Jasmine Paolini’s High-Wire Act

Jasmine Paolini at the 2022 Transylvania Open. Credit: Nuta Lucian

There are unorthodox aging curves, and then there’s whatever the hell Jasmine Paolini is doing right now. The best women tennis players tend to make their presence known in their late teens. I wrote earlier this year about the “improbable rise” of 22-year-old Emma Navarro.

Paolini is 28.

When Paolini was the age that Coco Gauff is now, she was ranked just inside the top 300, fresh off a first-round loss at an ITF $25K in Bulgaria. When she was the age that Iga Swiatek is now, she had finally cracked the top 150, about to head to Wimbledon qualifying. (She lost in the first round there, too.) When she was the age that Aryna Sabalenka is now, she had just stumbled through a four-match losing streak to the likes of Jil Teichmann and Irina-Camelia Begu that knocked her out of the top 50.

Just 16 months ago, Paolini was once again outside the top 50. For a five-foot, four-inch counterpuncher with no obvious weapons, she had achieved a great deal. There was little reason, though, to think she could climb much higher. Her peers were getting bigger, the game was becoming ever more aggressive, and she was reaching the age at which WTA stars begin to think about what else life might hold for them.

Then she started winning.

Since leaving Wimbledon last year, the Italian has won 66 of 99 matches, including two major semi-finals and five top-ten scalps. She picked up her first 1000-level title and made four other finals. Yesterday, she led Team Italy to a Billie Jean King Cup crown, starring in both singles and doubles en route to the championship. Her ranking is up to an astonishing 4th in the world. As if that weren’t enough, she’s in the top ten in doubles.

None of this was supposed to happen. Paolini’s late-2023 surge to the top 30 was one thing; what has happened since simply defies belief. How has she managed it? Is it a fluke, or will we see the Italian at the 2025 year-end championships as well?

Opportunistic effects

First, a bit of a caveat. Paolini, like Taylor Fritz, has played the official ranking system like a Stradivarius. She reached only three finals in 2024, yet two of them were slams. The other was a 1000. She earned huge chunks of points for a semi-final defeat of Mirra Andreeva at Roland Garros, a semi-final squeaker against Donna Vekic at Wimbledon, and a Dubai title that didn’t require her to face a top-ten opponent.

None of this is meant to take away from Paolini’s accomplishment. She beat the players in front of her, and in the case of Andreeva, she did so in emphatic fashion. The point is that her top-four finish has more to do with good timing than consistently dominant play.

My Elo ratings offer a second opinion, using an algorithm based on the quality of her opponents, rather than the venue and round of each match. By Elo, she stands in 9th place, just ahead of Madison Keys and Diana Shnaider, well back of Jessica Pegula and Elena Rybakina. Still a very good season, if a bit less astounding.

Even more revisionist is the total-points-won leaderboard. Going into the BJK Cup Finals, Paolini had won 51.8% of her total points this season. That’s a respectable rate, especially for someone who hovered in the 50% range for most of her tour-level career. But it is not typically top-five, or even top-ten material:

By this metric, the Italian stands in 19th place among the WTA top 50, behind a handful of players who didn’t even crack the official top 20. That doesn’t really mean she’s the 19th best player on tour: She faced one of the toughest schedules of anyone. Much as I love both Yulia Putintseva and counterintuitive arguments, I’m not going to try to convince you that Putintseva had the better season.

Still, Paolini’s position on the TPW list tells us something about how she won her matches. She didn’t lose many blowouts, but she didn’t win many, either. (She certainly didn’t get in the habit of spanking opponents like Swiatek and Sabalenka do.) Ten of her wins required a third set. Two victories–including the Wimbledon semi-final–came despite losing more points than she won.

The margins were not so narrow that we can ascribe the Italian’s breakout to luck. (Though the Vekic match could have gone either way, to say the least.) But this is the high-wire act that took Paolini to the top. She doesn’t have the tools to bludgeon her opponents. She has done a lot of things right to win 42 matches this year. To keep winning at a two-of-three clip, she’ll need to continue executing the new game plan to near-perfection.

The new game plan

It’s a bit tricky to isolate the key changes in Paolini’s approach, because–like Qinwen Zheng–she’s doing almost everything better than she did before the surge. That said, a few things stand out.

Check out the Italian’s breakdown of points won by rally length (in Match Charting Project-logged matches) before this season, compared with her performance this year:

Span     1-3 W%  4-6 W%  7-9 W%  10+ W%  
2016-23   49.1%   46.5%   51.0%   49.4%  
2024      49.8%   54.3%   56.6%   49.1%

Paolini’s improvement in 7- to 9-stroke rallies is significant, and her gain in the 4- to 6-shot category is enormous. In very short points and very long ones, little has changed.

Especially in the categories of shorter points, we need to keep in mind what these win rates measure. It’s tempting to think of a prototypical short point, then imagine Paolini, instead of her opponent, winning it. But the length of a given point is not handed down to us by God. When someone like Paolini starts winning more shorter points, it’s because she is ending them before they become long points, and/or she is preventing her opponents from ending points quickly.

The Italian can hardly stack up one-shot points (unreturned serves), and she can’t even reliably put away plus-ones–though she is doing that more than she used to. Instead, like the expert doubles player she has become, she can structure points that inch closer and closer to a point-ending opportunity. Call it plus-two tennis, aggressive point construction for undersized counterpunchers.

The plus-two forehand

Tactics are one thing; Paolini is a top-ten player because she has executed them so well. Her forehand is a big reason why.

She is ending points with her forehand at a much better clip than she did before the calendar flipped to 2024, and her inside-out forehand has seen particular improvement:

Span     FH Wnr%  DTL Wnr%  IO Wnr%  FHP/100  
2016-23    11.7%     17.7%     6.2%      2.9  
2024       17.5%     25.2%    13.3%     10.2

Here, “winners” refer to both clean winners and shots that induce forced errors. Through 2023, Paolini’s forehand winner/forced error rate of less than 12% put her in the bottom quarter of tour regulars. 17.5% moves her to the top third, not far behind Swiatek and Keys. The same stat for inside-out forehands (IO Wnr%) doesn’t put her in quite the same company, but it is an even better reflection of the tactical shift. Before, the Italian rarely used that shot as an offensive weapon; now it is a regular part of the arsenal.

The bottom line is reflected in the Forehand Potency (FHP/100) numbers. The number of points Paolini earns with her forehand more than tripled from previous seasons to 2024. That doesn’t quite account for the entire shift from a top-50 player to a top-fiver, but it explains a whole lot.

And the no-fearhand

One side effect of the Italian’s forehand-centered strategy is that she is less afraid of other players’ forehands.

Again, Paolini is doing just about everything better. For instance, 22% of her first serves went unreturned in 2024, compared with 20% in the past. Nice little boost, but not something you would notice by watching a couple of matches. A bigger shift is where she puts the first serves:

Span     1st Unret%  <=3 W%  RiP W%  D Wide%  A Wide%  
2016-23       20.2%   28.1%   48.3%    25.0%    45.7%  
2024          21.8%   34.8%   53.4%    37.4%    44.8%

Check out the rate at which she is hitting deuce-court first serves wide (D Wide%). 25% to 37% is a massive change, and one that would be dangerous for a different sort of player. In the deuce court, the down-the-tee serve is the conservative one: It goes to the backhand of a right-handed returner, and since it lands in the middle of the court, the returner doesn't have any sharp angles to exploit. The wide serve is the opposite, feeding forehands to opponents like Sabalenka, Rybakina, or Zheng along with the angles necessary to turn them into winners.

What Paolini knows--again, like a savvy doubles player--is that most players will fail to convert the majority of those opportunities, even if they occasionally smack a highlight-reel return winner. The Italian didn't crack the top five by running the table against the elite. Most of her 42 wins came against the next rung of competitors, women who are often held back by inconsistency. Paolini pushed them off the court, giving the choice of either going big (and frequently missing), or sending back a shot that she could handle with her own (improved!) forehand.

All those deuce-court wide serves explain how Paolini picked up so many more plus-one winners (the <=3 W% column) and converted so many in-play returns overall (RiP W%). Every individual wide serve is a gamble, but the Italian has discovered that, on net, they pay off.

The way forward

I'm a bit surprised to find myself concluding that, yes, Paolini might just maintain this level. The odds are heavily against another top-five finish. That was a quirk of her draws and well-timed (probably accidental!) peaks. But 52% of total points? A single-digit year-end ranking? Maybe!

Once I began thinking of the Italian's singles play in terms of doubles strategy, it all clicked. Her anticipation is outstanding--and like everything else, it is better than it was last year. She often wins points without working particularly hard. She's in the right place to end the point on the fifth or sixth shot of the rally. (That place is increasingly at the net. She came to net more in 2024, and she won more of those points than before, too.) Anticipation isn't a skill that will deteriorate with age, nor is it one that opponents can neutralize.

Paolini's new point-shortening, forehand-smacking, deuce-court-serving tactics aren't going to earn her many big upsets, just as they haven't so far. The strongest players--not coincidentally, often the ones with the most fearsome forehands--are the ones in the best position to take advantage the wide deuce-court serves and force the Italian both to move off the baseline and rely more on the backhand.

But a top-ten season doesn't require a pile of top-ten victories. Paolini was 3-6 against that group this year, and that included one win against a fading Ons Jabeur and another in Riyadh against a rusty Rybakina. The Italian's finish owed much more to her 38-15 record against everyone else. Despite the improbability of a top-ten debut at age 28, Paolini has built a game capable of repeating the feat in 2025.

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The Riddle of the Ruud-Rublev Reversal

Andrey Rublev and Casper Ruud

The story of the the 2024 ATP Tour Finals was the dominance of Jannik Sinner. I’ll refer you to what I wrote after the Australian Open: Yes, Jannik Sinner Really Is This Good. He just passed the 2,300 Elo threshold, becoming only the 12th man since Rod Laver to do so. When I update the Tennis 128 in a few weeks, he’ll be on it.

For all that, I’m preoccupied with something else. On the final day of round robin play, Casper Ruud beat Andrey Rublev to secure a place in the semi-finals. It was their eighth meeting and the Norwegian’s third victory:

Notice anything odd? Take away the unfinished Australian Open tilt, and the head-to-head breaks down precisely on surface lines. Rublev has won all four encounters on clay, while Ruud has run the table on hard courts. Not just any hard courts: indoors, at the Tour Finals.

We can look to external factors to explain some of the individual results. Casper had more at stake on Friday than the Russian did, with a chance to qualify for the final four. Rublev is older and broke through correspondingly earlier, so he was the natural favorite in their early meetings. Injuries and illness may have influenced another outcome or two, even aside from the retirement in Melbourne.

Still: 0-3 in completed matches for the ball-basher on hard courts, and 0-4 for the Roland Garros finalist on clay. Something’s going on here.

Not so fast

Rublev, to be fair, is hardly a fast-court specialist. His first tour-level title came on dirt in Umag, and he picked up a Masters crown last year in Monte Carlo, on one of the circuit’s slowest surfaces. The Russian’s forehand is a weapon in any conditions, and slow courts can disguise some of his weaknesses.

On the other hand, however much Rublev likes the dirt, Ruud likes it more. Earlier this year, I quantified the notion of “surface sensitivity,” the degree to which a player’s results are influenced by court speed. Rublev scored at -2.2, indicating that he does better on slower surfaces, a bit more so than the typical tour regular. Casper was considerably further down the list, at -5.0. The rating tells us that he’s more receptive to slow courts than Pablo Carreno Busta or Jaume Munar. He’s grades about the same as Diego Schwartzman.

