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Performance-environment mutual flow model using big data on baseball pitchers.

Yasuhiro Hashimoto1,2, Hiroki Nakata3

  • 1Faculty of Sustainable System Sciences, Osaka Metropolitan University, Osaka, Japan.

Frontiers in Sports and Active Living
|December 5, 2022
PubMed
Summary
This summary is machine-generated.

Baseball pitchers adjust release speed and spin based on ball and strike counts. Pitching performance is influenced by game situations, leading to a proposed "performance-environment flow model".

Keywords:
Major League Baseball (MLB)baseballgame flowhot handpitcher

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Area of Science:

  • Sports Science
  • Baseball Analytics
  • Biomechanics

Background:

  • Pitching performance is crucial in baseball.
  • Understanding how game situations affect pitcher mechanics is vital for performance optimization.

Purpose of the Study:

  • To investigate the relationship between ball and strike counts and baseball pitching performance.
  • To analyze how these counts influence release speed, spin rate, and release point data.

Main Methods:

  • Utilized publicly available Major League Baseball (MLB) data from 2015-2019.
  • Included data from 580 MLB pitchers, analyzing release speed, spin rate, and 3D release point coordinates.

Main Results:

  • Higher ball counts correlated with slower release speed and decreased spin rate.
  • Higher strike counts correlated with faster release speed and increased spin rate.
  • Pitching release points shifted based on counts, with specific changes observed for 4-seam pitches and other variations.

Conclusions:

  • Ball and strike counts significantly influence pitcher release speed, spin rate, and release point.
  • A "performance-environment flow model" is proposed, suggesting a dynamic interplay between game situation and player performance.