Tennis Analytics Pioneer Brings Data-Driven Strategy to Elite Competition, Challenging Traditional Coaching Methods

Tennis Analytics Pioneer Brings Data-Driven Strategy to Elite Competition, Challenging Traditional Coaching Methods

Craig O'Shannessy, a tennis strategist and analyst for multiple Grand Slam tournaments, is pushing professional tennis toward a more quantitative approach to competition, according to a February 11, 2026 appearance on Wharton's Moneyball podcast. His work—which includes contributions to The New York Times and strategic consulting at the sport's highest levels—centers on using match data to identify underutilized tactics and challenge conventional wisdom about optimal play.

The shift mirrors broader trends in corporate decision-making, where finance leaders increasingly demand empirical evidence over institutional intuition. O'Shannessy's focus on "coachability"—a player's willingness to adapt strategy based on analytical findings—parallels the cultural transformation CFOs face when implementing data-driven planning processes that contradict years of established practice.

During the podcast with Wharton professors Cade Massey, Eric Bradlow, and Shane Jensen, O'Shannessy detailed how analytics reveal gaps between what players believe works and what the numbers actually show. One specific area: net play and serve-and-volley tactics, which O'Shannessy argues remain significantly underused despite data suggesting higher win probabilities in certain match situations.

The resistance isn't about the quality of the data—it's about the difficulty of behavioral change under pressure. Professional tennis players, like corporate executives, often revert to familiar patterns during high-stakes moments, even when analysis suggests alternative approaches would yield better outcomes. O'Shannessy's role involves not just identifying these opportunities but convincing elite athletes to implement changes that feel counterintuitive.

The parallel to finance operations is direct: FP&A teams can build sophisticated forecasting models, but adoption depends on whether business unit leaders trust the output enough to alter their resource allocation decisions. O'Shannessy's emphasis on "continuous learning" as a competitive advantage reflects the same dynamic CFOs navigate when rolling out new planning systems or AI-assisted forecasting tools.

What makes O'Shannessy's work notable isn't the existence of tennis analytics—sports data is ubiquitous—but his focus on the implementation gap. The Grand Slam analyst position itself represents an institutional commitment to data-informed strategy at tournaments that have operated on traditional coaching methods for decades. His New York Times platform extends that influence beyond individual players to shape broader conversations about optimal tennis strategy.

For finance leaders, the lesson isn't about tennis tactics. It's about the universal challenge of translating analytical insights into changed behavior, particularly in high-pressure environments where reverting to familiar approaches feels safer than trusting new models. O'Shannessy's work suggests that sustainable adoption requires more than better data—it demands a cultural shift toward what he calls "coachability," or the institutional willingness to let evidence override experience.

The Wharton podcast appearance, which ran over an hour, positioned O'Shannessy's approach within the broader "Moneyball" framework of using analytics to identify market inefficiencies. In tennis, those inefficiencies appear as strategic choices that persist despite contradicting available data—a phenomenon CFOs will recognize from their own organizations.