The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/f86ba220-08a1-4fa0-89a9-d8995790675b

Gomaz, Larisa; van der Graaff, Erik (2023): Kinematic data from youth baseball pitchers recorded with PITCHPERFECT motion sensors. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/f86ba220-08a1-4fa0-89a9-d8995790675b.v1

Dataset

• Biomedical Engineering
• Human Movement and Sports Science
• Engineering
• Medical and Health Sciences

baseball, kinematics, pitch type, sensors, wearables

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Larisa Gomaz , Erik van der Graaff

Data underlying the research of Machine learning approach for pitch type classification based on pelvis and trunk kinematics captured with wearable sensors.

Data set contains kinematics, ball velocity, pitcher's characteristics and pitch types from youth pitchers that are members of the elite youth academies of the Royal Dutch Baseball and Softball Federation (KNBSB).

• 2023-11-06 first online, published, posted

4TU.ResearchData

*.csv

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft Institute of Applied Mathematics (DIAM)
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3ME), Department of BioMechanical Engineering