Major League Baseball is rolling out automated ball-strike calls for the 2026 season. A horse racing venue in Indianapolis just launched an AI handicapper to help fans pick winners. Yahoo has built an AI that speaks in the voice of NBA analyst Kevin O’Connor for draft queries. Across professional sport, artificial intelligence is showing up in places the industry would not have predicted three years ago, and the pace is accelerating.
Letting the algorithm call the pitch
Baseball’s Automated Ball-Strike Challenge System is one of the most visible AI deployments in professional sport right now. The system uses tracking technology to determine whether pitches cross the strike zone, with an automated call delivered almost instantly. Managers and players can challenge umpire calls to trigger the automated review.
For a sport with a 150-year relationship with the human strike zone, the rollout is significant. Umpires have always introduced individual variation into ball-strike calls, and plenty of players and coaches have built entire game plans around exploiting or managing that variation. The 2026 season will produce the most detailed data yet on how automated officiating changes player behavior, pitch selection, and game outcomes at the major league level.
The first AI handicapper in horse racing
Affinity Interactive’s Daily Racing Form, in partnership with Horseshoe Indianapolis, launched “A.I. Alan” earlier this year, described as the industry’s first virtual AI handicapper. The tool is designed to help fans and bettors analyze race cards, assess horse form, and think through wager decisions using AI-powered analytics rather than printed form guides and instinct alone.
Horse racing has always been data-intensive, with decades of race records, breeding histories, and track condition data available in principle but difficult for casual fans to navigate. A.I. Alan is an attempt to bring that depth of analysis to a wider audience, lowering the barrier to informed engagement with a sport that has struggled to attract younger fans. Whether it succeeds will depend on how well the tool handles the genuine complexity of the game rather than producing plausible-sounding selections.
Asking the expert on demand
Yahoo Sports launched “Ask Kevin O’Connor” on June 3, an AI feature that lets users pose NBA Draft questions and receive answers modeled on the voice and analytical style of the writer and analyst Kevin O’Connor. The product is built on Yahoo’s Scout AI answer engine, which the company is also deploying in its finance vertical.
The concept is notable for reasons beyond the specific application. It represents a bet that fans want on-demand expert analysis, not just access to statistics. O’Connor built his reputation through deep prospect evaluation and distinctive opinions, and the AI is trained to replicate that style. Whether it can reliably capture the nuance of his judgments, or mostly produces polished summaries, will become clear as Draft coverage plays out over the next few weeks.
How fast is the market moving?
Research published this year values the AI in sports market at $9.80 billion in 2026, with projections pointing toward $50.69 billion by 2033. The growth is being driven by a combination of factors: team performance analytics, broadcast enhancement tools, fan engagement platforms, ticketing and venue optimization, and player health monitoring systems.
Northeastern University researcher Lorenzo Torresani is studying a harder version of the same problem: whether AI can make sense of what is actually happening in a game, not just what the numbers say. His research found that current AI systems can describe what players do and where they move when performing an action, but a good sportscaster does much more than that. They explain why a play worked, anticipate what comes next, and decide which moments matter. Getting AI to that level of contextual understanding remains the genuine challenge.
The current wave of deployments is working on problems that are largely solved at the level of pattern recognition. The harder question is whether sport will eventually have AI that understands the game the way experienced coaches and analysts do, and not just the data behind it. For more coverage of AI in sport and technology, visit Mylistingo.
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