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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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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More About Drop Shots: Alexander Bublik Edition

Alexander Bublik in 2022. Credit: Getty

If Carlos Alcaraz is the prince of the drop shot, Alexander Bublik is the court jester. We learned this week that Bublik hits droppers more than any other tour regular, about once every 14 points. That’s three times as often as tour average. No one else goes to the well more than once per 19 points.

Persistence aside, Sasha’s results are mixed: He wins about 45% of those points. That’s unimpressive compared to the ATP norm of 54%, and it’s particularly weak next to Alcaraz’s mark of 62%. Assuming that drop shots are, on average, hit from a neutral rally position, one in which each player has a 50% chance of winning the point, Bublik costs himself 3.3 points per thousand with his drop shot. In the last decade, only Benoit Paire has been worse.

On the other hand, the number rests on a big assumption. Alcaraz excels from the baseline; Bublik relies more on his serve. For any given situation–say, 5th stroke of a second-serve point, ball coming to the backhand side–Carlitos probably has a better chance of winning it, drop shot or not. Indeed, based on Match Charting Project data, Alcaraz wins 52% of points from that position. Bublik manages only 46%.

That’s typical. Here are the six situations in which Bublik hits the most drop shots, broken down by whether he is the server or returner, whether it’s a first- or second-serve point, the stage of the rally, and whether he’s faced with a forehand- or backhand-side shot. The table shows the probability that he wins the point if he doesn’t hit a drop shot:

Sv/Ret  Serve  Shot  Side  Exp W%  
Sv      1st    3rd   FH     57.4%  
Ret     2nd    4th   BH     42.8%  
Sv      2nd    3rd   FH     48.2%  
Sv      1st    3rd   BH     51.6%  
Ret     2nd    4th   FH     42.5%  
Sv      2nd    3rd   BH     46.1%  
Ret     1st    6th+  FH     42.2%

Only two of these scenarios favor Sasha: Plus-one forehands and plus-one backhands behind a first serve. Just about anything else and he’s the underdog.

Here are the same six situations, with expected point winning percentages for Alcaraz:

Sv/Ret  Serve  Shot  Side  Exp W%  
Sv      1st    3rd   FH     60.7%  
Ret     2nd    4th   BH     51.5%  
Sv      2nd    3rd   FH     57.3%  
Sv      1st    3rd   BH     54.1%  
Ret     2nd    4th   FH     53.6%  
Sv      2nd    3rd   BH     50.7%  
Ret     1st    6th+  FH     55.1% 

When Carlitos opts for a drop shot, he’s trading in what’s already a positive expectation for one that he hopes is even rosier.

Repeat this exercise for every situation in which Bublik has hit a drop shot, take a weighted average, and we find that had he not hit drop shots, he would have won 46.5% of those points. With that in mind, his 45.4% drop-shot winning percentage doesn’t look so bad.

The recalculation doesn’t tell us that Bublik’s drop shot is good, but it does make the tactic look more viable. We’re assuming that in the aggregate, all shot opportunities with the same profile (i.e. second-serve point, ball to the backhand for the fifth shot of the rally) are about the same. That’s just an approximation, so a gap of one percentage point could occur because Sasha chooses lower-percentage moments to hit the drop. There’s even a sliver of evidence that he does so: Eight of his charted drop shots are backhands on the seventh shot of the rally or later of his own first-serve points. Those sound like desperate efforts to finish a point he’s given up on, and sure enough, he lost all eight. Take those out of the equation, and his win percentage on drop shots is exactly the same as when he hits something else.

Drops in expectation

Go through the same exercise for every player, and the drop-shot leaderboard takes on a different look.

Some players, like Kei Nishikori and Nicolas Jarry, win a very high percentage of drop shot points and exceed expectations by a wide margin. Others, like Alcaraz, see less of a benefit from their drop shot, in part because their other options are so good. Still others, like Daniil Medvedev, win more than half of drop-shot points, but because of the rest of their game and the moments they choose to deploy the drop, they may be sacrificing some points when they do so.

Call the new stat Drop Shot Wins Over Expectation, or DSWOE: the ratio of drop-shot success rate to non-drop-shot winning percentage, taking into account the situations in which the player chooses the drop.

Among the 60 players with the most charted points since 2015, here’s the top of the list–the men who gain the most per drop shot–along with a few notable names in Bublik’s section of the list, plus the most extreme laggards:

Player                       Drop W%  Exp W%  DSWOE  
Nicolas Jarry                  65.3%   50.4%   1.30  
Lucas Pouille                  60.3%   48.1%   1.25  
Kei Nishikori                  68.1%   54.5%   1.25  
Sebastian Baez                 63.2%   50.9%   1.24  
Richard Gasquet                60.7%   50.0%   1.22  
Kevin Anderson                 53.8%   44.6%   1.21  
Reilly Opelka                  52.1%   43.5%   1.20  
Marton Fucsovics               58.2%   49.5%   1.18  
Alejandro Davidovich Fokina    59.3%   50.7%   1.17  
Roger Federer                  59.5%   51.4%   1.16  
Robin Haase                    54.7%   47.8%   1.14  
Frances Tiafoe                 54.6%   48.0%   1.14  
Pablo Carreno Busta            58.9%   52.2%   1.13  
Dominic Thiem                  57.1%   50.7%   1.13  
Carlos Alcaraz                 62.1%   55.7%   1.12  
Rafael Nadal                   61.5%   55.4%   1.11  
Andy Murray                    55.7%   50.5%   1.10  
…                                                    
Holger Rune                    51.4%   51.3%   1.00  
Grigor Dimitrov                47.7%   47.9%   0.99  
Alexander Bublik               45.4%   46.5%   0.98  
Daniil Medvedev                53.0%   54.8%   0.97  
Novak Djokovic                 50.8%   52.9%   0.96  
…                                                    
Stan Wawrinka                  45.3%   48.9%   0.93  
Milos Raonic                   38.0%   41.3%   0.92  
Benoit Paire                   42.9%   46.8%   0.92  
Tommy Paul                     47.0%   51.5%   0.91  
Aslan Karatsev                 39.0%   49.9%   0.70

Surrounded by names like Rune and Djokovic, Bublik doesn’t seem so bad. Alcaraz, on the other hand, doesn’t stand out as much. He and list-neighbor Rafael Nadal are outrageously good in rallies whether they hit a drop shot or not. Even a world-class drop shot is only so much better than a standard Rafa or Alcaraz topspin groundstroke.

Tour average is around 1.05, meaning that the typical player does a bit better when they hit a drop shot than they would have had they chosen a different shot in the same situation. That tells us something that we probably suspected: Players are generally good at choosing the right moment to unleash the drop.

With this more fine-grained notion of expectations, we can re-calculate the number of points per thousand that each player gains or loses from drop shots. It is a function of both success rate (relative to expectations) and frequency. Nishikori and Jarry get great results from the drop but employ it rarely; men like Alcaraz and Sebastian Baez gain more points overall because they hit droppers so much more often.

Here are the players who gain the most points, along with the five tour regulars at the bottom of the list:

Player                       Freq%  W% - Exp%  DPOE/1000  
Sebastian Baez                3.9%      12.3%        4.8  
Alejandro Davidovich Fokina   5.2%       8.5%        4.5  
Lucas Pouille                 2.9%      12.2%        3.5  
Carlos Alcaraz                5.4%       6.4%        3.4  
Richard Gasquet               2.8%      10.8%        3.0  
Robin Haase                   3.9%       6.9%        2.7  
Kei Nishikori                 2.0%      13.6%        2.7  
Frances Tiafoe                3.2%       6.6%        2.1  
Pablo Carreno Busta           2.8%       6.7%        1.9  
Nicolas Jarry                 1.2%      14.9%        1.8  
Fabio Fognini                 3.7%       4.7%        1.8  
Andy Murray                   3.3%       5.2%        1.7  
Dominic Thiem                 2.6%       6.4%        1.7  
Marton Fucsovics              1.9%       8.7%        1.7  
Roger Federer                 2.0%       8.1%        1.6  
…                                                         
Novak Djokovic                3.3%      -2.1%       -0.7  
Alexander Bublik              7.2%      -1.0%       -0.8  
Lorenzo Musetti               5.1%      -2.3%       -1.2  
Aslan Karatsev                1.2%     -10.9%       -1.3  
Benoit Paire                  5.4%      -3.9%       -2.1

Five (or 4.8) points per thousand might not sound like a lot, but it represents the difference between Baez having a place in the top 20 and residing well outside of it. Alcaraz still grades well here, if not as much as he did before making all of the adjustments. Bublik scores closer to neutral too. His drop shot is probably more useful for earning him highlight-reel screentime than it is for winning points, but it isn’t hurting him that much.

Side matters

Armed with these adjustments, we can compare each player’s forehand and backhand drop shots, as well. Bublik has a fairly wide split. He wins just over 50% of points when he hits a forehand drop shot, next to only 39% behind a backhand drop shot. His expectations when faced with a backhand are worse in general, but not that much worse. His forehand drop shot success rate is two percentage points better than if he went with a standard groundstroke, while his backhand drop shot is five points worse.

So Sasha, if you’re reading this: We all love your drop shots. But maybe take it easy with the backhands.

The best forehand drop shots, compared to how the player would have fared with a different shot, belong(ed) to Kevin Anderson, Sebastian Baez, Lucas Pouille, Marton Fucsovics, and Nishikori, with Roger Federer not far behind. The most effective backhand droppers are those of Jarry, Reilly Opelka, Pouille, John Isner, and Richard Gasquet. “Expectations” is the key word for Opelka and Isner: They didn’t win a lot of points once a rally was underway, so a moderately good drop scores very well by comparison.

Here is the field of 60 regulars from the last decade. As usual, top right is good, bottom left is… yikes, Aslan Karatsev.

There are innumerable way to divide these numbers even further, and I know you’re tempted. But with drop shots, there is only so much data. Some of the outliers here, like Jarry and Anderson, are probably a bit aided by luck. Men who don’t hit many drop shots might only have a few dozen attempts on their weaker side. The standouts probably are better than average, but limits of our data lead us to overstate their advantage.