Maybe the oddball head-to-head is a quirk of when the pair have met? Not all hard courts play fast, and not all clay behaves like the crushed brick at Roland Garros. Here are the venues for the seven completed meetings, along with my ace-based surface speed rating for each. Ratings above 1 are faster than average, below 1 are slower:

Year  Tournament   Winner  Speed  
2024  Tour Finals  Ruud     1.36  
2023  Bastad       Rublev   0.86  
2022  Tour Finals  Ruud     1.50  
2021  Tour Finals  Ruud     1.51  
2021  Monte Carlo  Rublev   0.54  
2020  Hamburg      Rublev   0.52  
2019  Hamburg      Rublev   0.74

Hypothesis denied! The 2021 and 2022 Tour Finals were the fastest conditions of their respective years, while Monte Carlo was the slowest of the entire 2021 season. Last year’s Bastad surface was fairly neutral for a clay court, but the rest of the Ruud-Rublev showdowns took place on fast hard courts or slow clay.

We could always mark down a string of seven surface-confounding results to luck, especially when both players are capable in all conditions. But it would be far more satisfying to find an explanation that tells us something about the players and their particular skills.

Stoppable

We don’t have to look far. Here are Casper’s win rates on first and second serve points against Rublev, separated by surface:

Surface  1st W%  2nd W%  
Clay      56.8%   48.4%  
Hard      72.7%   50.7%

Everybody wins fewer first serve points on clay than on hard courts, but not like this. The average gap for top-50 players in 2024 is four percentage points–not sixteen. At tour level against the entire field, Ruud has shown an even smaller difference, winning 73.1% of hard-court first-serve points against 71.2% of those on clay.

Rublev is not a brilliant returner. He’s a serviceable one with tactics to match. He often struggles to get first serves back in play. On second serve, he’s unafraid to unleash his weapons, accepting some errors in exchange for tilting other points in his favor. On clay, he’s able to turn a few more first serves into rally openers. In 2024, his gap between clay and hard-court first-serve return points won was bigger than average. But not nearly as wide as it is against Casper.

When it works…

Ruud, like many men who have developed into strong clay-courters, doesn’t have a monster serve. He can place it, he can disguise it, and he knows how to play behind it. On a fast hard court, those skills–combined with a bit more risk-taking–can result in numbers that look more like those of a big server. Against Rublev last week, he won just shy of 80% of his serve points, supported by 15 aces.

When the Norwegian is hitting corners and the ball is skimming off a court like the speedy one in Turin, Rublev is helpless. Over his career, according to the nearly 200 matches logged by the Match Charting Project, he puts 58% of first serves back in play. Against Casper on Friday, he didn’t manage 50%–a repeat of his performance on the same court two years earlier.

Rublev’s first-serve-return struggles on hard court contrast with how he feasts on Ruud’s serve on clay. The next table shows the rate at which the Russian puts Casper’s first serves in play, as well as his win percentage when he does so:

Match                Result  1st: RiP%  RiP W%  
2024 Tour Finals RR       L      46.9%   43.3%  
2023 Bastad F             W      64.6%   61.3%  
2022 Tour Finals SF       L      45.7%   50.0%  
2021 Tour Finals RR       L      67.5%   51.9%  
2021 Monte Carlo SF       W      84.4%   59.3%  
2020 Hamburg SF           W      91.4%   59.4%

The exception to the rule here is the 2021 Tour Finals match, which ended in a third-set tiebreak. It was the closest either man has come to securing one of the matches he “should” have won. Rublev won 52.9% of total points, but Ruud served his way out of just enough jams to come through.

On the very slow Monte Carlo and Hamburg courts, Rublev’s ability to handle the Norwegian’s first serve meant that Ruud was left with no edge whatsoever. Casper might be the superior baseliner, but he started too many points at a disadvantage. The picture might look different if they played on slow clay today, since Ruud is stronger and tactically savvier on serve. But I imagine it would still be a struggle, one in which few of Casper’s service games would sail by quickly.

Pundits like to say that tennis is a game of matchups. They often overstate their case: The better player (by ranking, or Elo rating, or whatever) usually wins. When they don’t, it isn’t always because of some quirk in the head-to-head. With Rublev and Ruud, though, such a quirk dictates the results. Few men are able to erase Rublev’s advantage on a hard court as much as the Norwegian can. Casper’s first serve is rarely so ineffectual as when the Russian is waiting for it on dirt. Ruud is set for another big European clay swing next year–so long as his buddy Andrey lands in the other half of the draw.

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The Newly Opportunistic Taylor Fritz

Taylor Fritz at the 2023 US Open. Credit: Andy M. Wang

Taylor Fritz has been remarkably consistent over the last three seasons. He ended the 2022 campaign ranked 9th, finished last year 10th, and enters this week’s Tour Finals in 5th place, with a chance to overtake Daniil Medvedev for a spot in the top four.

Take a look at his top-line statistics for 2022, 2023, and 2024. They’re sorted by total points won (TPW). Can you tell which one belongs to his career-best current season?

Year   Win%   1st%   2nd%    RPW    TPW  
???   68.8%  78.4%  54.3%  37.7%  53.0%  
???   70.4%  78.3%  55.8%  36.2%  52.8%  
???   69.1%  76.4%  52.6%  38.2%  52.4%

You might be tempted to go with the first row, since he won the most points then. But the margin is small, and he won matches at a better clip in the second. Wait, though: He snagged the most return points in the third season, and more breaks of serve are particularly crucial for a player hovering in the 36% to 38% range.

I won’t leave you hanging. The second line belongs to 2024. Here are the three stat lines, now sorted by season:

Year   Win%   1st%   2nd%    RPW    TPW  
2024  70.4%  78.3%  55.8%  36.2%  52.8%  
2023  68.8%  78.4%  54.3%  37.7%  53.0%  
2022  69.1%  76.4%  52.6%  38.2%  52.4%

The 27-year-old American is clearly doing something right that isn’t captured by the usual stats. 10th to 5th is a major move. Last year he didn’t even qualify for the Tour Finals. After beating Medvedev yesterday, he’s one win away from a probable berth in the semis. What’s going on here?

All the right matches

The official ranking system ensures that tournaments and matches are very much unequal. When Fritz beat Frances Tiafoe in the Acapulco quarter-finals last year, he gained an additional 90 points for his semi-final showing. When he slipped past Tiafoe in this year’s US Open for a place in the championship match, he earned a whopping 480 points.

I could just about stop here. 480 points is the difference between Fritz’s current point total and 8th place. A slightly bigger difference of 560 points would knock him down to 10th, and he’d be hanging around Turin this week as an alternate. His stats would barely change, but the story of his season would be very different.

It’s not just the Tiafoe match; it’s more than the US Open final. 2024 was the first year that Fritz lived up to expectations at the slams in general. Here are his grand-slam win totals back to 2018:

Year  Wins                  
2024    17                  
2023     8                  
2022     8                  
2021     6                  
2020     6  * no Wimbledon  
2019     4                  
2018     4

No top tenner would be happy with just eight wins at majors. Simply reaching the fourth round at each slam adds up to 12. In 2022, Fritz lost five-setters to Stefanos Tsitsipas and Rafael Nadal, then fell to a streaking Brandon Holt in Flushing. Last year, he suffered two second-round exits. Both five-setters, the losses came against Alexei Popyrin in Australia and Mikael Ymer at Wimbledon.

When the 2024 season kicked off, Fritz had just two major quarter-finals to his name. His career record in five-setters was 8-10.

Since then, the American has reached three more quarters (including the US Open final run). He won four five-setters against just one defeat. He avenged the Melbourne loss to Tsitsipas and twice upset Alexander Zverev, a player who had beaten him in five of eight previous meetings.

The re-balancing

The odd thing about Fritz’s season is that his slam success has been offset by weaker results elsewhere. Returning to the observation I started with: He won nine more matches at majors in 2024 than in 2023, but his winning percentage barely budged. Instead of losing to Ymer or Holt on a big stage, he fell to Matteo Arnaldi in Acapulco, Thiago Seyboth Wild in Miami, Alex Michelsen in Geneva, and more.

It was a smart trade, though it was surely not a premeditated one. You can train with the majors in mind, but you can hardly punt an early-round match at a 250 with any kind of hope that it will result in a quarter-final victory at the next slam.

There’s another category, though, in which Fritz may have used stronger tactics to get better “luck.” Here are the American’s tiebreak records since 2021:

Year  TB W-L    TB%  
2024   21-11  65.6%  
2023   25-17  59.5%  
2022   24-20  54.5%  
2021   20-15  57.1%

The 2023 mark of 59% is about where Fritz should be, based on the rate at which he normally wins serve and return points, combined with the matches in which he finds himself in tiebreaks. 2024 was the first season he beat tiebreak expectations by a non-negligible margin.

This could be luck. Tiebreak records fluctuate, and very few players sustain records above or below expectations for long. Still, the American might have figured something out. In the sample of 2024 matches logged by the Match Charting Project (plus several others from grand slams), Fritz is serving way better in tiebreaks than he has in the past:

Year  TB SPW  
2024   80.3%  
2023   65.6%  
2022   70.9%  
2021   65.0%

80% is Isner territory. In the improbable event that Fritz can sustain these kinds of numbers, coupled with a solid return-points-won rate around 38%, he should be winning even more tiebreaks than he already does.

I don’t want to overemphasize tiebreaks: After all, his 21-11 record is only one or two tiebreaks better than it “should” be. On the other hand, it’s easy to scan through Fritz’s career results–including those at majors–and see how one or two tiebreaks could change the story. He took a first-set tiebreak from Tsitsipas in Melbourne this year. He split two against Zverev at Wimbledon, then took two of two from the German in New York. Take one of those away–just one!–and again, he might be watching the Tour Finals from the sidelines.

Zverev tolerance

Regardless of whether tiebreak luck played a role, Fritz’s two major victories over Zverev helped to define his season. Neither pre-match betting odds nor my Elo ratings predicted an American victory on either occasion.

Both Fritz and Zverev are tall guys with big serves; either one can put away a service game with four quick strikes. One key difference between them is that Zverev is more patient, comfortable playing long points from the baseline. This isn’t necessarily an asset: It isn’t always in the German’s interest to let matches go that way. But if you’re going to pick one of these two guys to play points from the baseline, it’s pretty clearly Zverev.

In the US Open quarter-final, though, 39 points went ten strokes or longer. Fritz won 20 of them. In the fourth-set tiebreak, three and half hours into the battle, the American won two of two: a 24-stroke grinder that Fritz finished at the net, then a 12-shotter on match point that Zverev squandered with a unforced forehand error.

Two lessons jump out. First, the American can hold his own from the backcourt with one of the best baseliners in the game, at least on a hard court. Second, that skill doesn’t seem to fade with fatigue, something that might have caused Fritz’s five-set struggles in the past.

A third takeaway may be even more important. Instead of the numerator–20 points won–consider the denominator: 39 points played. The first time Fritz and Zverev met at a major, at Wimbledon back in 2018, barely half as many points lasted so long, even though the match itself was longer. Yes, the surface kept that number down, but not by a factor of two. At Washington early in Fritz’s career, on a surface more like that in Flushing, the two men played an entire match with just one rally that reached ten strokes.

In that 2018 Wimbledon meeting, Fritz held his own in the long rallies, winning 9 of 21. The problem was his rush to avoid them. He committed 56 unforced errors to the German’s 36.

Zverev keeps his unforced error rates down because he is willing to wait. He forces opponents to take risks unless they want to spend all day grinding out baseline battles. Most players in the Fritz mold–including Fritz himself, in the past–opt to take their chances. They usually lose, which is why Zverev is ranked second in the world. The American has steadily improved his groundstrokes and his fitness to the point that he doesn’t need to take low-percentage big swings. It’s no guarantee of victory–after all, Fritz won just 50.9% of points in the Flushing four-setter–but it’s a better bet than the alternative.

Let’s play ten

There’s a wider lesson here, and not just for Taylor Fritz. We tend to think of long-rally proficiency as a clear-cut skill. Yes, some players are better at it than others, but not by a wide margin.

