How the Cincinnati Reds Are Leveraging AI to Improve Performance

Matt McLain’s Three ABS Challenges: A Case Study in AI-Augmented Plate Discipline

In a single plate appearance against the Padres on Monday, Reds second baseman Matt McLain challenged three pitches using the Automated Ball-Strike (ABS) system — and won all three. It was the first time any Major Leaguer had successfully overturned three calls in one at-bat since ABS challenges were implemented this season. McLain’s feat was not just a quirk; it demonstrated how real-time data can sharpen a hitter’s pitch recognition and discipline in the highest-leverage moments.

McLain became the first player since ABS challenges were implemented at the Major League level this season to successfully challenge three pitches in the same plate appearance.

The technology behind ABS uses high-speed cameras and AI to determine ball and strike calls with millimeter precision. By challenging sliders from Padres reliever Jason Adam that were initially called strikes but later confirmed out of the zone, McLain showed an ability to override human umpire judgment with machine-verified facts. Only one other player — the Dodgers’ Miguel Rojas — had attempted three challenges in a single plate appearance, but his final try failed. The contrast underscores the skill required to deploy the AI tool effectively.

• McLain’s three successful challenges in one at-bat are a Major League first, highlighting the tactical edge of using ABS.
• He became the fourth batter to win three challenges in a single game, joining teammates Sal Stewart and others.
• His 4-for-4 record on challenges this season reflects a keen eye honed by data-driven preparation.

Before Monday, McLain had attempted just one challenge all season. The willingness to use ABS three times in a single trip suggests the Reds have integrated the system into their in-game strategy, trusting the AI to back their players’ instincts.

From ABS Data to Training: How the Reds Integrate AI into Player Development

The ABS system doesn't just influence live at-bats. Its data feeds into the Reds’ broader analytics pipeline, where AI models analyze swing decisions, exit velocity, launch angle, and spin rate from every pitch. This creates personalized feedback loops that help players like McLain and teammate Sal Stewart refine their approaches.

McLain’s success — becoming the fourth batter to win three challenges in a single game — underscores how the Reds’ analytics staff feeds real-time data back to players during games.

The challenge data reveals umpire tendencies and strike zone biases, which the Reds translate into targeted drills. For instance, a hitter who consistently misses on low sliders can use ABS feedback to adjust his practice regimen. This mirrors broader trends in applying AI to high-stakes environments — as Neil Muller discusses in the context of cybersecurity AI, the ability to process real-time data and adapt is a competitive advantage across domains.

• The Reds use ABS data to map umpire-specific strike zones, giving hitters a pre-game edge.
• AI models analyze every bat-swing and pitch trajectory, generating daily optimization reports.
• McLain’s improved plate discipline — reflected in his challenge success — is a direct output of this system.

By closing the loop between game data and training, the Reds are turning the ballpark into a living laboratory. The result: players who enter the box with not just talent, but a dataset-driven understanding of what the umpire will call — and what the machine will correct.

Bringing AI to the Stands: The Reds’ Tech-Enhanced Fan Experience

The Reds don’t keep the AI in the clubhouse. Great American Ball Park displays ABS challenge replays on the scoreboard, letting fans see the same automated zone data the players use. This transparency demystifies umpire decisions and turns each challenge into a teachable moment for the audience.

Their mobile app goes further, integrating predictive AI for pitch outcomes and player performance — the same analytics that guide front-office decisions. By making data accessible, the Reds are pioneering a fan experience that educates and engages younger, tech-savvy crowds. Just as technology reshaped soccer after the 2006 World Cup, the Reds are using AI to modernize baseball’s live experience.

• Live ABS replays on the scoreboard show the pitch trajectory and strike zone overlay in real time.
• The mobile app offers AI-driven predictions for the next pitch, player performance probabilities, and win expectancy.
• In-stadium and broadcast integrations of ABS data have increased fan understanding of the game’s nuances.

The strategy is working: the Reds are drawing a younger demographic, and ticket sales for games featuring tech-enhanced broadcasts have risen. In a sport that often prides itself on tradition, the Reds are proving that AI and baseball can coexist — and that the stats on the screen can be just as thrilling as the action on the field.

Key Takeaways

• The Cincinnati Reds are at the forefront of using AI tools like the Automated Ball-Strike (ABS) system to give players like Matt McLain a competitive edge in pitch recognition and discipline.
• McLain’s three successful challenges in one at-bat — a Major League first — demonstrates how real-time data can be tactically deployed during games.
• The Reds’ analytics department integrates ABS and other AI-driven metrics into daily training, creating customized player development programs.
• Fan engagement has been boosted by making AI insights public via scoreboard replays and predictive app features, educating and exciting the audience.
• Adopting technology for both performance and fan experience helps the Reds attract talent and build a modern brand in a traditional sport.