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Is Aaron Judge The Next Babe Ruth … Or The Next Jeremy Lin?

After the latest chapter of Aaron Judge’s breakout season — a dominant Home Run Derby performance that was as impressive in its ease as it was in its raw power — the New York Yankees right fielder seems poised to take over as baseball’s elusive superstar ambassador.

“[He] can become the face of the game,” MLB commissioner Rob Manfred told reporters at the All-Star Game. “He is a tremendous talent on the field and really appealing off the field.”

Perhaps. Like the previous “face of baseball,” Derek Jeter, Judge plays in the biggest media market, for baseball’s highest-profile team. (One that happens to be having a surprisingly good season, its recent slide notwithstanding.) There’s a reason more people have Googled Judge in each month this season than have searched for possible future GOAT Mike Trout in any month of his career.

That’s an awful lot of pressure to heap on a guy who’s still technically an MLB rookie, of course, and his game still has flaws. Although he’s having one of baseball’s all-time great rookie seasons, even a player as gargantuan as Judge might be dwarfed by regression to the mean before the season is over.

Even if Judge gets swallowed whole by the regression monster, though, his phenomenal first half tells us a lot. Just as former Knicks guard Jeremy Lin’s dominant early games suggested he would become at least a pretty good player — which has been (kinda) true — it’s almost impossible to have even a half-season like Judge’s without at least panning out as a good ballplayer, if not something much more.

Let’s put some of his numbers to date in context: His 30 home runs at the All-Star break tied for the 26th most by any player — rookie or not — since 1913;1 his .691 slugging percentage was tied for 75th. He was one of only 44 players to post a first-half batting average of at least .320 and an isolated power of at least .350. Overall, his on-base plus slugging (OPS) was 101 percent better than league average, the 90th-best first half in that department that any hitter has enjoyed since 1913.

Most impressive is Judge’s company on that top-100 list: Babe Ruth (10 times), Ted Williams (eight), Lou Gehrig (five) and so forth. Twenty-five of the 52 players who appeared on the list are in the Hall of Fame, and many of those who aren’t either will be (Albert Pujols, Miguel Cabrera), should be (Larry Walker, Edgar Martinez), would be if not for a scandal (Barry Bonds, Shoeless Joe Jackson) or could eventually be (Bryce Harper).

And among rookies, Judge’s first half was virtually peerless. According to, he generated 5.1 wins above replacement (WAR) in the months of April, May and June. Since 1974,2 no other rookie has broken 5 WAR in the first three months of a season, and only one — Chris Sabo in 1988 — has even earned 4 WAR. Judge is easily off to the best first half of a rookie season in modern history.

The best rookie first halves of the modern era

Most wins above replacement (WAR) in April/May/June of a player’s rookie season since 1974

1 Aaron Judge 2017 334 5.1
2 Chris Sabo 1988 293 4.2 289 0.5
3 Albert Pujols 2001 332 3.8 344 3.5
3 Corey Seager 2016 343 3.8 344 3.7
3 Fred Lynn 1975 282 3.8 323 3.3
6 Mike Trout 2012 258 3.6 381 6.3
7 Devon White 1987 341 3.4 355 1.2
8 Mike Piazza 1993 288 3.2 314 4.3
8 Evan Longoria 2008 302 3.2 206 2.4
10 Tim Raines 1981 241 3.1 122 0.7
10 Joc Pederson 2015 324 3.1 261 -0.1
12 Ichiro Suzuki 2001 374 3.0 364 3.0
12 Eric Hinske 2002 299 3.0 351 1.6
12 Alvin Davis 1984 308 3.0 370 2.3
12 Greg Gross 1974 291 3.0 385 1.3
16 Kris Bryant 2015 294 2.9 356 3.7
16 Kent Hrbek 1982 274 2.9 317 0.4
18 Dan Uggla 2006 302 2.8 381 1.5
18 Mark McGwire 1987 284 2.8 357 2.2
20 Willie Randolph 1976 271 2.7 228 1.8
20 Juan Samuel 1984 354 2.7 383 0.4
22 Nomar Garciaparra 1997 358 2.6 376 3.8
22 Billy Hamilton 2014 303 2.6 308 1.1
22 Butch Wynegar 1976 283 2.6 339 0.9
25 Jose Canseco 1986 342 2.5 340 0.4
Average 307 3.2 325 2.1