Here are the long-rally (10+ shots) winning percentages for the ATP top ten, based on Match Charting Project data for the last 52 weeks:

Player            10+ W%  
Alex de Minaur     57.4%  
Carlos Alcaraz     57.1%  
Jannik Sinner      55.8%  
Daniil Medvedev    55.0%  
Grigor Dimitrov    54.2%  
Novak Djokovic     52.8%  
Andrey Rublev      51.8%  
Casper Ruud        50.2%  
Alexander Zverev   50.2%  
Taylor Fritz       46.8%

Before I studied this, I would’ve expected considerably more dispersion. While every edge counts, this one is not as crucial as it gets credit for. Fewer than one in ten points reach the long-rally threshold, so even the most extreme gaps–like that between Fritz and de Minaur here–would determine the outcome of only the closest matches.

More important, I suspect, is willingness to play these points. Fritz is never going to crack the top half of a list like this. He has–to his credit–maxed out the rally tolerance that his size and physical gifts will grant him. Still, a 47% chance of winning a protracted point is better than his odds after belting a low-percentage salvo to avoid the battle altogether.

Players who serve as effectively as Fritz does tend to be considerably less sturdy from the baseline. Pros with his (adequate if not world-beating) groundstrokes are often less inclined to rely on them. One-dimensional big servers almost never reach the top five. Yet Fritz, combining his primary weapon with a tactical savvy that allows him to maximize the rest of his assets, has done exactly that.

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Qinwen Zheng’s Rising Tide

Qinwen Zheng at the 2024 US Open

Since a first-round exit to Lulu Sun at Wimbledon this year, Qinwen Zheng has transformed herself from a rising prospect to a force at the top of the women’s game. The 22-year-old has won 30 of 35 matches, picking up three titles including an Olympic gold. In her first appearance at the tour finals this week, she has defeated two top-five players and earned a place in the semi-finals.

Zheng currently sits at 7th in the official rankings, equal to her career best. Her performance in Riyadh will move her up to at least sixth. Elo, a leading indicator as usual, already considers her the third-best player in the world, behind only Aryna Sabalenka and Iga Swiatek. The Chinese player is riding an astonishing 30-2 streak against everyone not named Sabalenka, so it’s hard to argue.

What has changed? Zheng has long been ticketed for big things. Her January run to the the Australian Open final indicated that she was reaching her potential. But she made only two quarter-finals in the next ten events, losing both. There were clear weaknesses in her game then. Has Qinwen 2.0 plugged those gaps?

Lifting all metrics

When I last wrote about Zheng, I referred to her serve as “under construction.” Her first serves were (and are) among the very best in the game. But she missed often, and her second serve was below average for a top-50 player.

I proposed an admittedly theoretical solution, that she could play somewhat more conservatively on the first serve, still winning plenty of points. Then she could go (relatively) bigger on seconds, trading a few more double faults for better results. The bottom line, at least according to the algorithm, was that the shift would increase her serve points won from a good 60.1% to a great 61.7%.

She hasn’t done any of that. Yet since leaving Wimbledon, she has won 63.3% of service points. That’s better than the full-season mark of anyone except Swiatek.

Qinwen found a blunter solution: She just got better at everything. Here’s an overview of her serve and return results for the two halves of 2024–up to and after Wimbledon–as well as her hard court results in 2023:

Time Span        W-L  1stIn%  1stW%  2ndW%    SPW    RPW  
2023 Hard      26-12   51.9%  74.3%  45.7%  60.5%  43.6%  
2024 1st half  19-12   51.5%  74.9%  45.5%  60.6%  42.9%  
2024 2nd half   30-5   53.8%  76.5%  47.9%  63.3%  45.9%

First serves in? Up two percentage points. First serves won? Two points. Second serves won? Two points. Return points won? Three points from the first half of 2024 to the second, even though the average surface is faster.

These are enormous shifts. 54% of first serves in still leaves her near the bottom of the table, but moving from 60.6% to 63.3% serve points won is the difference between the edge of the top ten and, as noted, number two. Key to the move is the rate of second serves won, which improved from the bottom third of tour players to the top half. On return, 42.9% to 45.9% is a jump from the bottom quartile of tour regulars to the top.

In short, Zheng went from having weaknesses to not having weaknesses. It’s never easy to divvy up the credit between player and coach, but if Pere Riba doesn’t win coach of the year, we might as well quit giving out the award.

Ratioing the tour

One of the goals of my research is to help us be more specific when we analyze players. Zheng’s various points-won rates give us a clearer view than just going goggle-eyed at a 30-5 record. But it’s tough to pinpoint a player’s improvement when she suddenly does everything better.

Qinwen’s rates of winners and unforced errors leave us in the same conundrum: She’s just gotten better by every conceivable metric. Still, I have to share. Sometimes it’s worth going goggle-eyed.

I have winner and unforced error stats for a limited subset of matches–77, in Zheng’s case–from a combination of grand slam data and the Match Charting Project. For the 58 matches through the loss at Wimbledon, she hit winners on 16.9% of points, versus UFEs on 19.2%. That works out to a ratio of 0.88, which is quite good. Commentators like to point to a 1:1 ratio as a goal, but that’s relatively rare on the women’s tour. 0.85 is usually sufficient to win a match.

Since July, the Chinese player’s W/UFE rates have basically flipped. In 18 matches worth of data, she’s hit winners on 19.3% of points, against a 17.0% unforced error rate. Those numbers are good for a ratio of 1.14. Here’s a complete list of the women who have posted better ratios this year:

1. Aryna Sabalenka

That’s it. With more complete data, it’s possible that Zheng would outscore Sabalenka, too. We have W/UFE for four of Qinwen’s five second-half losses, but only 14 of 30 wins. The sample is probably a bit biased against her.

The backhand complement

When I wrote about Zheng in January, her forehand–assessed by my Forehand Potency (FHP) metric–already ranked in the top ten among tour regulars. Her backhand remained a question mark.

If there are any specifics we can glean about the 22-year-old’s improvement, it is here. Until the beginning of this season, her backhand was, more or less, a neutral shot. The Backhand Potency (BHP) stat measures how often a shot ends the point for or against the player, as well as how often it sets up a point-ending shot shortly thereafter. In 2024, Qinwen’s backhand has been five times more effective that it was before:

Time Span  BHP/100  Negative Matches  
2021-23        1.2          13 of 32  
2024           6.3           6 of 34

In the past, the Zheng backhand cost her points–that is, it rated a negative BHP–nearly half the time, in 13 of 32 charted matches. This year, it has rarely done so. While BHP per 100 backhands (BHP/100) can’t be directly converted to a number of points per match, it’s safe to estimate that her backhand is now worth at least two or three points per match that she wasn’t winning before.

A few points per contest are enough to separate a good player from a great one. The backhand alone accounts for a big chunk of the gap between early Qinwen and the current unbeatable model.

We can even see the connection between BHP and return points won. This year, Zheng has gotten more returns in play: about one percentage point more, despite the fact that she has played Sabalenka so many times. Often, pros increase that metric by playing more conservatively. They send more balls back but do so weakly, losing most of those points. The Chinese woman, on the other hand, has also improved her win rate when she puts the return in play. That number–at least in the sample of charted matches–has risen from 53.8% to 56.8%.

Return stats aren’t all about the backhand, but when someone has as dangerous of a forehand as Zheng does, opponents make the return as much about the backhand as they can. No longer anything resembling a servebot, Qinwen threatens in more and more return games. Last year, she earned a break point in 43% of (charted) return games; this year, she is up to 49%.

Up and to the right

At the risk of repeating myself: Every trendline for the 22-year-old is headed in the right direction.

Zheng has never beaten Sabalenka, but after losing 6-1, 6-2 at the US Open, she pushed the Belarusian to three tough sets in Wuhan. She had lost five straight to Swiatek, then straight-setted her on the Parisian clay at the Olympics. Last fall, Qinwen salvaged just three games against Elena Rybakina in Beijing. This week she beat her. Zheng needed three sets to get past Jasmine Paolini last month; yesterday she allowed the Italian a measly 37 points.

The only player left in the Riyadh field that the Chinese woman hasn’t defeated is Coco Gauff. They’ve met just once, in Rome this season. Zheng won just 44% of points that day, landing an abysmal 41% of first serves. Should the pair meet to decide the season-ending championship, Gauff may still have enough of an edge to come out on top. But if we’ve learned anything from Qinwen’s four-month surge, it’s that she’s going to play a whole lot better this time.

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Aryna Sabalenka, Drop Shot Queen

Aryna Sabalenka, watching another poor woman hopelessly run around

In May this year, Aryna Sabalenka unleashed a new weapon: a drop shot she was willing to use far more than ever. After winning six of six drop-shot points in a Rome first-rounder against Katie Volynets, Sabalenka inflicted 28 droppers on Elina Svitolina. That match went to a third-set tiebreak, and her 15 outright drop-shot winners represented more than the margin of victory.

In her career up to that point, Sabalenka’s drop shots represented 1.1% of her (non-serve) strokes–about half the tour average of 2.2%. That rate nearly quadrupled, to 4.1%, for her eleven matches in Rome and Paris. On faster courts since, it has fallen, but not all the way back. Her drop-shot rate since June has been 1.9%. As we will see, the weapon has continued to give her more value even as she uses it less often.

The tactic makes perfect sense for a player with Sabalenka’s skills. She hits hard from the baseline, so opponents are usually positioned defensively, on the back foot. She’s capable in the forecourt (former doubles #1!), so not only does she have the touch to pull off the deception, she has the ability to deal with the rapid-fire net play that can ensue when someone runs a drop shot down.

The only question–had we thought to make the suggestion, say, a year ago–was whether the idea appealed to her. Not everyone is Carlos Alcaraz, ready to throw the tennis equivalent of a curveball into any point. Sabalenka was doing fine bashing groundstrokes into submission; why change? Now we know she’s comfortable with the tactic, even if 4% is probably reserved for the slowest courts.

How, then, does Aryna’s drop shot stack up against those of her peers, in terms of frequency, success rate, and value? I wrote two articles in March that outlined various ways of analyzing drop shot tactics. Those pieces looked at Alcaraz, Alexander Bublik, and the men’s game in general. The same approach can shed light on Sabalenka and the women’s tour, as well.

Getting the drop

All the data in this piece is based on the shot-by-shot logs from the Match Charting Project. I’ve limited the scope to the last decade. Nearly every tour-level Sabalenka match is charted, but for many other players, coverage is more limited. It’s also not necessarily random, so these numbers are approximate.

It’s also important to define “drop shot.” For the purposes of this piece, I’m looking only at the first drop shot in each point. “Re-drops” are a skill of their own, and probably a very different one. They are also tough to study because they are so much rarer than the already-uncommon standard drop shot. So we skip them for now.

Let’s start with the most prolific WTA drop-shotters since 2015. Remember that tour average is 2.2%–one dropper per 45 shots or so. Here are the thirteen women who have equaled or exceeded clay-Aryna’s 4.1% for their entire (charted) careers:

Player                Drop%  
Yulia Putintseva       8.6%  
Ons Jabeur             8.2%  
Laura Siegemund        7.6%  
Anastasija Sevastova   6.6%  
Marketa Vondrousova    6.3%  
Petra Martic           5.6%  
Kristina Mladenovic    5.2%  
Su Wei Hsieh           4.5%  
Agnieszka Radwanska    4.2%  
Karolina Muchova       4.2%  
Kiki Bertens           4.1%  
Viktorija Golubic      4.1%

Everything checks out so far. Putintseva dropshots to drive you nuts, Jabeur hits them to show off, and Aga did it just because she could.

The other end of the list has its amusements as well. In over 50 charted matches, spanning over 7,000 points, Camila Giorgi hit five drop shots. Yes, five. Two of them went for winners, and she lost the other three.

