Advertise on podcast: Wharton Moneyball

Baseball's biggest advantages are not always bought with the biggest payroll. Mike Petriello, Major League Baseball's Director of Stats and Research, explains how teams such as the Milwaukee Brewers use Statcast, plate discipline, player development, and tailored matchups to compete with the sport's biggest spenders. He also examines the data behind Shohei Ohtani's postseason struggles, what swing path and pitch shape reveal about hitters, and why analytics only matter when coaches and players can put them into action. Hosted on Acast. See acast.com/privacy for more information.

The transfer portal has changed how quickly a college football team can change. The data used to evaluate players, forecast seasons, and inform fans has to keep up. Ron Yurko, Director of the Carnegie Mellon Sports Analytics Center, explores how analytics are helping modernize the Heisman race and make player evaluation more inclusive across positions. He discusses why transfer activity makes college football harder to predict, how uncertainty should shape team forecasts, and what students need to understand about sports betting and prediction markets. Hosted on Acast. See acast.com/privacy for more information.

The NHL's salary cap is set to rise dramatically. For front offices, that means a new set of decisions about contracts, free agency, draft picks, and where to find an edge. Samuel Ventura, Vice President of Hockey Strategy and Research for the Buffalo Sabres, explains how teams are modeling the effects of more cap space and adjusting the way they value players and build rosters. He also discusses how analytics has become more collaborative across hockey, from player evaluation to strategic decisions. Ventura examines the potential of new player and puck tracking data, including how computer vision could help teams understand shooting mechanics, puck battles, and other previously hard-to-measure parts of the game. He also shares what NHL teams are learning about hiring analysts in the age of AI. Hosted on Acast. See acast.com/privacy for more information.

In a league built around star quarterbacks, the ability to survive an injury can decide a season. Neil Paine, sports writer and data analyst, explores how NFL teams can build a more resilient formula when their starting quarterback is unavailable. He examines why defenses, coaching, and the gap between a starter and backup can determine whether a team stays competitive, along with the strategic question of when to play a rookie quarterback. Paine also breaks down Major League Baseball's playoff-seeding problem, where weak division winners can receive advantages over stronger wild card teams. The conversation closes with a look at the Florida Panthers and why an injury-plagued "gap year" does not always mean a championship window has closed. Hosted on Acast. See acast.com/privacy for more information.

The first week of the NFL season creates more opinions than answers. Tej Seth, data scientist, breaks down how analysts can distinguish meaningful early-season signals from misleading results. He explains why offensive scheme changes can matter more than raw Week 1 statistics, why turnovers and late-down performance should be treated carefully, and how models should update after surprising games. The conversation examines the Baltimore Ravens' evolving offense, the Kansas City Chiefs' new running game, San Francisco's edge over the Rams, and the matchups worth watching as the NFL season takes shape. Hosted on Acast. See acast.com/privacy for more information.

Is this NFL season more wide open than it appears? Brian Burke, Sports Data Scientist at ESPN, and Kevin Cole, Data Scientist at PFF, use football analytics to examine the season ahead. Burke explains how tracking data is changing the way teams measure pass protection and pressure, while Cole breaks down quarterback projections, team strength, and why the league's top contenders may be closer together than expected. Hosted on Acast. See acast.com/privacy for more information.

The road to the College Football Playoff is not as straightforward as a preseason ranking suggests. Bill Connelly, ESPN staff writer and creator of SP+, breaks down the analytics shaping the college football season. He examines why roster turnover creates a wider range of outcomes, how schedule strength affects playoff chances, the difference between the SEC and Big Ten, and the teams best positioned to contend. He also shares what his season simulations reveal about the title race and why a few unexpected teams could break through. Hosted on Acast. See acast.com/privacy for more information.

What happens when college football players can make more money by staying in school than by entering the NFL? Steven Godfrey, college football journalist and co-host of Yahoo's College Football Enquirer, examines the financial incentives reshaping college football. He discusses NIL deals, transfer rules, eligibility loopholes, and why former NFL players attempting to return to college football could test the sport's limits. Godfrey also breaks down the Big Ten and SEC, coaching pressure at USC and Michigan, conference depth, playoff paths, and why Notre Dame and Ohio State stand out in the national championship picture. Hosted on Acast. See acast.com/privacy for more information.

