Who’s the greatest baseball player of all time? For fans and historians, the debate is eternal.
But a team of University of Illinois researchers thinks they’ve finally built a fairer way to answer the question, one that levels the playing field across decades of evolving talent. Their new statistical framework, published in the Annals of Applied Statistics, suggests that Barry Bonds and Willie Mays deserve top billing, surpassing long-revered names like Babe Ruth and Hank Aaron when performance is adjusted for era-specific factors.
A Fresh Take on a Century-Old Argument
The research team, composed of statisticians Shen Yan, Christopher Kinson, and Daniel Eck, along with historian Adrian Burgos Jr., developed what they call “Full House Models.” These models compare players within their seasons while also factoring in the size and strength of the overall MLB talent pool at the time. The bigger the pool, the tougher the competition—so the bar for greatness rises accordingly.
“What we’re really asking is: how impressive is a performance when judged against the best players someone could have reasonably competed against?” said co-author Daniel Eck. While the team didn’t invent player comparisons, their approach goes beyond raw stats or even traditional sabermetrics by mathematically accounting for the historical context of the league.
Who Ranks Where?
The findings reshuffle the all-time leaderboard:
- Barry Bonds and Willie Mays top the list of batters
- Roger Clemens, Greg Maddux, and Randy Johnson lead the pitching ranks
- Legends like Hank Aaron and Babe Ruth rank slightly lower than their popular reputation suggests
This is not to say Ruth and Aaron weren’t dominant, the researchers emphasize. But when today’s players face a global talent pool that’s grown dramatically in size and diversity, maintaining dominance means something different. The model, they argue, gives modern players credit where it’s due—and may correct for nostalgia-driven bias in historical rankings.
Why the Talent Pool Matters
In Ruth’s era, the MLB talent pool excluded entire racial and international demographics. “A smaller, segregated league meant fewer top-tier athletes competing for fewer spots,” the authors note. Today’s players emerge from a vast and globalized system, making statistical outliers even rarer and more impressive.
The Full House Modeling approach quantifies this shift, using nonparametric methods and order statistics to recenter greatness in its proper statistical context. The team also ran sensitivity and multiverse analyses to test how different assumptions—like alternate talent pool estimates—might impact the rankings. The top names held firm.
From Stat Lab to Baseball YouTube
This research is part of a broader initiative at the Eck Sports Lab, a group committed to merging data science with baseball storytelling. Their work has already made its way into popular media: a recent Baseball Bits segment by Foolish Baseball spotlighted their approach in a video on Hank Aaron’s uncanny consistency.
Still, the researchers stop short of declaring a final verdict. “This model is a tool, not a pronouncement,” Eck said. “It adds to the conversation, and we hope it makes that conversation better.”
The Game Goes On
So will fans stop debating Ruth versus Bonds at barstools and ballparks? Not likely. But now, thanks to some mathematical firepower from Illinois, those arguments can at least be a little more informed—and maybe a little more fun.
Published in the Annals of Applied Statistics, Vol. 19, No. 2, June 2025
DOI: 10.1214/24-AOAS1992
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