More important than frequency is points won. Here are the 14 women whose career drop-shot win rates surpass Sabalenka’s recent clip of 55.6%:

Player                 Drop%  Point W%  
Dominika Cibulkova      2.5%     61.4%  
Qinwen Zheng            2.0%     60.7%  
Sara Sorribes Tormo     2.3%     60.4%  
Ashleigh Barty          1.7%     59.5%  
Barbora Krejcikova      1.8%     59.0%  
Marketa Vondrousova     6.3%     58.7%  
Emma Raducanu           1.6%     58.3%  
Liudmila Samsonova      1.3%     58.2%  
Bianca Andreescu        3.2%     58.1%  
Anett Kontaveit         1.1%     57.4%  
Sofia Kenin             4.1%     57.4%  
Aliaksandra Sasnovich   3.3%     56.6%  
Sorana Cirstea          1.9%     56.3%  
Kiki Bertens            4.1%     56.1%  
…                                       
Average                 2.2%     52.6%  
…                                       
Aryna 2017-Apr '24      1.1%     53.2%  
Aryna 2024 Rome/RG      4.1%     61.9%  
Aryna 2024 2nd half     1.9%     55.6%

There is virtually no correlation between frequency and success rate, so players like Vondrousova and Kenin (and slow-clay Sabalenka) really stand out.

Here’s the same dataset, with more players, in visual form:

Most women cluster in the 1-2% frequency range, regardless of their drop-shot skills. Vondrousova and Putintseva really stand out for their combination of frequent attempts and consistent success.

Chasing down value

As much as youngsters dream of someday showing up on a leaderboard on this blog, what really matters is winning points. You can do that by hitting tons of drop shots and winning those points at a decent rate (like Putintseva), or by choosing moments carefully and executing well (like Qinwen Zheng).

Assume for the time being that the typical drop shot is hit from a perfectly neutral position, one in which each player has a 50% chance of winning the point. Combine the two metrics we’ve seen so far–multiply frequency by the difference between winning percentage and 50%–and we have the value added by a player’s drop shots. I’ve multiplied the results by 1,000 so all the zeroes don’t make our eyes hurt.

Player                 Drop%  Point W%  Drop Pts/1000  
Marketa Vondrousova     6.3%     58.7%            5.4  
(Aryna 2024 Rome/RG)    4.1%     61.9%            4.9  
Yulia Putintseva        8.6%     55.1%            4.4  
Sofia Kenin             4.1%     57.4%            3.0  
Dominika Cibulkova      2.5%     61.4%            2.9  
Kiki Bertens            4.1%     56.1%            2.5  
Bianca Andreescu        3.2%     58.1%            2.5  
Sara Sorribes Tormo     2.3%     60.4%            2.4  
Petra Martic            5.6%     54.2%            2.3  
Aliaksandra Sasnovich   3.3%     56.6%            2.2  
Qinwen Zheng            2.0%     60.7%            2.1  
Su Wei Hsieh            4.5%     54.5%            2.0  
Karolina Muchova        4.2%     54.8%            2.0  
...                                                   
(Aryna 2024 2nd half)   1.9%     55.6%            1.1  
Average                 2.2%     52.6%            0.6  
(Aryna 2017-Apr '24)    1.1%     53.2%            0.4  
...                                                    
Elise Mertens           1.9%     46.1%           -0.7  
Sloane Stephens         1.1%     42.2%           -0.8  
Amanda Anisimova        2.0%     45.8%           -0.9  
Kristina Mladenovic     5.2%     47.1%           -1.5  
Laura Siegemund         7.6%     47.7%           -1.7  
Ons Jabeur              8.2%     47.3%           -2.2

Clay may be particularly drop-shot friendly, but still, how about clay-Aryna!

At the other end of the spectrum… is Jabeur actually bad at drop shots? We need more context before we could establish any such conclusion. Perhaps the Tunisian hits droppers at particularly desperate times. Still, it’s jarring to see the star’s name at the bottom of the list.

Did someone say context?

The most common situation for a Sabalenka drop shot is when she makes a first serve and the ball comes back to her backhand. Over her entire career, when she hits a dropper with her second shot, she wins 51.1% of points. If she doesn’t go for the drop, she wins 51.8%.

Without camera-tracking data, that (and the dozen-plus analogous categories) is as far as we can drill down. Maybe the returns to the backhand that she dropshots are different from the ones she doesn’t. Match Charting Project data can’t tell us that.

Adjusting for context remains valuable even with those limitations. We can classify each drop shot by whether the player who hit it was the server or returner, whether it was a first or second serve point, whether it was a forehand or backhand-side drop shot, and how far into the rally it occurred. When Aryna waits one more shot on a first-serve point, her drop is much deadlier. Instead of the 47% of points she wins on a third shot from her backhand side with something other than a drop shot, she wins 55%.

The list looks quite a bit different when we take these additional factors into consideration. I tallied each player’s results in each of those categories, so we can compare their drop shot winning percentages with how they fared in the same mix of situations. “DSWOE” is Drop Shot Wins Over Expectation, the ratio between the two numbers:

Player               Drop W%  Exp W%  DSWOE  
Dominika Cibulkova     63.5%   50.1%   1.27  
Petra Martic           54.2%   42.9%   1.26  
Sara Sorribes Tormo    60.4%   47.9%   1.26  
Martina Trevisan       59.5%   48.7%   1.22  
Marketa Vondrousova    58.7%   48.1%   1.22  
Danka Kovinic          56.0%   46.1%   1.21  
Sorana Cirstea         56.8%   46.8%   1.21  
Kaja Juvan             58.5%   48.4%   1.21  
Ashleigh Barty         59.1%   49.3%   1.20  
Kiki Bertens           56.2%   47.2%   1.19
...  
Average                51.3%   49.2%   1.04
...  
Ons Jabeur             47.3%   47.8%   0.99  
Agnieszka Radwanska    48.9%   49.9%   0.98  
Maria Sakkari          48.6%   49.9%   0.97  
Jelena Ostapenko       49.7%   52.9%   0.94  
Caroline Wozniacki     50.0%   53.3%   0.94  
Elise Mertens          46.1%   50.2%   0.92  
Serena Williams        45.5%   49.8%   0.91  
Amanda Anisimova       45.8%   50.4%   0.91  
Sloane Stephens        44.1%   48.8%   0.90  
Iga Swiatek            49.6%   56.2%   0.88

(The winning percentages here are very slightly different from the ones above because some of the data wasn’t detailed enough to be used for this calculation.)

The average rate of 1.04 seems plausible. Players generally know what they’re doing; they wouldn’t hit drop shots if they didn’t have reason to think it would improve their odds. Jabeur does indeed look better in context. She still finds herself in the bottom ten, but a DSWOE of 0.99 means that if she is costing herself anything with all the droppers, it isn’t much. It’s possible that even this more granular approach is missing some details that would explain why Ons makes the decisions she does.

I must also acknowledge the oddity of finding Swiatek at the bottom of the list–or any list. Her 49.6% drop shot win rate isn’t that bad: It’s what she does the rest of the time that is such an outlier. She isn’t known for her drop shot, and she doesn’t hit many. So as with Jabeur, it’s possible that these categories don’t capture how hopeless the situations are when she tries to drag her opponent up to the net.

This metric confirms our story about Sabalenka. Her drop shots were fine–if rare–before May, became devilishly effective on the clay, then settled back to a more modest level on faster surfaces:

Player       Drop W%  Exp W%  DSWOE  
2017-April     53.3%   51.2%   1.04  
May            61.9%   51.4%   1.20  
Second Half    55.6%   52.4%   1.06

Buried in the details of Aryna’s respectable 1.06 ratio since June is a particularly encouraging trend. Remember those plus-one backhands that she shouldn’t have been dropshotting? Since June, she basically stopped. Out of 108 total drop shots, those have represented only five.

Drop and roll

For someone who hits as hard as Sabalenka does, throwing in a drop shot can be about more than just winning a point. Once an opponent realizes that they might have to chase down a dropper, they are that much less focused on defending against deep groundstrokes.

That’s the idea, anyway. When I wrote about drop shots in the men’s game, I was surprised to discover that drop shots didn’t influence the outcome of subsequent points in the way I expected. The majority of drop shots are hit by servers, but after they hit one, servers are less likely to win points later in the same game. If there is any discernable pattern in the ATP data, it is that once a drop shot is played–whichever player makes the move–the returner has an edge for the rest of the game. This probably isn’t a causal relationship: Perhaps drop shots are more likely to come into play when the server is struggling to control the action.

The data for women’s tennis tells a different story. On the point after a drop shot–win or lose!–the drop-shotting player wins 51.1% of the time. Two points later, there’s still an advantage, and the edge stays in place for the remainder of the game:

Situation          Win%  
Next point        51.1%  
Two points later  50.7%  
Same game         50.7%  
All others        49.9%

That advantage is not the same for every player. The following list shows the point winning percentages for players who get the biggest post-drop-shot bang for the buck, along with those who–like servers in the men’s game–see their post-drop fortunes dip.

Player                Same game  All others   Diff  
Jasmine Paolini           56.5%       50.4%   6.2%  
Marta Kostyuk             55.9%       50.1%   5.8%  
Sloane Stephens           55.0%       49.9%   5.1%  
Beatriz Haddad Maia       53.0%       48.7%   4.3%  
Qinwen Zheng              54.5%       50.7%   3.8%  
Naomi Osaka               54.5%       50.8%   3.7%  
Anastasija Sevastova      53.3%       49.7%   3.7%  
Maria Sakkari             53.1%       49.7%   3.3%  
Angelique Kerber          53.8%       50.5%   3.3%  
Su Wei Hsieh              50.9%       47.9%   3.1%  
Karolina Pliskova         54.0%       51.0%   3.1%  
Danielle Collins          53.7%       50.7%   2.9%  
Marketa Vondrousova       52.8%       50.0%   2.8%  
Agnieszka Radwanska       54.0%       51.4%   2.5%  
Garbine Muguruza          53.4%       50.9%   2.5%  
Aryna Sabalenka           55.0%       52.5%   2.5%  
…                                                   
Average                   50.7%       49.9%   0.7%  
…                                                   
Ons Jabeur                50.2%       50.3%   0.0%  
…                                                   
Emma Raducanu             49.6%       51.1%  -1.5%  
Ashleigh Barty            51.5%       53.0%  -1.5%  
Eugenie Bouchard          48.9%       50.6%  -1.7%  
Svetlana Kuznetsova       47.8%       49.8%  -2.0%  
Karolina Muchova          48.6%       50.7%  -2.1%  
Monica Niculescu          46.9%       49.1%  -2.2%  
Barbora Krejcikova        47.4%       50.1%  -2.7%  
Jessica Pegula            47.6%       50.6%  -2.9%  
Lesia Tsurenko            44.5%       47.5%  -3.0%  
Caroline Garcia           44.9%       49.6%  -4.7%

Jasmine Paolini! It’s tough to pinpoint exactly what she does that has caused her improvement in 2024. Her post-drop-shot success rate is too niche a skill to account for much of it, but it’s fascinating to consider.

I added Jabeur to this list because she illustrates one of the factors that makes analyzing drop shots so complicated. As noted, the theory is that once a player hits a drop, her opponent has to start thinking about it. But against Jabeur, opponents have to think about it from the moment they step on court! One more drop shot from the wizard isn’t going to change that.

That’s just one reason why the relationships between frequency, success rate, and post-drop-shot success rate are unpredictable. Some players, like Stephens and Osaka, play droppers rarely. They don’t win much when they do. But the after-effect might make up for it. At the other end, Muchova has a great drop shot that she deploys often, and for whatever reason, her results on subsequent points suffer.

Back to Sabalenka one last time. I snuck her into the table above because, even before she hit lots of drop shots, she saw a post-drop boost. You will not be surprised to learn that those numbers have gotten better in the last six months:

Span            Same game  All others  Diff  
2017 - Apr '24      54.3%       52.3%  1.9%  
2024 Rome/RG        60.2%       53.7%  6.5%  
2024 2nd half       58.9%       54.2%  4.8%

Clay-Sabalenka got the best of both worlds. She won more points by playing the drop, and she won more points because of the tactic’s lingering effect. Perhaps because of her growing reputation as a drop shot queen, the effect has persisted since June, even when she doesn’t go to the well so often.

The Aryna Sabalenka path to drop shot success won’t help everybody. But no matter how we slice up the numbers, it sure has worked for her.

