Professor David Henkin, a historian of American culture and author of Out of the Ballpark, joins the Wharton Moneyball team to examine how baseball’s history, statistical evolution, and fan engagement reveal a complex, ever-changing sport that defies any single interpretation. Cade, Eric, Shane, and Adi also discuss early data and strategy implications of the automated ball-strike system in Major League Baseball while also analyzing tournament dynamics and competitive balance in NCAA March Madness.

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Eric Tulski, Head of Hockey Operations for the Carolina Hurricanes, joins the Moneyball team to explains how analytics, roster construction, and organizational philosophy influence performance, player evaluation, and playoff outcomes in the NHL. Cade, Shane, and Adi also discuss the dominance of teams like the Los Angeles Dodgers, the debate over salary caps and spending floors, and how analytics and labor negotiations may shape the future of Major League Baseball.

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Brandt Tilis, Executive Vice President for Football Operations for the Carolina Panthers, joins the show to break down NFL roster construction, draft strategy, and the economics of quarterback contracts. He explains how teams balance analytics, film evaluation, and salary cap constraints. In the second half, the hosts discuss the intensity of the World Baseball Classic, automated strike zones, and surprising NHL playoff races.

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Brandt Tillis, Executive Vice President for Football Operations for the Carolina Panthers, joins the show to break down NFL roster construction, draft strategy, and the economics of quarterback contracts. He explains how teams balance analytics, film evaluation, and salary cap constraints. In the second half, the hosts discuss the intensity of the World Baseball Classic, automated strike zones, and surprising NHL playoff races.

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Ken Pomeroy, college basketball statistician and founder of KenPom, joins Wharton Moneyball to break down tempo-free efficiency ratings, the four factors (shooting, turnovers, rebounding, and free throws), and how he evaluates prediction accuracy and calibration across a full season. Plus, Eric, Shane, and Adi discuss what caught their eye in sports — from World Baseball Classic odds and preseason workload questions to tennis dominance and what makes today’s stars so statistically extraordinary.

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Theo Epstein, Senior Advisor and part owner of Fenway Sports Group and former executive with the Boston Red Sox and Chicago Cubs, explains how integrating analytics with scouting built championship organizations, how reforms like the pitch timer reshaped the pace of play, and how Major League Baseball can reenergize its national appeal.

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Josh Rawitch, President of the National Baseball Hall of Fame and Museum, joins Eric, Shane, and Cade to explore how Cooperstown preserves baseball history, adapts to analytics and evolving standards of excellence, and prepares for America’s 250th anniversary while shaping the future of the game’s most iconic institution. Plus, the Moneyball team analyzes standout moments from the Winter Olympics—including three-on-three hockey and mixed doubles curling—while also examining NHL goaltending streaks and Major League Baseball preseason projections that raise broader questions about league parity.

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Ben Alamar—former NBA analytics executive with the Oklahoma City Thunder and Cleveland Cavaliers, and author of Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers—joins Wharton Moneyball to break down emerging NBA storylines, the unintended consequences of draft lottery reform, bold alternatives to tanking, and the case for analytics trailblazer Dean Oliver’s induction into the Basketball Hall of Fame. Cade, Eric, and Adi also explore statistical evidence of Olympic figure skating bias, debate event proliferation in skiing and speed skating, unpack the Los Angeles Lakers’ Pythagorean paradox, and assess historic performance runs by athletes such as Mikaela Shiffrin and Scottie Scheffler.

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Craig O'Shannessy, tennis strategist, analyst for multiple Grand Slams, and New York Times contributor, joins the show to discusses how data-driven decision-making, underused tactics like serve-and-volley, and coachability separate today’s champions from the rest of the field. Cade, Eric, and Shane also analyze Seattle’s defensive-driven win in Super Bowl LX, reassess quarterback ceilings under pressure, and connect those insights to Olympic tournament design and the role of randomness in elite sports outcomes.

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Michael Lopez, Senior Director of Football Data and Analytics at the NFL, joins the Moneyball team to explain the use of causal inference and drive simulations in shaping the modern game of football. Plus, Eric and Adi explore the mathematical phenomenon of regression to the mean and how it applies to the unprecedented career trajectories of athletes like Carlos Alcaraz and Shohei Ohtani.

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