Performance-environment mutual flow model using big data on baseball pitchers
- PMID: 36465584
- PMCID: PMC9715958
- DOI: 10.3389/fspor.2022.967088
Performance-environment mutual flow model using big data on baseball pitchers
Abstract
Introduction: The study investigated the baseball pitching performance in terms of release speed, spin rate, and 3D coordinate data of the release point depending on the ball and strike counts.
Methods: We used open data provided on the official website of Major League Baseball (MLB), which included data related to 580 pitchers who pitched in the MLB between 2015 and 2019.
Results: The results show that a higher ball count corresponds to a slower release speed and decreased spin rate, and a higher strike count corresponds to a faster release speed and increased spin rate. For a higher ball count, the pitcher's release point tended to be lower and more forward, while for a higher strike count, the pitcher's release point tended to be to the left from the right pitcher's point of view. This result was more pronounced in 4-seam pitches, which consisted the largest number of pitchers. The same tendency was confirmed in other pitches such as sinker, slider, cut ball, and curve.
Discussion: Our findings suggest that the ball count is associated with the pitcher's release speed, spin rate, and 3D coordinate data. From a different perspective, as the pitcher's pitching performance is associated with the ball and strike count, the ball and strike count is associated with pitching performance. With regard to the aforementioned factor, we propose a "performance-environment flow model," indicating that a player's performance changes according to the game situation, and the game situation consequently changes the player's next performance.
Keywords: Major League Baseball (MLB); baseball; game flow; hot hand; pitcher.
Copyright © 2022 Hashimoto and Nakata.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Figures
Similar articles
-
The relationship between pitching parameters and release points of different pitch types in major league baseball players.Front Sports Act Living. 2023 Apr 24;5:1113069. doi: 10.3389/fspor.2023.1113069. eCollection 2023. Front Sports Act Living. 2023. PMID: 37168522 Free PMC article.
-
Ball Speed and Release Consistency Predict Pitching Success in Major League Baseball.J Strength Cond Res. 2016 Jul;30(7):1787-95. doi: 10.1519/JSC.0000000000001296. J Strength Cond Res. 2016. PMID: 26677832
-
Changes in a Starting Pitcher's Performance Characteristics Across the Duration of a Major League Baseball Game.Int J Sports Physiol Perform. 2016 Mar;11(2):247-54. doi: 10.1123/ijspp.2015-0121. Epub 2015 Jul 27. Int J Sports Physiol Perform. 2016. PMID: 26218542
-
Using Advanced Data to Analyze the Impact of Injury on Performance of Major League Baseball Pitchers: A Narrative Review.Orthop J Sports Med. 2022 Jul 20;10(7):23259671221111169. doi: 10.1177/23259671221111169. eCollection 2022 Jul. Orthop J Sports Med. 2022. PMID: 35898207 Free PMC article. Review.
-
Review: Approaches to Visual-motor Control in Baseball Batting.Optom Vis Sci. 2021 Jul 1;98(7):738-749. doi: 10.1097/OPX.0000000000001719. Optom Vis Sci. 2021. PMID: 34328452 Review.
Cited by
-
The relationship between pitching parameters and release points of different pitch types in major league baseball players.Front Sports Act Living. 2023 Apr 24;5:1113069. doi: 10.3389/fspor.2023.1113069. eCollection 2023. Front Sports Act Living. 2023. PMID: 37168522 Free PMC article.
References
LinkOut - more resources
Full Text Sources