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Does Mpetshi Perricard’s Backhand Even Matter?

Giovanni Mpetshi Perricard in Basel, playing a longer rally than usual.
Credit: Skyscraper2010

The story of last week’s tournament in Basel was the blistering service performance of Giovanni Mpetshi Perricard. The six-foot, eight-inch Frenchman racked up 109 aces in five matches, including more than one-third of his service points in Sunday’s final against Ben Shelton.

Mpetshi Perricard is a big server straight out of central casting. He can nail the corners at 150 miles per hour; on Sunday he hit one second serve at 146. He puts plenty of mustard on his groundstrokes as well. He often plays a high-risk brand of baseline tennis, recognizing that with a serve like his, he only needs to break once or twice–or just pick off a couple of return points in the tiebreak.

The Frenchman’s rapid rise through the ranks also fits his style. For a big server, wins can come in batches, when conditions–or, simply, tiebreak luck–are on his side. After an unexpected breakthrough on clay in Lyon, Mpetshi Perricard upset Sebastian Korda (in four tiebreaks!) and reached the second week at Wimbledon. Basel played faster than any tour event this year, and he took advantage. In between, he suffered through a 1-7 stretch in which he lost five straight tiebreaks and saw his double-fault rate balloon into double digits.

Much of Mpetshi Perricard’s future success will depend on his ability to handle these ups and downs. So far, he has struggled a bit to avoid the bad patches that spell doom for one-dimensional players. In his limited tour-level action, he has won more service points (70.2%) than anyone except Jannik Sinner. Yet five men hold more reliably than the Frenchman does, even after an unbroken week in Basel. The successes of Milos Raonic and John Isner–and even Shelton last year–come from playing better than usual under pressure, something Mpetshi Perricard has yet to consistently demonstrate.

I do love talking about servebots serving service aces. But while everybody raves about the GMP serve, I keep thinking about the backhand.

On the one hand

Mpetshi Perricard is now the fourth-highest ranked man with a one-handed backhand. His shot is nothing like the graceful, big-backswing, Federer- and Gasquet-inspired strokes of Grigor Dimitrov and Lorenzo Musetti. He often does little more than set up the racket to block the ball back. Strong as he is, the resulting flat shot can be much more than a mere defensive maneuver.

A few generations ago, it was standard to see big servers with one-handers. Think Richard Krajicek or Greg Rusedski; you might even put Pete Sampras in that category. More recently, Ivo Karlovic sported a one-handed backhand, though he mostly hit slices. Christopher Eubanks fits a broadly similar mold. Now, though, one-handers are dying breed, with just nine representatives in the top 100 of the ATP rankings.

Unlike Musetti or Stefanos Tsitsipas, Mpetshi Perricard isn’t likely to inspire the next generation of one-handed stars. No one is going to call this guy a throwback. On a good serving day, the Frenchman’s highlight reel features barely any groundstrokes at all.

What, then, do the numbers say? Is the Mpetshi Perricard backhand any good? Would he be better off with a two-hander like Raonic’s, Isner’s, or Reilly Opelka’s? Or, to return to the question I started with: For someone who specializes in ending rallies before they begin, does his backhand even matter?

Safely hidden

When the Frenchman’s game plan is working, his backhand is tucked away, out of sight. No backhands are necessary when the serve doesn’t come back, and when he controls the point, he prefers the forehand. Setting aside service returns, few players avoid their backhands as scrupulously as Mpetshi Perricard does.

The average ATPer hits 44% of their groundstrokes from the backhand side. Here are the most backhand-shy men with at least 15 matches in the Match Charting Project database, along with some other big servers of note:

Player                      BH/GS  
Ivo Karlovic                30.1%  
Jack Draper                 32.5%  
Ryan Harrison               35.2%  
Thiago Monteiro             35.5%  
Giovanni Mpetshi Perricard  35.5%  
Jaume Munar                 36.1%  
Vasek Pospisil              36.4%  
Alejandro Tabilo            37.1%  
Alexei Popyrin              37.3%  
Guido Pella                 37.4%  
Ben Shelton                 37.6%  
Maxime Cressy               37.9%  
…                                  
Christopher Eubanks         38.9%  
Matteo Berrettini           41.1%  
Milos Raonic                42.9%  
-- Average                  44.0%  
John Isner                  44.3%  
Reilly Opelka               45.6%  
Greg Rusedski               46.2%  
Nick Kyrgios                46.8%  
Pete Sampras                47.7%  
Richard Krajicek            48.3%  
Goran Ivanisevic            51.1%  
Mark Philippoussis          52.1%

Backhands per groundstroke is not the easiest stat to parse, because it is the product of so many different factors. Nearly everyone would like to keep their number low, so it’s partly a function of footwork and anticipation. (And sheer willingness to hit forehands from outlandish positions.) But it is also influenced by opponents, who will work more or less hard to find the backhand. Mpetshi Perricard’s place on this list, then, could be telling us various things. He hits his forehand when he can, and his movement is good enough to make it happen. Opponents might not be trying as hard as they could to force a backhand.

Yet another factor is how comfortable the player is with their slice. GMP hits his quite a bit, meaning that he unleashes the flat one-hander that much more rarely. The typical tour player hits their flat or top-spin backhand on 35% of groundstrokes. The Frenchman comes in at 25%, not as often as his most extreme peers, but in line with other big servers:

Player                      not-slice-BH/GS  
Ivo Karlovic                           6.1%  
Daniel Evans                          11.6%  
Milos Raonic                          20.2%  
Maxime Cressy                         20.4%  
Matteo Berrettini                     21.3%  
Grigor Dimitrov                       22.7%  
Corentin Moutet                       23.3%  
Christopher Eubanks                   23.6%  
Giovanni Mpetshi Perricard            25.2%  
Alexei Popyrin                        26.3%  
...
Bernard Tomic                         27.9%  
John Isner                            28.0%  
Ben Shelton                           28.5%  
Reilly Opelka                         31.5%  
-- Average                            34.7%

All of this is to say: Mpetshi Perricard hardly leans on the flat backhand. His serve keeps point short, and his preferences are for other shots. In the 138 points of the Basel final, he hit only 28 flat backhands, six of them on service returns.

Backhand impact

When the Frenchman is forced to hit a backhand (or chooses to–anything’s possible, I guess), the results aren’t great. When he goes for the flat backhand, he wins 43% of points, compared to a tour average of 49%. He takes more risks than his peers, but not overwhelmingly so: 9% of his one-handers end in a winner or forced error, while 12% are unforced errors. (Tour norms are 8% and 9%, respectively.)

These outcomes aren’t as extreme as his preferences. Of about 200 players with as many non-slice backhands in the MCP database, Mpetshi Perricard’s 43% comes in 21st from the bottom. Compared to other big servers, that win rate is positively respectable:

Player                      W/FE%   UFE%  inPointsWon%  
John Isner                   6.9%  12.8%         35.8%  
Milos Raonic                 7.3%  12.5%         40.4%  
Matteo Berrettini            4.8%  10.4%         42.5%  
Andy Roddick                 5.5%   7.8%         42.6%  
Felix Auger-Aliassime        6.0%   9.9%         43.4%  
Giovanni Mpetshi Perricard   8.9%  12.6%         43.5%  
Ben Shelton                  6.2%  11.1%         43.8%  
Nick Kyrgios                 7.9%  10.7%         43.9%  
Kevin Anderson               7.6%  11.0%         44.1%  
Hubert Hurkacz               6.2%  10.0%         45.6%  
-- Average                   7.3%   9.0%         48.6%  
Jack Draper                  6.5%   5.7%         49.1%

Against this group, the Frenchman’s winner (and forced error) rate really stands out. Given the outcomes when he doesn’t go for it, it’s possible he should be even more aggressive than he already is. Master tactician Milos Raonic took a similar tack, piling up as many unforced errors as GMP does, but without quite as many winners.

The picture is less rosy when we look at slice backhands. As noted, Mpetshi Perricard hits a lot of them–close to one-third of his groundstrokes from that wing. When he does, he wins 33% of points, compared to 42% for his peers. Only a handful of players have posted such low slice-backhand win rates, and they are mostly the names you would expect:

Player                      W/FE%   UFE%  inPointsWon%  
John Isner                   1.5%  11.1%         27.3%  
Christopher Eubanks          1.6%  10.7%         30.2%  
Kevin Anderson               3.2%   6.5%         31.4%  
Nicolas Jarry                4.0%  13.2%         32.7%  
Ivo Karlovic                 3.5%  12.0%         32.8%  
Giovanni Mpetshi Perricard   3.1%   3.9%         33.1%  
Ben Shelton                  2.0%   7.1%         33.3%  
...
Nick Kyrgios                 4.2%   6.1%         35.6%  
Felix Auger-Aliassime        3.6%   8.2%         38.1%  
Hubert Hurkacz               2.7%   3.9%         38.1%  
Milos Raonic                 4.7%   9.4%         40.3%  
Matteo Berrettini            2.8%   9.0%         41.5%  
-- Average                   3.3%   5.4%         41.6%

The Frenchman doesn’t miss much. Why just keep the ball in play, though, if you’re likely to lose the point anyway? By hitting so many slices, Mpetshi Perricard makes his flat-backhand numbers look better, but he probably doesn’t pick up any points by making the trade. Prolonging the point is a good strategy if you’re Casper Ruud–or, really, about 80% of the guys on tour. But if you play like GMP, it’s better to go big.

This is one way in which the one-hander may cost him. The two-handed backhand is particularly valuable in its ability to block overpowering shots without retreating to a fully defensive mode. While players with one-handers try to achieve the same thing with a slice, the stats tell us that it’s a poor imitation. The Frenchman’s in particular isn’t doing him any favors.

So, does it even matter?

Mpetshi Perricard doesn’t hit that many backhands, and he isn’t that much worse than average when he does. But, the margins in tennis are small, and the margins for big servers are smaller still. In 26 tour-level matches this year through the Basel final, GMP won exactly 50% of his points. (Not 50.1%, not 49.9%–50% on the dot.) Five players in the top 20 win 50.8% or less. That’s how close the Frenchman is to an even bigger breakthrough.

My backhand potency (BHP) stat quantifies the impact that each player’s (non-slice) backhands have on their broader results. The stat measures how often a shot ends the point in either direction, as well as what happens on the shot after that. Based on the matches we’ve charted this year, GMP’s BHP per 100 backhands stands at -4.3, one of the lower numbers on tour for players with at least 10 charted matches from the last 52 weeks:

Player                      BHP/100  
Nicolas Jarry                  -6.9  
Felix Auger Aliassime          -4.6  
Tallon Griekspoor              -4.6  
Flavio Cobolli                 -4.3  
Giovanni Mpetshi Perricard     -4.3  
Alexei Popyrin                 -4.2  
Dominic Thiem                  -4.1  
Botic Van De Zandschulp        -3.5  
Matteo Berrettini              -3.1  
Ben Shelton                    -2.4  
Stefanos Tsitsipas             -2.4

What does this mean for the bottom line? -4.3 BHP is equivalent to about -3 points per 100 backhands. Since he doesn’t hit many backhands, that’s about -1.1 per 100 points.

My best estimate, then, is that if we magically replaced the Frenchman’s backhand with a neutral one–say, that of Arthur Fils–he’d pick up 1.1 more points per 100. Instead of winning 50% of points at tour level, he’d win 51.1%. That isn’t good enough to crack the top 10, but it would probably get him into the top 20.

Quantifying the impact of slices is tougher, because the more conservative shot is less likely to end the point immediately, or even on the next shot. If we figure that Mpetshi Perricard’s slice is roughly the same distance below average as his flat backhand, that’s another 0.5 or 0.6 points per 100 he could gain by acquiring a tour-average shot. Daniil Medvedev has hung in the top five in the ATP rankings while winning 51.9% of points. Stringing all of these assumptions together, we can start to see how a capably-backhanded GMP could reach that level.