Source: FanGraphs

But the history of great rookie seasons also shows how strong the pull of regression can be: The average player on this list ended up producing only two-thirds as many WAR in the second half of his rookie campaign as he did in the first. For every Trout, who started strong (despite a delayed call-up) and then decimated the league down the stretch, there were more cases like Devon White, Joc Pederson and even Sabo, all of whom struggled to recapture the magic of their first-half performances.

Judge will likely face a similar fate. Based on his batted-ball numbers, we’d expect Judge to be hitting .303 right now, not .329. Although nobody hits the ball harder, Judge’s .426 batting average on balls in play (BABIP) stands out even next to the game’s other hard hitters, suggesting some kind of second-half downturn is probably in order.3 Likewise, Judge has hit a staggering 42 percent of his fly balls out of the park, another relatively luck-driven number that will likely come back down to earth. (Even the most powerful hitters can sustain a homers-per-fly rate of only 25 to 30 percent.)4 And while Judge has drawn plenty of walks and shown good plate discipline for a rookie, he’s also whiffed a lot. His low contact rate might become problematic as pitchers study his weaknesses and develop more sophisticated strategies against him.

Given all that, it would be very surprising if the regression bug didn’t bite Judge during the season’s second half.

If and when that does happen, some folks will surely blame it on the dreaded “Home Run Derby curse” — the idea that participating in the contest (much less winning it as Judge did) mucks up a player’s swing over the rest of the season. This topic has been researched to death over the years, with various studies finding it to be a myth … or maybe slightly real. While it’s true that far more Derby participants have fallen off in the second half than have improved, there’s an obvious selection bias at work, too: In order to be picked for the contest in the first place, players need great first-half power numbers — most likely well above their career norms. By regression to the mean alone, we’d expect a group of players selected specifically because they had an abnormally great first half to decline in the second.

For what it’s worth, I tried to account for this effect by measuring Derby contestants against a control group of hitters who had similar first-half power numbers (as measured by at-bats per home run) but didn’t participate in the contest.5 Since 2002, the average Derby participant saw his OPS decline by 56 points in the second half of the season — but the average member of the control group also saw his OPS fall by 49 points, a negligible difference.

However, there is one area where Derby participants did drop off a bit more than we’d expect: raw power. While the control group’s average isolated power (or slugging percentage minus batting average) fell 25 points, the Derby group’s average dropped by 36 points. Both groups saw an identical 0.5 percentage-point dip in hard-hit ball rate, but Derby hitters hit slightly fewer fly balls than we’d expect based on the control group,6 and their rate of home runs per fly fell by 2.8 percentage points, compared with a decline of 1.7 percentage points for the control group.

Either way, the overall cost of participating in the Derby is (at most) quite small compared with the toll exacted by regression to the mean.

And said regression will probably be Aaron Judge’s biggest enemy in the second half of the season. Sadly, no player can escape its clutches for very long — not even the most wildly entertaining hitter on the planet.


  1. The earliest season for which’s split finder has data.

  2. The first year tracked monthly WAR splits.

  3. Although, as my ESPN colleague Paul Hembekides pointed out, BABIP doesn’t include home runs. If you add Judge’s homers into his BABIP, he’s hitting a ridiculous .516 when he doesn’t strike out — the best single-season mark in history.

  4. Sometimes this particular stat can be more sustainable than we’d expect on its face because of park effects, but Yankee Stadium is much more of a haven for left-handed power hitters than righties like Judge.

  5. In each season, the control group had to include players who logged as many plate appearances, as many at-bats per homer and as high an OPS as the lowest-ranked Derby participant in each category. That left me with a sample of 416 hitters in the control group since 2002, versus 122 Derby contestants.

  6. A decline of 1 percentage point, versus a 0.6-percentage-point dip for the control group.

Neil Paine was the acting sports editor at FiveThirtyEight.