A research for analysing characteristics of university baseball players using swing measurement unit

Abstract

In the field of sports engineering, though policies for developing human resources in sports are promoted nationally, lack of managers and coaches who can give highly-qualified instruction to an individual player is an urgent problem. Therefore, a swing measurement unit is developed for quantitatively analyzing a batter’s swing form in baseball. However, it is difficult for managers and coaches to utilize the sensor data and give players an instruction based on the data. The purpose of the study is to find out new knowledge for giving appropriate advice to individual players by analyzing the swing characteristics with the swing measurement unit. In order to verify whether the swing characteristics of university baseball players can be properly classified, the swing data and batting performance data were classified individually using the k-means method. As a result, when the swing characteristics and batting performance were classified into two cluster by the k-means method, the players could be classified with high accuracy. Furthermore, the principal component analysis was performed to examine the relationship between the measurement results obtained from the swing measurement device and the swing characteristics in conjunction with this classification result. The results of principal component analysis also showed that it was possible to classify high-ranked players and low-ranked players. From these results, it showed elements of the measurement items related to classification. It was found that players with long swing rotational radius, short swing time and high head speed were classified as high-ranked players.

Keywords

• biomechanics
• baseball
• swing
• inertial sensor
• k-means clustering
• principal component analysis