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How AI Can Improve Play on the Diamond

Traditionally, data analytics uses artificial intelligence (AI) to process and make sense of this data in ways that cannot be replicated manually by humans. Recent developments in AI and the associated technology of machine learning (ML) have yielded the ability to simulate human intelligence to assist coaches and managers in making real-time decisions. By studying the patterns revealed through analytics and working with AI applications, players and teams can improve their performance in games and get more value from practice sessions.

AI for Enhanced Practice

Baseball players at all levels appreciate the benefits that come from focused practice. Concentrating on specific aspects of the sport that need improvement is a strategy as old as the game itself. While the goal of getting better at the game is the same, today’s athletes can make use of the technological advancements in AI to create a personalized program that addresses their weaknesses and builds on their strengths.

An example of AI in action is an app we have developed here at SportsTrace which brings machine learning and markerless motion capture data to anyone with a smartphone. Why is that valuable? The app makes sense of split second data from player footage, while analyzing, for instance, pitcher’s mechanics and provides coaching recommendations. Thanks to AI, our app generates frame-by-frame images to assesses a player’s throwing and hitting motion based on 11 variables, such as balance, release point, and most notably kinematic sequence.

Understanding proper kinematic sequence is key to understanding how software like SportsTrace accurately takes a player’s movements and provides personalized solutions. Kinematic sequences study how energy is transferred through the body when throwing or batting a baseball. The concept behind the kinematic sequence is that power comes from the ground up through the four links of the pelvis, torso, arm, and hand. Maximum power when throwing or batting comes from the efficient transfer of energy as evidenced in the rotational velocity and timing of the body segments. Understanding the flaws in the sequence is about understanding flaws in transfer of energy. Once players correctly transfer energy through their body—well that’s a homerun thanks to AI systems.

Artificial intelligence engines like SportsTrace, Mustard, and ProplayAI perform a regression analysis on the images and suggests corrective exercises. The application considers specific factors regarding the player including their size and age so it can make the most appropriate recommendations. This makes it an excellent tool for players of any age and skill level and offers players a method of obtaining top-flight coaching anytime and anywhere.

Using AI during Games

Teams have been using the practice of shifting fielders for years, but advancements in analytics and AI have enabled precise placement of infielders and outfielders to address specific opposing batters. Based on the predictions made by their software resources, the Tampa Bay Rays employ four and sometimes five outfielders as seen in this year’s postseason. Their data indicates that this positioning gives them a better chance of success than going with a standard alignment.

Tools like the Kinatrax monitor collect data during a game to help prevent injuries, enhance performance, and alert the coaching staff about potential fatigue issues. Teams can use the insights to replace pitchers before rather than after they give up a homerun due to their arm strength dipping slightly. The additional information provided by these tools along with the experience that a manager brings to the table adds up to a big advantage over the opposition.

It’s no longer enough to go with instinct or feel when making decisions regarding the lineup and placement of players during a game. Teams and players who choose to disregard the benefits of AI will find themselves at a distinct disadvantage over their more tech-savvy rivals.