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\u201cBaseball is 90% mental. The other half is physical.\u201d<\/p>\n
\u201cYou\u2019ve got to be very careful if you don\u2019t know where you are going because you might not get there.\u201d<\/p>\n
\u201cThe future ain\u2019t what it used to be.\u201d<\/p>\n
These witticisms were uttered decades ago by Hall of Fame New York Yankees catcher and manager Yogi Berra. As artificial intelligence (AI) becomes more ubiquitous in all walks of life, the sayings may also prove prescient when it comes to baseball.<\/p>\n
AI is quickly becoming an essential tool for Major League Baseball. In fact, a recent study conducted at the McKelvey School of Engineering at Washington University in St. Louis produced some interesting results. The study concentrated on data from the 2015-2018 seasons.<\/p>\n
As reported in The Source (a Washington University publication), Yevgeniy Vorobeychik, an associate professor of computer science at the university, said he and his co-authors used deep neural networks to predict pitch outcomes whenever a batter swings. Key results indicated that AI can enable less experienced or skilled pitchers to enhance their performance through optimized pitch sequencing.<\/p>\n
\u201cEssentially, all pitchers who make it to the major leagues have great stuff,\u2019 Vorobeychik said. \u201cWhat distinguishes those who are great from those who are merely good is, in part, how they use their arsenal in a game setting for particular batters. Formally solving this as a game may enable pitchers with less experience or ability to figure out the best pitch sequencing and to better utilize their stuff.\u201d<\/p>\n
The study, according to The Source, also evaluated the effectiveness of the optimized pitching strategies by comparing them with observed pitching efficacy in the data \u2013 \u201cresults showed a significant reduction in batter on-base percentage, particularly for lower-ranked pitchers.\u201d<\/p>\n
So, beyond studies like these, how is AI now being used by MLB?<\/p>\n
As reported in the Wall Street Journal (WSJ), MLB recently partnered with Uplift Labs, a biomechanics company, that says it can document a prospect\u2019s specific movement patterns using two iPhone cameras. The setup was tested at an MLB draft combine last month in Arizona.<\/p>\n
Uplift, according to the WSJ, is using AI \u201cto translate the images captured by the phone cameras into metrics that can quantify elements of player movement. It believes the data it generates can detect player\u2019s flaws, forecast their potential, and possibly, flag their potential for injury.\u201d<\/p>\n
\u201cWe have metrics on things like kinematic sequence, stride length, ball contact timing,\u201d said Sukemasa Kabayama, Uplift\u2019s founder. \u201cAt the same time, we also have this new kind of very early injury warning detection. Let\u2019s say if you have too much of an arm flare, you know there may be potential overload on the elbow, which can, unfortunately, lead to Tommy John surgery.\u201d<\/p>\n
Phil Buckley pens a blog for the Central North Carolina Men\u2019s Senior Baseball League, a wood bat summer baseball league that has divisions for 18+, 40+ and 50+ year olds. Buckley said MLB is using AI and machine learning for player performance analysis (e.g., sensor data analysis, video analysis, performance modeling, injury prevention, stolen bases); pitch tracking (e.g., radar technology, machine learning algorithms, spin rate analysis, trajectory analysis); fan engagement (personalized recommendations, chatbots, virtual reality, social media engagement); and in-game decision making (player tracking, pitch selection, probability monitoring, umpire decision support).<\/p>\n
Buckley succinctly summed up how AI is changing baseball:<\/p>\n
\u201cAI is revolutionizing the way coaches, managers and scouts approach the game,\u201d says Buckley. \u201cWith advancements in data-driven technology and data analytics, AI is providing deeper insights\u2026and you don\u2019t need to be a big market team in New York or Los Angeles to take advantage of this technology to reach the World Series.\u201d<\/p>\n
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Want More Tech News? Subscribe to ComputingEdge<\/i> Newsletter Today!<\/strong><\/p>\n \u00a0<\/p>\n \u00a0<\/p>\n So, it appears that when it comes to AI, MLB is heeding yet another of Yogi Berra\u2019s famous sayings:<\/p>\n \u201cWhen you come to a fork in the road, take it.\u201d<\/p>\n \u00a0<\/p>\n Disclaimer:<\/strong> The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE\u2019s position nor that of the Computer Society nor its Leadership.<\/p>\n<\/div>\n
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