The bad news for the Frenchman is that climbing the ranks is hard. Mpetshi Perricard is the worst returner in the top 50, and it isn’t even close. He breaks in about 10% of his return games; no one else is below 14%. Earlier this year, I wrote about the similar challenges facing Ben Shelton: Historically, a lot of players have arrived on tour with big serves, huge potential, and tons of hype. Few of them have been able to shore up their weak points enough to crack the top ten, let alone achieve greater feats.

The good news: There is so much room for improvement. Even without polishing the strokes themselves, it’s possible that a more aggressive set of tactics could win him a few more points on return. In yesterday’s loss to Karen Khachanov, the Frenchman won the first set despite picking off just two of 37 return points. One-dimensional servebot or not, he can learn to do better than that.

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With Tommy Paul, Get Ready To Backhand

The Tommy Paul backhand

On Sunday, Tommy Paul won the Stockholm final with one well-executed tactic. He hammered the Grigor Dimitrov backhand, shot after shot, point after point. Paul hit 71% of his backhands cross-court, far above the tour average of 50%. He also aimed his forehands at Dimitrov’s weaker side, going inside-out with 38% of his forehands, compared to the typical clip of 24%.

The results: 6-4 6-3 to the American, and a paltry seven rally winners for his opponent. Dimitrov was forced to hit backhands for 58% of his non-return groundstrokes, compared to his usual hard-court rate of 43%.

Paul doesn’t have any overwhelming weapons of his own, so he wins matches–42 of them already this year–by neutralizing opponents. In the case of Sunday’s final, that meant putting pressure on a backhand that is more flashy than effective. Dimitrov’s signature one-hander is not the worst on tour, but it is not much of an asset. His career backhand potency (BHP) is negative, meaning it costs him more points than it gains. Paul’s elite movement allowed him to exploit a weakness that the Bulgarian can usually hide.

Grigor isn’t the only man on tour with a preference for the forehand. Even players with top-tier backhands will often opt for a forehand because of the angles it opens up. Paul’s ability to pepper the backhand, then, is often on display. Facing Jannik Sinner at the US Open, the American hit 60% of his backhands cross-court–good enough to push the world number one to two tiebreaks. At Indian Wells against Casper Ruud, he hit 61% of his backhands cross-court. That proved successful enough to secure his first top-ten win of the season.

Few pros play like this. Or more accurately: Few men are able to play like this. The Match Charting Project has at least 20 hard-court righty-versus-righty matches for almost 100 different men. Here are the top 15, ranked by how often they hit backhands cross-court.

Player                 BH XC%  
Lleyton Hewitt          70.0%  
Andre Agassi            65.9%  
Marat Safin             62.8%  
Yevgeny Kafelnikov      62.8%  
Richard Gasquet         59.8%  
Daniil Medvedev         59.4%  
Jenson Brooksby         59.3%  
James Blake             59.0%  
Kei Nishikori           58.7%  
Pete Sampras            58.6%  
Tommy Paul              58.6%  
Borna Coric             58.1%  
David Ferrer            58.0%  
Juan Martin del Potro   58.0%  
David Nalbandian        57.9%

That’s pretty good company. The active players highest on the list–Medvedev and Gasquet–are known for camping out far behind the baseline, giving them extra time to choose their shot. Paul and Nishikori (and the category-busting Brooksby) act faster. They rely on anticipation, footwork, and racket control to direct the ball where their opponent doesn’t want it to go.

Here’s a similar list–again, out of 100 or so players–ranked by inside-out forehand frequency. Same goal, different shot:

Player                 FH IO%  
Milos Raonic            39.5%  
Jack Sock               38.4%  
John Isner              38.1%  
Jim Courier             37.9%  
Reilly Opelka           33.3%  
Robin Haase             33.1%  
Andrey Rublev           33.0%  
Holger Rune             32.5%  
Daniel Evans            32.3%  
David Ferrer            32.3%  
Marin Cilic             31.8%  
Felix Auger-Aliassime   31.7%  
Thanasi Kokkinakis      31.6%  
Fabio Fognini           31.3%  
Kevin Anderson          31.1%  
Jo-Wilfried Tsonga      30.6%  
James Blake             30.1%  
Roberto Bautista Agut   30.0%  
Matteo Berrettini       29.9%  
Tommy Paul              29.7%

Many of these men make the list because they prey on weak service returns, or because they play high-risk shots when running around their backhands. Despite standing outside those categories, Paul ranks high on this metric as well. There’s very little overlap between the two lists: Only James Blake ranks above Tommy on both.

In short: Everybody (usually) wants to hit to the backhand, but few men are able to do so as often as Tommy Paul.

When tactics fail

Stockholm trophy in tow, Paul took his winning streak to Vienna. He began his campaign yesterday against compatriot Brandon Nakashima. Nakashima has become a thorn in Paul’s side, with three previous tour-level wins on three different surfaces. Tommy’s only victory came at a Challenger in 2019, when Nakashima was and 18-year-old ranked 942nd in the world.

Nothing changed this week. Nakashima secured a 6-4, 6-4 victory and improved his record against the older man to 4-1. Paul unleashed the same tactical plan that he used to beat Dimitrov, and he discovered–not for the first time–that it isn’t so effective against a sturdier backhand.

Paul hit nearly as many backhands cross-court as he did in the Stockholm final. But unlike Dimitrov, Nakashima was able to go toe-to-toe from that corner. Dimitrov went to the slice nearly half the time–opening up, incidentally, many of the opportunities Paul seized to hit inside-out forehands. Nakashima hit the slice barely half as often. 12% of Dimitrov’s topspin backhands became unforced errors; only 5% of Nakashima’s did.

Nakashima took the tournament’s (unfortunately phrased) advice.

We can’t explain the entire result based on Paul’s tactical preference. He looked sluggish throughout, coughing up 31 unforced errors compared with just 20 in the Stockholm final. But causation can run multiple directions: Nakashima didn’t allow him to play the clean, logical game that earned him the trophy in Sweden. The veteran scuffled to find another solution.

Another of Tommy’s worst matchups has a similar profile. He is 0-5 against Alex de Minaur, whose backhand also rarely lets him down. Both times they met in 2023, Paul hit his backhand cross-court more than 62% of the time. In Acapulco, the American hit his forehand inside-out more than 40% of the time, the highest mark we have for him in the Match Charting Project database. De Minaur doesn’t blow him off the court, so Paul can hit the shots he wants. Those shots–regardless of the Aussie’s own traits–are aimed at the backhand corner.

But against a player like Nakashima or de Minaur, the tactic doesn’t work. Lots of inside-out forehands are a safe bet against a player like Dimitrov, but de Minaur’s defense is too good. In Acapulco, Paul won only half of those inside-out forehands, well below tour average. The American generally played the way he wanted to, forcing de Minaur to hit a whopping 66% of his rally groundstrokes from the backhand side in their Los Cabos meeting. But the Aussie didn’t mind. At least in those matches, Paul showed little sign of a plan B.

Another dilemma for Tommy arises when someone takes away his plan A. The only other player who has defeated him five times is Andrey Rublev, hardly a man you’d select to run a backhand clinic. We don’t yet have any charted matches from this head-to-head, but it’s easy to speculate what goes wrong for Paul. In order to hit a disproportionate number of shots to a particular location, you need to have some control over the proceedings. Rublev, with his devastating forehand and aggressive mindset, is one of the few players on tour who can outslug the American’s speed.

The American’s losses are a good illustration of just how hard it is to excel at the highest levels of professional tennis. He is perhaps as good as anyone in the game at taking and keeping control of rallies from the baseline. But even that world-class skill can be nullified by a howitzer forehand or a backhand like a brick wall. Paul has twice upset Carlos Alcaraz, but when handed a first-round opponent with a solid backhand, as he was yesterday in Vienna, he sometimes finds that his best isn’t good enough.

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Matteo Berrettini and the Pursuit of Expected Value

Matteo Berrettini hitting a forehand that will probably end the point

A few weeks ago, Agustin Lebron made a broad claim:

Most strategic improvements in sports have been in the direction of increasing variance and living with the (better EV) results:
Baseball: more extra base hits, no more bunting.
Football: more passing game, going for it on 4th.
Golf: driver ball speed increases.
Bball: 3 pointer
Tennis: bigger serves/groundstrokes.
Snooker: cannoning the pack to extend breaks.
Chess: sub-optimal but niche exploitive lines.

“EV” means expected value or, roughly speaking, probability of success. Thanks to baseball’s sabermetric revolution and its influence on other sports, we better understand how players and teams win. Competitors, knowingly or not, are chasing EV.

Lebron’s claim is a bit more specific, that players and coaches across sports are playing riskier games because the ultimate payoff is greater. In baseball, a sacrifice bunt makes it more likely that a team scores one run, but less likely that the team piles on multiple runs. Hoopsters land two-point shots at a better rate than three-pointers, but the additional point makes the tradeoff worthwhile. Ice hockey coaches pull the goalie sooner than they used to, taking the chance that an extra skater will result in a game-tying goal, even if the decision could result in an easy score for the opposition.

Many more examples and counter-examples appear in the discussion around Lebron’s tweet and in the comments at Marginal Revolution.

It’s less clear that tennis ought to be grouped with these other sports. It may be true that players have uniformly bigger serves, or that they hit forehands harder than their predecessors. But is their pursuit of expected value causing them to take more risks?

Serve trends

Since 1991, when the ATP started recording stats like aces and double faults, aces have indeed gone up. That first year, about 5% of points ended with an untouched serve. The tour reached 7% by 2000, then cleared 8% in 2014. The rate has held fairly steady since then, sitting at 7.7% in 2024.

One way to hit more aces is to push closer to the edge. Aim for the lines, smack it as hard as you can, and accept that you’ll miss more, too. That would fit nicely with the increasing-variance hypothesis. But that’s not what has happened. As aces have gone up, the percent of first serves made has also risen:

The increasing-variance hypothesis holds for 1991-2000: Aces went up at the cost of fewer first serves in the box. Since then, though, players have kept hitting more aces (if only slightly), while landing even more first serves.

This is almost definitely thanks to better racket and string technology. You can swing harder than ever, with more spin than ever, and keep control of the ball. But that isn’t the whole story. For any given level of technology, players could take more risks, cracking still more aces at the expense of fewer first serves in. For nearly a quarter-century, that is not the decision pro men have made.

Second serves and double faults tell the same story:

Second serves offer an opportunity to take even more risks. If you go big and miss, you lose the point. But men have generally opted to take their chances with a ball in play. Double faults have cratered since the mid-90s and are currently at an all-time low. Yet players are winning about as many second serve points as ever.

In the last decade, we’ve seen a few players–Nick Kyrgios and Alexander Bublik come to mind–who do sometimes take their chances with a big second serve. Across 129 charted matches, Kyrgios hits aces on 4% of his second serves. Tour average is below 1%. Even Nick, though, doesn’t think it’s worth a major change in his risk profile. His career double fault rate is 4.2%: above average, but hardly an outlier among tour regulars.

The Aussie recognizes that the second serve evolved for a reason. Hitting a big second serve–deploying, in other words, two first serves–is a negative-EV play. It may be worth trotting out for variety’s sake, but not more than that.

Which brings us, finally, to Matteo Berrettini. The six-foot, five-inch Italian is the apotheosis of the big-serve, big-forehand, “plus-one” game. He’s the sort of player Lebron might have been thinking of when he bucketed tennis with the other sports on the list.

For all his power from the line, Berrettini is as conservative as they come. His career ace rate of 12.3% is outstanding, yet there is no apparent cost. He makes almost 64% of his first serves. He wins more second serve points than average, too, despite a miniscule double-fault rate of 2.4%. His game has gotten even safer as he reaches his late 20s. This year, he is hitting slightly more aces (12.8%) and landing far more first serves (68.6%) and committing fewer double faults (2.0%).

If the Italian is any indication, tennis is moving toward bigger serves and forehands. Yet when it comes to the serve, variance is headed in the opposite direction.

