Unadjusted analysis demonstrated that sliders had the lowest BAA (0.190), while changeups had the highest (0.293) [Table 5]. Higher pitching speed was not significantly associated with preventing a hit (χ2 (5) = 9.9, p=.08) but was significantly associated with lower accuracy (χ2 (5) = 13.2, p=.02).  No other pitcher variable other than accuracy of intended location was significantly associated with pitcher success. 

Assuming an accurate pitch, then high-in (2.02) and high-middle (2.96) pitches were significantly more likely to be successful at hitting the spot than baseline comparison (middle-middle). All off-speed pitches except for curveballs were significantly more likely to be successful than their baseline comparator (the fastball) with odds ratios ranging from 1.6 (sinker) to 2.8 (slider) [Table 8].

Discussion:  

Success in pitching is a combination of many different features, including game situation, the batter, the pitcher, and the pitch.  However, pitch accuracy has always been considered one of the most important features of a pitcher until recently when much of the attention has turned to pitch speed.  This study sought to investigate the impact of pitching accuracy, specifically the ability to hit the location of an intended pitch, on the success of pitchers in MLB games.  While many features of a pitch can affect the outcome, few of them (if not none in our study) have the impact that accuracy has on batter outcome.  In fact, our study indicates an unadjusted reduction of nearly 50% in batting average and slugging percentage when pitchers hit their intended location with an adjusted odds ratio of 3.28.          

Sports analytics is a $2.7B industry that is expected to have a compound annual growth rate of more than 20% over the next ten years.(Research, 2022)  The sport of baseball has been one of the earliest adopters and the clearest example of successful use of baseball analytics. Though baseball is considered a team sport, it is in fact a series of sequential events and therefore lends itself to more precise statistical analyzation.(Bechtold, 2023)  This has led to the rise of slow-motion video, new metrics for pitch movement and success, and the development of whole analytics departments in all MLB teams.  This information has given rise to pitch location analysis, enhanced studying of the influence of framing of pitches by catchers, profiles of pitch spin and movement, comparative pitching analytics, and even the possibility of machine learning and predictive analytics for pitching. 

The success of a pitcher is affected by so many features of the pitcher and the batter.  In the pitcher alone, features like pitch speed, spin rate, and selection are important.(Manzi et al., 2022)  Even pitcher mechanics has an effect on pitch accuracy.(Venkadesan & Mahadevan, 2017)  Pitching mechanics gets refined over time and studies indicate pitchers have greater accuracy at higher performance levels.(Kawamura et al., 2017)  However, it is hard to quantify the importance of each of these features.   The common belief is that pitch speed dominates all other features of pitcher success.  However, one study that incorporated pitch speed was only able to show that the combination of pitch speed, refined special pitch release location, and variation in pitch selection accounted for only 22% of the variance in pitcher performance.(Whiteside et al., 2016)  Our study demonstrated a significant portion of variance in accuracy is explained by pitch speed (21.5%); the higher the pitch speed the less accurate the pitch.  Overall, the adjusted model demonstrated pitch speed did not affect pitch success as opposed to an accurate pitch being greater than three times more likely to be successful. 

This study relied upon retrospective review of a random sample of regular season games to determine the effect of pitch accuracy while simultaneously accounting for some of the most important, traditional features of pitching success – pitch speed, location, and selection.  Unadjusted analysis reinforced some of the common opinions about current pitching – sliders and splitters if placed correctly are some of the most difficult pitches to hit (Table 5) and pitches thrown over the middle of the plate are more likely to lead to batter success (Table 6).  However, it also demonstrated some unexpected outcomes – that fastballs were some of the least accurate pitches and that pitch speed had limited, if any, effect on batter outcome.  However, after adjustment some interesting associations were revealed.  Pitching high in the zone had an odds ratio of success consistently two times greater than the middle of the zone, and that pitching low in the zone was not associated with improved pitcher outcome.  While interesting, this is not entirely surprising as it follows the trend of pitchers throwing higher much more commonly than they once did as batters have adopted an upward sloping swing to maximize launch angle.(Gutwein, 2021; Lu Chen, 2022)   Additionally, almost all pitches were more successful than a fastball at getting a batter out; this too reflects the trend toward increasing use of off-speed pitches in the MLB.(Norris, 2023)  After adjustment, all these other features of commonly accepted pitching importance – speed, pitch selection, and pitch location had limited effect on the outcome of the pitch in comparison with pitch accuracy.  An accurate pitch was more than three times (OR 3.28, 95% CI 2.45-4.4) more likely to result in a favorable outcome and resulted in 50% reduction in batting average and slugging percentage. 

Any study that attempts to study one feature (pitch accuracy) amongst a number of complex other potential confounding factors is bound to have some limitations.  Complexity itself is a limitation. Though many of the variables (pitcher, game, time in the season, etc.) were randomized, the complexity offered by any one pitcher limits interpretation.  For example, certain pitchers may not offer certain pitches or the quality of their pitches varies as compared to another when pitching in one location.  Any study incorporating such features would be much more complex and would also limit real world real-time application.  The retrospective nature of this study would normally be a limitation, but it allowed specificity of pitch location due to the ability to review the video and record features of each pitch.  However, certain features of each pitch were not available to the investigators – like spin rate, lateral and vertical movement.  These features may have a role in determining pitcher accuracy as well as batter outcome independent of pitcher accuracy.  Lastly, any study involving individual review with a general goal of subjectively identifying whether a pitch was accurate runs the risk of consistent over-estimation or under-estimation and/or variation.  Only computerized video review algorithms would be able to reduce imprecision further.  Computer algorithms and machine learning may eventually be able to be incorporated to refine this work. 

Conclusion:

In conclusion, this study suggests that pitching accuracy, particularly hitting the intended location of a pitch, is a crucial factor in determining pitcher success in MLB.  The findings provide valuable insights into the relative importance of various pitching variables, emphasizing the significance of strategic accuracy over sheer pitching speed.  This study contributes to the ongoing discourse about the multifaceted nature of successful pitching in professional baseball and emphasizes the importance of one of the most important features of a successful pitcher – accuracy. 

Applications in Sport:

This study highlights the critical importance of pitching accuracy in Major League Baseball (MLB), demonstrating that accurate pitches significantly reduce batter success rates, with a 50% decrease in batting average and slugging percentage when pitchers “hit their spot.” While pitch speed has traditionally been emphasized, this research shows that higher speeds often reduce accuracy and have limited impact on outcomes compared to precise pitch placement. The findings suggest that prioritizing accuracy over speed could improve pitcher performance and reduce injury risks associated with the current focus on velocity. These insights could inform training strategies, analytics, and even machine learning applications to optimize pitching success, offering a shift in how pitching effectiveness is evaluated and developed in modern baseball.