djoko stats

Ivan Lendl was a pioneer back in his mid-1980s heyday, always willing to try new and different ways to maintain his sovereignty. One of his strategies, the Czech Hall-of-Famer revealed to fellow pro Jimmy Arias, was that at break point, his bitter rival John McEnroe served down the middle (T) at a rate of 72.6%. The calculation, at the time, seemed something like spycraft.

“Ivan would do [the math] himself,” Arias recently told me. “Somehow, Ivan would get video tapes of the matches of the guys he was most worried about and chart them to figure it all out. It had to be a lot of work.”

We’ve come a long way since Lendl sledgehammered his way into the International Tennis Hall of Fame. Now we all—from Wall Street to Main Street—worship at the altar of data and analytics. The trend is particularly striking in tennis, the only sport in which you can accumulate more measurable units (points, goals, runs) than an opponent and still lose.

That’s a real quandary for tennis, because not all points are of equal value. Grab more of the important ones in any given match and you win. But the margins these days are so small—“miniscule” may be the better word—that in many percentage-based statistical categories the difference between the leader and sometimes an entire group of lower-rated peers seems more like a rounding error than a valuable data point on which to hang your hat.

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Consider this: Rafael Nadal ranks No. 4 overall in the ATP’s career (best) Under Pressure category, behind (in order from the top), Novak Djokovic, Pete Sampras, and Carlos Alcaraz. Worthy rivals all, right? Nadal leads the pack in the break point conversion category, and trails only Sampras in break points saved. The real-world difference: Nadal’s superior BPC percentage of 44.9% means that out of every 300 BP opportunities, he successfully converted 134.7 points. Djokovic, whose BPC is 44.1%, converted 132.3. That’s a difference of just over two more points—over a career.

The truism is that statistics don’t lie. But they often don’t tell you very much, or what you often really want to know. Why does one player win Wimbledon, while another with nearly identical stats does not? The stats like the rankings themselves, are efficiency ratings, crying out for context.

“I used to get annoyed at a player I [worked with] because he would get 80% of his first serves in—the tour leader in 2025 at the moment is Alexander Zverev, at 71.5%—but he won a relatively low percentage of them because he was just spinning the first ball in,” recalled Arias.

Or take the WTA, where in the current rankings Aryna Sabalenka is No. 1 and Karolina Muchova is No. 20. Big difference, right? But the gap in their stats is larger than three percentage points in just one category, break points saved: 64.9% for Sabalenka, 61.1% for Muchova. It’s a telling stat but it hardly accounts for the great disparity in their ranking and record.

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People sometimes go wrong by looking at the numbers in isolation...They don't always look at when things happen in a match, or why they happen. I think it's really important to understand why the numbers are what they are. Paul Annacone

“To really get a good sense of what a stat means,” veteran coach Craig Boynton told me, “You really have to drill down into it, see what factors are in play, including other stats.”

Tennis Channel analyst and elite coach Paul Annacone echoed that theme when he told me that he doesn’t want to be an “old dinosaur,” and is therefore a fan of analytics and metrics. But, he noted, “People sometimes go wrong by looking at the numbers in isolation...They don't always look at when things happen in a match, or why they happen. I think it's really important to understand why the numbers are what they are.”

As an example, he cited the case of someone who had an excellent first-serve conversion percentage of 67% but still lost 6-4, 6-4 because at 4-5 in each set the player presumably got nervous and missed five out of six first serves.

Stats answer basic questions, like: “Who wins the most second serve points?” or “Who has the best ratio of winners to unforced errors?” And some have great, not entirely obvious value. Most insiders, including Arias, put a lot of stock in second-serve points won stats. “That one tells you who is winning the neutral rallies,” he said. “Generally, I'd like that person to have a better chance to win.”

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The shortcomings of stats have helped propel the march of a related applied science, analytics, based on metrics that can be tracked—even in real time. That’s why you see many player associates courtside, their noses buried in computer tablets.

Hawkeye, provider of the original electronic line-calling system that transformed tennis, along with other entities now create real-time data streams on everything from height-of-bounce on a given court to positioning, serving and returning patterns, distance run and other technical and bio-mechanical data, including a player’s degree of body rotation while making a shot.

These are all handy if not 100% guaranteed knockout tools. In fact, overreliance on stats and analytics can lead to damaging, rigid thinking. Hence, Annacone’s advice to proceed with caution in the realm of stats. Many coaches agree.

Boynton said that a coach must be really careful not to suggest to his player that some metric or other is a magic bullet, even though such information can be a confidence booster. Knowing that your opponent’s serve usually goes straight down the pipe at deuce is valuable, but who really knows when or why an opponent will break tendency and leave his opponent confused? After all, every player is also aware of his or her own stats.

It’s an important point because confusion, overthinking, and color-by-numbers tennis is generally anathema to quality players. Arias said he isn’t the “biggest fan” of analytics because part of the game he loves is the challenge to “out-think” an opponent, or instinctively “feel” what the moment calls for from you.

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In individual sports, players have innate skills and with too much data they’re just not going to feel it, or get that instinctive sense of, ‘This is going to happen,’ or, ‘This is what I’m going to do.’ Paul Annacone

Annacone hits a similar theme. Loading up a player with metrics and data can “suffocate” his or her instincts, which is never a good thing. “In individual sports, players have innate skills and with too much data they’re just not going to feel it, or get that instinctive sense of, ‘This is going to happen,’ or, ‘This is what I’m going to do.’”

He cited a time when his protege Pete Sampras, in a Wimbledon final with his career rival Andre Agassi, unexpectedly began to hit second serves fully seven mph faster than in previous matches. After Sampras won, Annacone asked him why he made that strategic choice.

“Because it was Andre,” Sampras said, demonstrating yet again his instinct for doing the right thing—sans analytics.

Now that analytics are so influential, it pays to remember that their message should be delivered carefully. Boynton liked to “frame it up” a certain way for his player: “Hey, look, if you can’t get a feel, or some tell, about what your opponent’s doing to bother you, here's a tendency. Don’t make it non-negotiable. You want the player to make the judgement and the final decision.”

Sometimes, though, even that is of little help. As Arias said, “When you watch [Jannik} Sinner, and he's hitting every ball a billion miles an hour into the corner, you know that you're in trouble regardless of what the stats say.”