Rally aggression

What about groundstrokes? Nearly everyone these days talks about plus-one tennis. The serve–when it doesn’t end the point outright–generates opportunities to put the ball away. When those opportunities appear, don’t screw around! The strategy looks different in the hands of Berrettini than it does with, say, Jelena Ostapenko, but more than ever, players think in terms of recognizing and converting opportunities to end points.

Once the serve has landed, some players have indeed adopted a higher-variance approach that is probably unprecedented. Ostapenko, the freest swinger of all, ends nearly two-thirds of points on her own racket. Inevitably, she misses a huge fraction of those. Her Rally Aggression score of 182 (on a scale designed to run from -100 to 100) leads active players, and it massively outstrips anyone who started their career before about 2005.

Here, alas, we are hamstrung by data limitations. I discussed the men’s tour above because women’s ace and double-fault data only goes back to 2010 or so. The situation is even worse with groundstrokes. While the Match Charting Project now spans over 14,000 matches, relatively few of those predate 2010. Those “early” matches are heavily skewed toward a handful of top players.

We can still draw some comparisons. Lindsay Davenport and Maria Sharapova, often-erratic free swingers a generation or two before Ostapenko, grade out with Rally Aggression scores in the mid-40s. That’s below Iga Swiatek. Let that sink in for a moment. Today’s rock-solid, heavy-topspinning queen of clay plays as aggressively as two earlier-era emblems of high-risk slugging.

Again, we see the effect of better tech. When Ostapenko swings away, there is perhaps a 60% chance it lands in. If it does, it probably isn’t coming back. When Davenport (or to a greater extent, her own predecessors) took a big cut with a 60/40 chance of falling between the lines, it wasn’t quite as hard, and it didn’t have as much spin. It was that much less likely to end the point immediately, or in her favor at all. The chance of an error was always high; modern rackets and strings have upped the odds that the risk is worth taking.

Berrettini, though, once again illustrates that the risk isn’t necessary. The Italian’s Rally Aggression score is 24: above average but not by much. In part the number is low because he struggles to create opportunities on return (or when his serve fails to create chances), but in part he rates where he does because he doesn’t often miss. Roger Federer, for broadly similar reasons, is in the same range.

Modern tech allows players to hit as many winners as ever with less risk. Jannik Sinner, with his career Rally Aggression score of -24 and Carlos Alcaraz, at +8, point toward a lower-variance future, at least in the men’s game.

Ebbs and flows, serves and volleys

The biggest gap in the increasing-variance hypothesis is that it doesn’t explain the death of the serve-and-volley.

Few tactics in any sport are higher variance than old-school, rush-the-net-on-every-point serve-and-volleying. Think of Boris Becker at Wimbledon. He hit a bomb, and if it came back, he was often sprawled across the court simply trying to get a racket on the ball. Today’s net forays aren’t always so kinetic, but they remain high-risk. For every easy volley, there’s an untouchable passing-shot winner.

What’s more, the most dedicated form of serve-and-volleying, Jack Kramer’s “Big Game,” was explicitly an EV play, the brainchild of an actual engineer decades before anyone thought to put “sports” and “analytics” in the same sentence. Kramer and club-mate Cliff Roche worked out the angles and the probabilities, and the on-court results were so overwhelmingly positive that other Americans quickly followed suit. Thanks to a Davis Cup drubbing in 1946, Kramer’s game also changed the course of Australian tennis, inspiring Frank Sedgman and indirectly defining the style of innumerable hopefuls, including Rod Laver.

Serve-and-volleying, in the right hands, was the smart play for reasons that no longer persist. Returners couldn’t do much with a good serve. Court conditions made baseline tennis chancy: Much more tennis was played on grass, and almost none of that grass resembled the impeccable grounds at Wimbledon. Rushing the net was the only way to avoid losing on a bad bounce.

There’s a direct line running from Kramer, through Laver and Pete Sampras, to early-career Federer. Roger gave up serve-and-volleying only when Lleyton Hewitt showed how a sturdy, precise defense–made possible, again, by improved tech–could turn even a strong serve-and-volley attack into a negative-EV proposition.

The overarching theme here is that tennis pros will chase expected value, just as they have for a century. If they don’t, other players will come along with a better approach and displace them. The tactics that work in a given era are heavily driven by tech, and they may or may not move in the direction of higher variance.

The women’s game shows us the potential of high-risk tennis. So many top players go for broke that someone like Swiatek–an aggressive player by historical standards–looks conservative by comparison. Ostapenko-style slugging looks nothing like serve-and-volleying, but the philosophy is similar: Put the ball away before your opponent has the chance.

The men’s game, though, is becoming ever more precise. Sinner and Alcaraz don’t have low Rally Aggression scores because they play so passively. They just don’t miss very often. Berrettini is more aggressive, but only just. Few men hit serves harder or pepper the corners so persistently. Fewer still are so relentless in how they capitalize on a short ball. Yet he does that seemingly without cost. The Italian has plenty of limitations–injuries and a limited backhand, for starters–but they aren’t tactical. He and his colleagues have concluded that higher risks aren’t worth it, and they are probably right.

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Coco Gauff’s Big What-If

Coco Gauff at the 2022 US Open. Credit: All-Pro Reels

The best players are able to work around their weaknesses. Coco Gauff is so solid that she has overcome two: an unreliable forehand and a second serve that hands too many points to her opponents. On Wednesday in Wuhan, Gauff coughed up 5 double faults out of 19 second serves. Despite surrendering more than 10% of her serve points for the fifth consecutive match, she eased past Viktoriya Tomova. The Bulgarian managed just three games.

The forehand is a subject for another day. Lately, the serve has been a bigger concern, the one blot on an eight-match win streak (and counting) in China.

Start with season totals. Through last week’s Beijing final, Gauff has missed more than one in five of her second serves. The result: She has double-faulted 8.9% of her 2024 service points. No other woman in the WTA top 60 has double faulted so often.

The typical tour regular loses barely half so many points this way. Tour average is 5.1%. Fellow elites Iga Swiatek, Jessica Pegula, and Jasmine Paolini come in at 3% or lower; Emma Navarro just misses that mark at 3.1%. Even Aryna Sabalenka, with her recurring bouts of service shakiness and occasional risk-taking on the second serve, gives away only 4.5% of points.

Still, Coco rates as the fourth-best player in the world. She’ll be back to #3 on Monday, and she has a good chance of ending the season there. The rest of her game is so sturdy that she has piled up nearly 50 wins on the season despite committing 274 more double faults than Swiatek has.

This is uncharted territory. In the last 15 years–the extent of my serve stats for women’s tennis–only two players have hit double faults so often and still managed to finish in the top five. No one has cracked the top three:

DF Rate  Player             Year  Rank  
  10.4%  Aryna Sabalenka    2022     5  
   9.6%  Maria Sharapova    2011     4  
   8.9%  Coco Gauff         2024     ?  
   8.7%  Elena Dementieva   2009     5  
   8.4%  Maria Sharapova    2015     4  
   8.1%  Dinara Safina      2008     3  
   7.9%  Dinara Safina      2009     2  
   7.9%  Maria Sharapova    2014     2  
   7.9%  Karolina Pliskova  2021     4  
   7.6%  Victoria Azarenka  2013     2  
   7.6%  Aryna Sabalenka    2021     2  
   7.5%  Maria Sharapova    2013     4  
   7.3%  Maria Sharapova    2012     2  
   7.0%  Venus Williams     2010     5

The typical year-end number one double faults only 4.1% of the time. Victoria Azarenka’s 2012 season, at 6.8%, was the only such occasion over 6%. This isn’t exactly a law of physics, but if Gauff is to dislodge the two women atop her in the ranking table, she’ll probably need to make a substantial move in that direction.

What-ifs

It’s no easy task to fix a leaky serve. The good news for Coco is that it may be all she needs to do.

Back to the season totals. Gauff is basically tied with Swiatek as the best returner in the game. The American has won 48.4% of her return points this year, compared to Iga’s 48.5%. Gauff has played slightly weaker opposition, but in any case, it’s a minor gap. Both women stand well above the pack; no one else tops 47.5%. With no double faults working against her, Coco’s return game is worthy of a world number one.

By service points won–where the double faults come into play–Gauff ranks a more pedestrian 12th. That’s entirely because of the deliveries that miss. She wins more first-serve points than anyone except for Qinwen Zheng and Elena Rybakina. In an era without megastars, the combination of 1st or 2nd on return and 12th on serve might be good enough to lead the field, but with an all-rounder like Swiatek and a dominant slugger like Sabalenka to contend with, it doesn’t do the job.

Here, then, is the what-if. Wave a magic wand and proclaim that all of Gauff’s second serves find the box. The 9% of her service points that end in double faults turn into second serves in play: points that she wins at a 56% clip.

Do that, and her rate of serve points won–currently at 60.2%, good for 12th place–becomes 65.3%, better than anybody. A double-fault-free Coco Gauff would rack up more serve points than anyone on tour, while still winning almost as many return points as Iga does. A handful of key points might swing the year-end number one in either direction, but statistically, the American would be the best player in the world.

You might argue that even in the rosiest real-life scenario, Coco isn’t going to eliminate double faults entirely. Fair enough. Reduce her double fault rate to tour average, and she wins 62.5% of service points. Not as good as Swiatek, Sabalenka, or Rybakina (or, technically, Lulu Sun in her limited tour-level action), but ahead of everybody else.

Combine serve and return into total points won (TPW%), and we see how these wishful adjustments move Gauff clear of the field–or, at least, everyone except for Iga:

TPW%   Player                      
56.9%  Coco Gauff (no dfs)  
56.5%  Iga Swiatek                 
55.4%  Coco Gauff (avg dfs)  
54.3%  Coco Gauff (actual)  
54.3%  Aryna Sabalenka             
53.7%  Elena Rybakina              
53.1%  Karolina Muchova            
52.9%  Qinwen Zheng                
52.8%  Danielle Collins            
52.7%  Mirra Andreeva              
52.6%  Jessica Pegula              
52.3%  Victoria Azarenka           
52.3%  Maria Sakkari               
52.3%  Paula Badosa                
52.1%  Madison Keys                
52.0%  Jasmine Paolini

Actual-Coco is already near the top of the list. Take away all or half of her double faults, and at the very least she looks stronger than Sabalenka and Rybakina.

The specifics

This may seem a bit too abstract, especially since the total-points-won list has so many differences from the official ranking table. Greatness is not measured by points, but by titles, and some trophies count much more than others.

Remember that these points we’re changing took place in real–often close–matches. Reversing just a few of the double faults would have tipped the scales in Gauff’s direction. In the counterfactual, she probably didn’t lose 15 matches this year. She likely picked up more than two titles.

Take the most painful loss of the season: Coco’s fourth round defeat at the US Open. Against Emma Navarro, she committed a gut-wrenching 19 double faults. Despite that, she won 46.8% of total points. All else equal, had she landed those 19 second serves, Gauff would have almost exactly flipped the tally, winning 53.0% of points. Even with a tour-average double fault rate, she would have won 51.0% of points and–barring bad luck or a ill-timed choke–earned a victory.

Run the same exercise for the American’s other defeats this year, and we see just how strong her season could have been. If we reduce her double faults to a tour-average 5.1%, 4 of her 15 losses probably would have gone her way. Two more matches would have ended within a point of 50/50, safely in the range where a clutch (or lucky) break point or two can reverse the result.

Cut out double faults entirely, and Gauff wins at least 50.8% of points in six of the losses. She would have cleared 48% in four more, putting those in the range where luck could hand her the victory.

Even in the more conservative scenario, Gauff’s campaign looks quite different. Instead of losing to Anna Kalinskaya in the Dubai quarters, she would have faced off with Iga in the semi-finals. She wouldn’t have lost to Marta Kostyuk in Stuttgart: She’d have played Marketa Vondrousova for a place in the final. In Madrid, she would have handily beaten Madison Keys, earning a quarter-final date with Ons Jabeur. Flip the Navarro result in New York, and Coco could well have defended her US Open title.

