He’s as close to the complete package as a hitter as you can find. Of course, Judge doesn’t stick out merely for his home run prowess. All of the men who hit 61 home runs or more had, at most, nine home runs between them and the second place finisher – Maris beat out Mickey Mantle by seven home runs in 1961. If you look at every 50+ home run season, the average difference between the person hitting 50+ home runs and second place that year was only five home runs. Judge stands out not just for overall total, but for how much of an outlier his performance is compared to the competition. Right now, Judge is 20 home runs ahead of his nearest competitor, Philadelphia Phillies left fielder Kyle Schwarber. When Mark McGwire hit 70 home runs in 1998, Sosa hit 66. When Bonds hit 73 home runs in 2001, Sosa hit 64. Whether or not you believe those other records are legitimate, what can’t be argued with is that records like Bonds’ happened during an era in which home runs flew out of the park faster than a Concorde jet. Bonds and Sammy Sosa have denied those allegations.Īaron Judge's lead in the home run race is an outlier in MLB history. Anyone who has been following Judge’s pursuit will note that most people have brushed aside that record – held by Barry Bonds – or any home run season north of 61 home runs because all those men were embroiled in performance enhancing drug scandals and allegedly used steroids. Judge is likely to fall short of the Major League Baseball record of 73 home runs. That means he’ll likely end up far ahead of the longtime American League record of 61 homers by Roger Maris. Judge stands at 60 home runs and is on pace to end up in the mid 60s. A look across different metrics shows just how dominant Judge has been – and how it has helped garner interest for the once favorite pastime of America. Yes, Judge is likely to break the American League record for home runs in a season, which is impressive onto itself. That said, you’d have to be an idiot to not recognize the historic season Aaron Judge is having. I hate them and everyone who plays for them. Even if 2.4% isn’t a huge amount in the abstract, it’s enormous in the context of the sheer difficulty.Let me be clear: I’d rather be audited by the IRS than see the New York Yankees win a World Series. Of course he didn’t! And the dead ball should only have lowered those odds. If I told you Judge had a 1-in-40 shot of hitting 70 homers before the year, you’d laugh at me. On the other hand, it’s a phenomenal achievement anyway. With the changes in my approach, he gets there in roughly 2.4% of simulations. With this method, I feel more confident in saying that 70 is a long shot, even with the way Judge is playing. To hit six homers in 14 games, Judge both needs to be in good form and likely needs almost all of those 14 games. That works out to a 32.4% chance, and if you’re going to witness that home run in person, you’ll want tickets to the last series of the season, naturally enough. Here, for example, are the days when Judge might hit his 66th homer, tying Sammy Sosa on the single-season home run list: I think this model does a better job of accounting for the odds of something remarkable happening. In each simulation, I picked an underlying home run rate talent from a distribution of possible Judge home run rates rather than just using the average. If Judge is going to hit 70 homers, it stands to reason that he’ll probably do it when he’s the best version of himself, on a personal home run tear. There’s no way of knowing in advance which of the two he’ll be, but players don’t produce at a monotonic level forever. Sometimes he might be feeling off, and only have a 6% likelihood. Sometimes, he might be feeling good and briefly have an 8% true-talent likelihood. In plain English, Aaron Judge might be 7% likely to hit a home run on any given plate appearance over the medium and long run, but that’s not necessarily the case week to week. As Dan noted in his piece on triple crown odds, picking an underlying player talent level from a distribution does a better job of reflecting reality than using a static number. That works pretty well for the center of the probability distribution, but if you’re looking for outliers (like 70 homers), it falls short. Previously, I estimated a true-talent home run rate and used that for every simulation.
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