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Two methods for recommending bat weights

A T Bahill1, M M Freitas

  • 1University of Arizona, Tucson 85721, USA.

Annals of Biomedical Engineering
|July 1, 1995
PubMed
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Researchers developed methods to determine the ideal baseball bat weight for players. They explored mathematical models and physics, then addressed data gaps using novel techniques to create practical bat weight recommendations.

Area of Science:

  • Sports Science
  • Biomechanics
  • Data Science

Background:

  • Determining optimal baseball bat weight is crucial for player performance.
  • Previous methods relied on sophisticated equipment, limiting accessibility.
  • Data limitations, including missing values, hindered traditional analysis.

Purpose of the Study:

  • To compute the ideal bat weight for individual baseball players.
  • To develop accessible models for recommending optimal bat weights.
  • To address challenges posed by incomplete datasets in sports science research.

Main Methods:

  • Mathematical modeling of bat swings and bat-ball collisions.
  • Utilizing physics equations to calculate ideal bat weight.
  • Employing three novel imputation techniques (neural networks, commercial software, random number generation) to handle missing data.

Related Experiment Videos

Main Results:

  • Successfully generated complete datasets despite initial data sparsity.
  • Derived several simple models for recommending bat weights based on imputed data.
  • Demonstrated feasibility of creating accessible bat weight recommendations.

Conclusions:

  • Accessible methods for determining ideal bat weight are achievable.
  • Novel data imputation strategies can overcome limitations in sports science datasets.
  • The derived models offer practical solutions for players and coaches.