ANALYSIS OF FIELDER STARTS AND BENCH ABILITY ON AMERICAN PROFESSIONAL BASEBALL PLAYERS
DOI:
https://doi.org/10.46827/ejpe.v0i0.2226Keywords:
data mining, feature selection, sports forecast, major leagueAbstract
The development of athletes or players depends on two aspects: nature and nurture. The former is the talent and qualification of the players themselves, while the latter is the training that consumes human, material and financial resources. Take professional baseball players as an example. Matching the talents of players and referring to the relevant starting rules of the professional baseball league, when the up-and-coming players are first discovered, focused training are used on them. By doing so, the value of the players would be effectively enhanced and the players are helped to seek a better way out. This can form a virtuous circle: the pellets get quality players, and the players get better results. That is to say, strengthening the training for the shortcomings of the players with the potential of the starting players can avoid unnecessary training and huge training expenses behind them, and greatly reduce the risk of career, so that the players have higher security in their short career, and get a win-win-win situation. This study is aimed at the schedule information of the American Baseball League teams. Through feature selection of data mining, this study analyzes the main relationships and key differences between starting player and bench player of second baseman and shortstop in League of Nations teams. It is found that the on base percentage and speed of the infielders is an important ability indicator for the starting position; whereas, the second baseman emphasizes on the attack and the shortstop focuses on fielding. This feature is verified by comparing the opinions of experts and commentators.
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