Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data
Ball velocity is considered an important performance measure in baseball pitching. Proper pitching mechanics play an important role in both maximising ball velocity and injury-free participation of baseball pitchers. However, an individual pitcher’s characteristics display individuality and may cont...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/22/7442 |
| _version_ | 1797508511802851328 |
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| author | Larisa Gomaz DirkJan Veeger Erik van der Graaff Bart van Trigt Frank van der Meulen |
| author_facet | Larisa Gomaz DirkJan Veeger Erik van der Graaff Bart van Trigt Frank van der Meulen |
| author_sort | Larisa Gomaz |
| collection | DOAJ |
| description | Ball velocity is considered an important performance measure in baseball pitching. Proper pitching mechanics play an important role in both maximising ball velocity and injury-free participation of baseball pitchers. However, an individual pitcher’s characteristics display individuality and may contribute to velocity imparted to the ball. The aim of this study is to predict ball velocity in baseball pitching, such that prediction is tailored to the individual pitcher, and to investigate the added value of the individuality to predictive performance. Twenty-five youth baseball pitchers, members of a national youth baseball team and six baseball academies in The Netherlands, performed ten baseball pitches with maximal effort. The angular velocity of pelvis and trunk were measured with IMU sensors placed on pelvis and sternum, while the ball velocity was measured with a radar gun. We develop three Bayesian regression models with different predictors which were subsequently evaluated based on predictive performance. We found that pitcher’s height adds value to ball velocity prediction based on body segment rotation. The developed method provides a feasible and affordable method for ball velocity prediction in baseball pitching. |
| first_indexed | 2024-03-10T05:04:59Z |
| format | Article |
| id | doaj.art-5eaeabc9b6914b32a0eda1685c374995 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:04:59Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5eaeabc9b6914b32a0eda1685c3749952023-11-23T01:23:17ZengMDPI AGSensors1424-82202021-11-012122744210.3390/s21227442Individualised Ball Speed Prediction in Baseball Pitching Based on IMU DataLarisa Gomaz0DirkJan Veeger1Erik van der Graaff2Bart van Trigt3Frank van der Meulen4Delft Institute of Applied Mathematics, Delft University of Technology, 2628 CD Delft, The NetherlandsBioMechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, 2628 CD Delft, The NetherlandsFaculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The NetherlandsBioMechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, 2628 CD Delft, The NetherlandsDelft Institute of Applied Mathematics, Delft University of Technology, 2628 CD Delft, The NetherlandsBall velocity is considered an important performance measure in baseball pitching. Proper pitching mechanics play an important role in both maximising ball velocity and injury-free participation of baseball pitchers. However, an individual pitcher’s characteristics display individuality and may contribute to velocity imparted to the ball. The aim of this study is to predict ball velocity in baseball pitching, such that prediction is tailored to the individual pitcher, and to investigate the added value of the individuality to predictive performance. Twenty-five youth baseball pitchers, members of a national youth baseball team and six baseball academies in The Netherlands, performed ten baseball pitches with maximal effort. The angular velocity of pelvis and trunk were measured with IMU sensors placed on pelvis and sternum, while the ball velocity was measured with a radar gun. We develop three Bayesian regression models with different predictors which were subsequently evaluated based on predictive performance. We found that pitcher’s height adds value to ball velocity prediction based on body segment rotation. The developed method provides a feasible and affordable method for ball velocity prediction in baseball pitching.https://www.mdpi.com/1424-8220/21/22/7442ball velocityinertial measurement unitmultilevel modelingpitchingbaseball |
| spellingShingle | Larisa Gomaz DirkJan Veeger Erik van der Graaff Bart van Trigt Frank van der Meulen Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data Sensors ball velocity inertial measurement unit multilevel modeling pitching baseball |
| title | Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data |
| title_full | Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data |
| title_fullStr | Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data |
| title_full_unstemmed | Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data |
| title_short | Individualised Ball Speed Prediction in Baseball Pitching Based on IMU Data |
| title_sort | individualised ball speed prediction in baseball pitching based on imu data |
| topic | ball velocity inertial measurement unit multilevel modeling pitching baseball |
| url | https://www.mdpi.com/1424-8220/21/22/7442 |
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