Kinematic data from youth baseball pitchers recorded with PITCHPERFECT motion sensors

DOI:10.4121/f86ba220-08a1-4fa0-89a9-d8995790675b.v1
The DOI displayed 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

Datacite citation style

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
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

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).

History

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

Publisher

4TU.ResearchData

Format

*.csv

Organizations

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

DATA

Files (2)