Today’s action in Wuhan offered a glimpse of a sturdier future. Gauff cast aside Kostyuk with nary a double fault, advancing to the quarters in just 61 minutes. It was her quickest match since April–against an opponent who has bedeviled her in the past–and her first double-fault-free outing in 14 months.

The American has somehow established herself as a top-five player and grand slam champion despite handing her opponents more free points than any of her peers. A stingier Coco Gauff could soon be the best player in the world.

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Daniil Medvedev’s Instinct For Survival

Daniil Medvedev at the 2023 Italian Open

Clay-court tennis is known for its slow bounces, defensive court positions, and long rallies. Still, a whole lot of points are determined by the bang-bang, plus-one tactics that define the modern game.

The first week of this year’s European clay season was a wake-up call. The champions in Estoril, Houston, and Marrakech were Hubert Hurkacz, Ben Shelton, and Matteo Berrettini, hardly a trio of counterpunching grinders. In Estoril, 70% of Hubi’s serve points ended in four shots or less–and he won 83% of them. In Houston, three-quarters of Shelton’s ended so quickly, and runner-up Frances Tiafoe’s serve points were even shorter. Berrettini finished 77% of his serve points in four shots or less, winning 76% of them. In other words, the Italian won nearly 60% of his serve points with his serve and plus-one alone.

Tournaments since then have settled into something closer to the stereotype. Marton Fucsovics outlasted Mariano Navone in a Bucharest slugfest. The Munich final was decided between two big hitters, Taylor Fritz and Jan-Lennard Struff, but Struff secured the victory with far fewer short serve points than Berrettini and company.

Yet quick points have an outsized effect on clay-court outcomes. When Stefanos Tsitsipas beat Casper Ruud in Monte Carlo, he finished nearly 70% of his serve points in four shots or less–a Hurkaczian performance befitting a server of his caliber. A week later in Barcelona, the relevant number fell to 63%, not much better than tour average on the surface. Stef found himself exposed, fighting out more rallies against one of the game’s best baseliners. He was broken three times and lost in straights.

Fans tend to look at rally-length stats and focus on winning percentage. How did Jannik Sinner fare on points between 0 and 4 shots? Did Carlos Alcaraz win more than half of 10-plus-shot rallies? While these sliced-up winning percentages matter, you can often tell more about a match–including the likely victor–by looking at the frequency of point types. When Berrettini finishes so many of his serve points quickly, his game is working as intended, and he’s probably winning. If he’s spending more time in long rallies, his opponent has more chances to dictate play, hinting at the opposite outcome.

On clay, then, the battle is to survive, to drag the server into a rally. Nobody on tour does that better than Daniil Medvedev.

Octopus on dirt

In the typical men’s clay-court match, 61% of points end in four strokes or less. That’s based on Match Charting Project data since 2015, spanning over 200,000 clay-court points. Here’s how the returner fares in each type of rally:

              Frequency  Win %  
Short (0-4)       61.2%  33.1%  
Medium (5-9)      27.5%  35.3%  
Long (10+)        11.2%  55.8%

The longer the rally, the better the returner’s chances, even if the process is gradual. Five- and six-shot rallies still lean in the server’s direction, though not as much as shorter ones. Ten-plusses are effectively neutral. They look slightly returner-friendly because rallies of exactly ten shots are won by the returner, and that’s the most frequent length in the ten-plus bucket. (If we drew the line at nine or eleven, we’d have the opposite problem.)

Now check out Medvedev:

              Frequency  Win %  
Short (0-4)       52.5%  35.5%  
Medium (5-9)      30.3%  36.1%  
Long (10+)        17.2%  52.3%

The short- and medium-point winning percentages are a bit better, but the real story is in the frequency column. The average match has about 80 serve points for each player. In that time, Medvedev erases about seven short points and adds about five long ones.

In this sense, being a good returner isn’t about cracking return winners or wrong-footing the server. The goal is simply to stay alive. Get the return back, preferably placed well-enough to take away a high-percentage plus-one winner. In last year’s Rome final, Medvedev dragged Holger Rune into long service points almost exactly in line with his career averages: 54% short points, 31% mediums. Rune did just fine through those first nine shots. But when Medvedev reached the ten-shot mark–10 times in 67 Rune service points–he snatched away all but one. Two of those long points gave Medvedev a break for the first set; another 22-shot gutbuster secured the break when Rune failed to serve out the second set.

The Russian’s defense is even more impressive when we compare him to men with better clay-court pedigrees. Here are the top 20 players (minimum 500 charted clay-court return points since 2015) ranked by frequency of short return points:

Player                       Frequency  Win %  
Daniil Medvedev                  52.5%  35.5%  
Diego Schwartzman                53.5%  36.5%  
Rafael Nadal                     54.7%  39.5%  
Alex de Minaur                   54.9%  31.2%  
David Ferrer                     55.1%  34.6%  
Marton Fucsovics                 55.6%  41.8%  
Andy Murray                      55.6%  40.0%  
Novak Djokovic                   55.7%  36.4%  
Gael Monfils                     55.8%  34.7%  
Francisco Cerundolo              55.8%  38.6%  
Stefanos Tsitsipas               56.1%  31.8%  
Jannik Sinner                    56.9%  36.0%  
Jaume Munar                      57.0%  36.5%  
Hubert Hurkacz                   57.1%  30.3%  
Alexander Zverev                 57.5%  34.8%  
Alejandro Davidovich Fokina      58.3%  33.7%  
Sebastian Baez                   58.3%  36.3%  
Gilles Simon                     58.6%  35.9%  
Dominic Thiem                    58.6%  32.5%  
Guido Pella                      58.8%  35.1%

The entire list is packed in a range of about six percentage points, so the full point between Medvedev and Diego Schwartzman–not to mention the two-plus points between him and Rafael Nadal–illustrates just how much of an outlier he is. A low frequency isn’t necessarily better: I’d take Rafa’s combination of frequency and winning percentage over Medvedev, just as I’m sure you would have before reading the first word of this article. But while the Russian doesn’t pick off as many short return points as Nadal, Andy Murray, or Fucsovics(?), his conservatism is hardly a liability. He wins nearly as many as Schwartzman, Sinner, or Novak Djokovic. All this despite a game style tailored to neutralizing the rally further down the line.

The ten-point truth

Medvedev’s long-rally domination of Rune can be misleading. As we’ve seen, he wins about half of clay-court return points that reach ten strokes. Most players do. The benefit of generating long rallies isn’t to sweep the lot: Nobody comes close to accomplishing that, as we will see. The goal is to neutralize rallies. The average server wins 64% of clay-court points, so anything the returner can do to increase the number of 50/50 points is a good deal.

There may be a knock-on effect, as well. Wear out the server, and he might not have as much energy for the next delivery. He might also take more risks in an attempt to end the next points quickly.

The best baseliners don’t need a knock-on effect. Medvedev excels at creating long points, but other men are much better at securing those rallies for themselves. Here are the top 20 among players with at least 100 charted long return points:

Player                   Long Points  Win %  
Kei Nishikori                    141  69.5%  
David Ferrer                     129  67.4%  
Nicolas Jarry                    126  65.1%  
Rafael Nadal                     863  62.9%  
Gilles Simon                     121  62.0%  
Philipp Kohlschreiber            133  60.9%  
Aljaz Bedene                     167  60.5%  
Richard Gasquet                  116  60.3%  
Andrey Rublev                    271  60.1%  
Roberto Carballes Baena          158  60.1%  
Carlos Alcaraz                   381  60.1%  
Botic van de Zandschulp          210  60.0%  
Robin Haase                      142  59.2%  
Sebastian Baez                   284  59.2%  
Borna Coric                      164  59.1%  
Pablo Carreno Busta              203  58.6%  
Lorenzo Musetti                  144  58.3%  
Novak Djokovic                  1099  58.0%  
Alexander Zverev                 793  57.9%  
Juan Martin del Potro            168  57.7%

(Nicolas Jarry?!)

That’s a very different list than what we saw above. The skills required to stretch out a rally are not quite the same as those needed to finish them off. The ideal, then, is a player who balances the two. Kei Nishikori’s win percentage is excellent, but Medvedev is nearly twice as likely to push any given return point to the ten-shot mark. Jarry plays ten-shot rallies on return less than one-third as often as the Russian does.

The key is to think in marginal terms. Longer points work in the returner’s favor, so we can think of every long point as a medium point that the returner successfully extended. The average player increases his chance of winning a rally by 21 percentage points (from ~35% to ~56%) by nudging it from “medium” to “long.” Call that the “marginal value” of a long rally. When we multiply a player’s marginal long-rally value with his frequency of generating long rallies, we get the total payoff of this defensive skill. The average player reaches ten shots about 11% of the time, so their payoff is 21% * 11% = 2.3%. It’s not a meaningful number on its own, but it provides a reference point for individual stats. If a returner’s payoff is higher, they get more benefit than average from their ability to generate long rallies.

Here’s the top 20 (plus a few other players of note), as measured by this combination of long-rally frequency and success rate:

Player                   Long Pts   Freq  MargValue  Payoff  
David Ferrer                  129  14.2%      30.5%    5.3%  
Roberto Carballes Baena       158  14.1%      29.0%    4.4%  
Gilles Simon                  121  14.7%      35.5%    3.9%  
Aljaz Bedene                  167  12.6%      31.2%    3.7%  
Lorenzo Sonego                131  11.7%      23.0%    3.6%  
Pablo Carreno Busta           203  13.0%      31.7%    3.5%  
Robin Haase                   142  11.5%      28.7%    3.5%  
Rafael Nadal                  863  14.4%      39.8%    3.3%  
Novak Djokovic               1099  16.2%      37.5%    3.3%  
Stefanos Tsitsipas            558  13.3%      32.4%    3.2%  
Juan Martin del Potro         168  12.6%      32.1%    3.2%  
Marton Fucsovics              137  16.0%      31.7%    3.1%  
Diego Schwartzman             751  17.3%      37.7%    3.1%  
Alexander Zverev              793  13.0%      36.0%    2.8%  
Daniil Medvedev               394  17.2%      36.1%    2.8%  
Richard Gasquet               116  10.5%      34.0%    2.8%  
Kei Nishikori                 141   9.6%      41.0%    2.7%  
Dominic Thiem                 931  13.2%      34.9%    2.7%  
Holger Rune                   185  11.1%      33.3%    2.7%  
Cameron Norrie                103  10.0%      29.5%    2.7%  
                                                             
Player                   Long Pts   Freq  MargValue  Payoff  
Jannik Sinner                 352  12.9%      38.5%    2.4%  
…                                                            
Andy Murray                   299  12.5%      33.1%    2.3%  
AVERAGE                                                2.3%  
…                                                            
Casper Ruud                   560   9.3%      35.9%    1.7%  
…                                                            
Carlos Alcaraz                381   8.4%      41.7%    1.5%  
Nicolas Jarry                 126   5.6%      38.4%    1.5%  
…                                                            
Stan Wawrinka                 193   8.4%      36.2%    1.4%

We have additional evidence, then, that David Ferrer is the 79th best player of the last century. These numbers might even understate his long-rally prowess, since I’ve limited this analysis to 2015-present. The timeframe probably hurts Nadal as well. Also, there aren’t many long points, so the small sample makes the top of the list somewhat misleading: I’m certainly not ready to take Lorenzo Sonego’s long-rally skills over most of the guys below him on the list.

Caveats aside, we have a plausible estimate of how much value each player reaps from his ability to drag servers into long rallies. Ruud and (especially) Alcaraz are very good past the ten-shot mark, but they don’t get there very often. Medvedev remains our king of negating short service points and creating long ones, but many of his peers are better at working a marathon rally to their own advantage.

No matter how we order the list, the key takeaway is that frequency is as important as win percentage. Returners rarely have a chance to finish points early, so extending the rally is almost always a positive step. Do that a lot, and you don’t have to convert a particularly high rate of those long points. Medvedev doesn’t, and he has become one of the tour’s best players on his least favorite surface. Annoyingly often, he breaks serve simply by putting one more ball in play.

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