Development of strategic pitching skill items in professional baseball games

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Publicado en:Journal of Physical Education and Sport vol. 25, no. 8 (Aug 2025), p. 1742-1752
Autor principal: Tahara, Yasuhiro
Otros Autores: Matsuoka, Hiroki, Hato, Kenta, Nishijima, Takahiko
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Universitatea din Pitesti
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Acceso en línea:Citation/Abstract
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024 7 |a 10.7752/jpes.2025.08194  |2 doi 
035 |a 3265962878 
045 2 |b d20250801  |b d20250831 
084 |a 164144  |2 nlm 
100 1 |a Tahara, Yasuhiro  |u Doctoral Program in Physical Education Sciences, Graduate School of Comprehensive Human Sciences, University of Tsukuba, JAPAN 
245 1 |a Development of strategic pitching skill items in professional baseball games 
260 |b Universitatea din Pitesti  |c Aug 2025 
513 |a Journal Article 
520 3 |a Introduction: Strategic decision-making in pitching is a crucial factor in baseball performance, yet traditional metrics like earned run average and even advanced sabermetrics such as fielding independent pitching (FIP) and strikeout-to-walk ratio (K/BB) fail to directly measure how pitchers adapt their pitch selection in response to situational demands. Relatedly, although sports science has explored biomechanical and physiological aspects of pitching, little attention has been paid to the intentional structure of pitching strategy. This study addresses this critical gap by developing and validating a measurement model of strategic pitching skills based on pitch-bypitch data. Materials and Methods: Using data from Nippon Professional Baseball (NPB), the study analyzed 28,222 plate appearances. A causal-effect analysis with the Delphi method was conducted with expert input to define two main domains of strategic pitching skill: pitch velocity skill and pitch location skill. Sub-skills included off-speed variation (velocity) and vertical, horizontal, and diagonal skills. A total of 20 items were initially created based on differences in pitch characteristics relative to the context (e.g., pitch count, previous pitch). Exploratory and confirmatory factor analyses were conducted to test the construct validity, followed by structural equation modeling (SEM) to examine criterion-related validity using FIP and K/BB as external indicators. Results and Discussion: After the exploratory analysis, 18 items remained, yielding a four-factor model that explained 70% of the variance. A confirmatory factor analysis further supported this model, and both horizontal and off-speed skills showed significant associations with improved performance, reflected in lower FIP (-0.51 and -0.39, respectively) and higher K/BB (0.76 for horizontal skill). These results confirm that the developed items are not only statistically valid but also practically meaningful. This model provides a novel framework for evaluating strategic pitching skills and has potential applications in individualized coaching, performance analysis, and AI-based scouting systems. Conclusions: This study developed and validated a set of strategic pitching skill items based on pitch-by-pitch data from NPB. The resulting model consists of two domains-pitch velocity skill and pitch location skill-comprising four sub-skills. Construct and criterionrelated validity were confirmed, particularly for horizontal and off-speed skills. These skills offer practical value as measurable indicators for coaching, scouting, and player development. 
610 4 |a Nippon Professional Baseball 
653 |a Physiology 
653 |a Datasets 
653 |a Discriminant analysis 
653 |a Structural equation modeling 
653 |a Professional baseball 
653 |a Coaching 
653 |a Coaches & managers 
653 |a Validation studies 
653 |a Skills 
653 |a Velocity 
653 |a Validity 
653 |a Decision making 
653 |a Sport science 
653 |a Delphi method 
653 |a Biomechanics 
653 |a Graduate students 
653 |a Indexes 
653 |a Construct Validity 
653 |a Structural Equation Models 
653 |a Factor Analysis 
653 |a Motion 
653 |a Goodness of Fit 
653 |a Statistical Significance 
653 |a Games 
653 |a Factor Structure 
653 |a Team Sports 
653 |a Delphi Technique 
653 |a Maximum Likelihood Statistics 
653 |a Decision Making Skills 
653 |a Statistical Analysis 
653 |a Predictive Validity 
653 |a Performance Based Assessment 
653 |a Content Validity 
700 1 |a Matsuoka, Hiroki  |u Department of Health Informatics, Faculty of Healthcare Management, Niigata University of Health and Welfare, JAPAN 
700 1 |a Hato, Kenta  |u Institute of Health and Sport Sciences, University of Tsukuba, JAPAN 
700 1 |a Nishijima, Takahiko  |u Graduate School of Sport Science, International Pacific University, JAPAN 
773 0 |t Journal of Physical Education and Sport  |g vol. 25, no. 8 (Aug 2025), p. 1742-1752 
786 0 |d ProQuest  |t Consumer Health Database 
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