Why are today's MLB pitchers harder to hit than ever? Adam Ottavino, former 15-year MLB reliever and current ESPN analyst, explains how pitch-tracking data, high-speed cameras, and personalized pitching labs reshaped his own career and changed player development across baseball. He breaks down how pitchers design new pitches, use bat-tracking data to attack hitters, and adapt their strategy from pitch to pitch. Ottavino also examines why pitching may have gained an edge over hitting, how teams use data to plan pitch selection, the limits of velocity, automated ball-strike challenges, and what a temporary velocity drop can mean for a pitcher such as Paul Skenes. Hosted on Acast. See acast.com/privacy for more information.

Which NFL teams are the numbers backing before the 2026 season begins? Aaron Schatz, National NFL Analyst at ESPN and Chief Analytics Officer at FTN Fantasy, explains why the Houston Texans stand out in the AFC and why the Seattle Seahawks project as one of the league's strongest teams. He breaks down the Rams' Super Bowl outlook, the Bills' defense, the Eagles' path through the NFC East, and the teams that could surprise or regress. Schatz also explores how DVOA-based forecasts account for quarterback performance, coaching changes, injuries, schedules, and the balance of offense, defense, and special teams. Plus, why even the best projections leave plenty of room for the chaos of an NFL season. Hosted on Acast. See acast.com/privacy for more information.

What if baseball’s most trusted pitching limit is more habit than science? Travis Sawchik, baseball analytics writer and author of Big Data Baseball and The MVP Machine, breaks down why pitch counts can miss the real stress on a pitcher’s arm, how workload units and acute-to-chronic ratios offer a better view of fatigue, and why teams may need to rethink how they build pitching capacity. The conversation also covers MLB trade deadline strategy, the Dodgers’ title odds, the Brewers’ risk calculus, when teams should chase variance instead of average gains, Baker Mayfield’s recent production compared with Patrick Mahomes, the Ravens’ coaching changes, Saquon Barkley’s workload, and college football playoff storylines. Hosted on Acast. See acast.com/privacy for more information.

Can the Philadelphia 76ers turn a roster featuring LeBron James, Joel Embiid, Tyrese Maxey, Jaylen Brown, and VJ Edgecombe into a championship team? Basketball analytics pioneer and ESPN data scientist Dean Oliver joins the Wharton Moneyball team to examine how Philadelphia might distribute possessions among so many high-usage players, whether LeBron can succeed as a point forward, and who should control the ball in critical late-game situations. The conversation also explores three-point shooting, defensive concerns, and why analytics can measure player performance more easily than it can predict chemistry and fit. Plus, the hosts discuss the enduring appeal of the Baseball Hall of Fame and the arrival of corporate jersey sponsorships in college football. Hosted on Acast. See acast.com/privacy for more information.

The right limits can lead to better ideas and better performance. David Epstein, bestselling author of The Sports Gene, Range, and Inside the Box: How Constraints Make Us Better, joins Wharton Moneyball to explore how constraints can strengthen creativity, focus, and decision-making. Epstein discusses the value of tight briefs and rapid prototypes, why first ideas are not always the best ideas, and why young athletes may benefit from playing multiple sports before specializing. Hosted on Acast. See acast.com/privacy for more information.

If the best team does not always win, how much of sports success comes down to skill, strategy, or randomness? Eric Eager, Vice President of Football Analytics for the Carolina Panthers, joins the Wharton Moneyball team to examine the role of unpredictability in sports. The conversation explores whether the Home Run Derby is more revealing than it appears, how tournament design influences results, and why major competitions can feel random even when familiar contenders ultimately advance. The discussion also covers World Cup win probabilities, the importance of superstar players, NHL contracts and salary caps, the disappearance of 200-game winners in baseball, and whether momentum can explain the changing performance of elite golfers. Hosted on Acast. See acast.com/privacy for more information.

What if one of soccer’s most important analytics metrics is missing some of the most dangerous moments in a match? Recorded live with students from the Wharton Moneyball Academy, Jonathan Pipping, Ph.D. student and member of the Wharton Sports Analytics and Business Initiative Research Team, explains the limitations of expected goals and the development of XG+, a new approach that accounts for both the probability of a shot being taken and the likelihood of it becoming a goal. He discusses how player tracking data can reveal opportunities that traditional XG misses, why creating shooting opportunities may be more predictive than finishing ability, and how advanced metrics could help teams better evaluate player performance and transfer value. Hosted on Acast. See acast.com/privacy for more information.