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AI predict best batters in baseball

The research comes from the Duke University Medical Center. With the study, computer scientists discovered that baseball players with higher scores on computer-based vision and motor tasks went on to have better on-base percentages. In addition, these players had more walks and fewer strikeouts (‘plate discipline’) compared with those who did not take part in similar tests. Artificial intelligence was used to make the predictions, drawing inferences from Bayesian hierarchical latent variable models.

The inference is that the baseball scouts of tomorrow who are on the look out for a consistent, conscientious hitter may find as many clues by assessing data gathered from how the player completes task in front of a computer screen as they would from watching the player exhibit his or her sporting prowess on the field.

For the study, the researchers looked at 252 baseball professionals, from major and minor league teams in the U.S., found that players who scored highest after completing a series of vision and motor tasks using Nike Sensory Stations went on to show better game statistics (assessed in terms of on-base percentages, more walks and fewer strikeouts).

The computer assessments looked at whether the player could assess information from a faint object within a split second, plus skills like reaction time, perception-span tasks, and hand-eye coordination. The researchers plan further studies involving baseball players using virtual reality, perceptual learning video games and brain training. This will be used to explore whether the required skills are ‘hard-wired’ into the brain or whether they can be learned (in other words is someone born a good baseball player or can the necessary skills to play at a high level be learned?)

Commenting on the study, lead researcher Dr. Kyle Burris states: “There has been a data revolution in the game of baseball over the past decade with the introduction of technologies that track the speed and movement of every pitch, the location of players in the field, and other tools that can quantify player performance like never before.”

More details are shown in the video, featuring an interview with Dr. Burris:

The research has been published in the journal Scientific Reports. The research paper is titled “Sensorimotor abilities predict on-field performance in professional baseball.”

In related sports-meets-technology news a new sports platform has developed a Blockchain based infrastructure which is designed to reward sports fans who comment on games, post reviews and other on-line activities (see: “Sports platform evolves Blockchain based infrastructure.”)

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Dr. Tim Sandle is Digital Journal's Editor-at-Large for science news. Tim specializes in science, technology, environmental, business, and health journalism. He is additionally a practising microbiologist; and an author. He is also interested in history, politics and current affairs.

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