At least with the forehand/backhand division, adjusted for how players would have fared with something other than a drop shot, we can get some hints as to how our faves can improve their games. Taylor Fritz has a strong backhand, and I doubt the points he’s losing with his backhand drop shot are making it any more effective. Alexander Zverev isn’t doing himself any favors with his occasional forehand droppers. Karatsev, well… not everyone can excel at everything.

Bublik, despite his negative numbers in the aggregate, has an effective forehand drop shot. With the power of his serve and forehand, he’ll continue to earn plenty of opportunities to use it. If he resists the urge to showboat on his backhand side, the court jester of the drop shot could continue to show off his touch and still earn a more coveted position in the tactic’s royal house.

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Effects and After-Effects of the Carlos Alcaraz Drop Shot

Also today: Wild cards and doping bans; Miami preview podcast

Carlos Alcaraz in the 2022 US Open final

It is not easy to analyze the drop shot. Players don’t hit it very often, they sometimes hit it from very favorable or very unfavorable circumstances, and the goal of the shot sometimes extends beyond winning the point at hand. We can point to someone who hits droppers well and seems to win a lot of points doing so, but how much is the skill really worth?

Carlos Alcaraz is the poster boy for the modern drop shot. He loves to hit it–possibly too much–and when he executes, it’s one of the most stunning shots in tennis. At the business end of his Indian Wells campaign last week, he went to the well seven times against Alexander Zverev, ten times against Jannik Sinner, and three more in the final against Daniil Medvedev. He won 11 of those 20 points. That doesn’t sound so impressive, but Alcaraz could hardly complain about the end result.

To get a grip on drop shot numbers, we have a lot of work to do. What is a good winning percentage? Do any players suffer because they hit the drop shot too much? Is there a lingering effect from disrupting your opponent’s balance? Finally, once we have a better idea of all that, how does Alcaraz stack up?

Drop shot basics

To keep the data as clean as possible, let’s be specific about which strokes we’re looking at. While one can hit a drop shot in response to another drop shot (a “re-drop”), and it’s possible to hit a drop shot from the net in reply to a short volley or half-volley, those aren’t typically what we’re referring to. There are probably players (starting with Alcaraz!) who are better at that sort of thing than their peers, but those low-percentage recoveries aren’t today’s focus.

In this post, when I say “drop shot,” I mean a drop shot from the baseline, excluding all shots from the net, including responses to earlier drops.

The Match Charting Project gives us over 4,600 men’s matches to work with since 2015. Those 750,000 points include almost 35,000 drop shots. That works out to a drop shot in about 4.6% of points. Or from the perspective of a single player, it’s 2.3%, 1 out of every 44 points. The player who hits the drop shot ends the point immediately (via winner or forced error) about one-third of the time, and 19% of the droppers miss for unforced errors. Overall, the player who hits the drop shot wins the point 53.8% of the time.

From the 60 players with the most charted points to analyze, here are the 15 who win the highest percentage of points behind their drop shots:

Player                       Drop Point W%  
Kei Nishikori                        69.6%  
Richard Gasquet                      66.2%  
Nicolas Jarry                        65.3%  
Sebastian Baez                       63.2%  
Carlos Alcaraz                       62.1%  
Rafael Nadal                         61.3%  
Lucas Pouille                        60.3%  
Roger Federer                        59.7%  
Alejandro Davidovich Fokina          59.3%  
Roberto Bautista Agut                58.9%  
Marton Fucsovics                     58.2%  
Pablo Carreno Busta                  58.1%  
Jannik Sinner                        57.7%  
Dominic Thiem                        57.5%  
Andy Murray                          56.7%

Alcaraz does well here! Despite the presence of Kei Nishikori at the top, the list is heavily skewed toward clay-courters. Drop shots are a more central tactic on clay than on other surfaces, which works in both directions: Clay-courters are more likely to develop good drop shots, and players who have dangerous droppers are more likely to succeed on dirt.

Another skill that contributes to a spot on the list is good judgment. Nicolas Jarry doesn’t hit many drop shots, so he is probably picking the ripest opportunities when he does. There’s almost zero correlation between frequency of drop shots and drop shot success rate. Call it the Bublik Rule. From the same group of 60 tour regulars, here are the top 15 ranked by frequency:

Player                       Drop/Pt  Drop Point W%  
Alexander Bublik                7.2%          45.4%  
Benoit Paire                    5.4%          41.7%  
Carlos Alcaraz                  5.4%          62.1%  
Alejandro Davidovich Fokina     5.2%          59.3%  
Lorenzo Musetti                 5.1%          50.7%  
Holger Rune                     4.8%          50.9%  
Sebastian Baez                  3.9%          63.2%  
Robin Haase                     3.9%          55.1%  
Fabio Fognini                   3.7%          54.7%  
Matteo Berrettini               3.5%          52.0%  
Nick Kyrgios                    3.3%          54.9%  
Andy Murray                     3.3%          56.7%  
Novak Djokovic                  3.3%          50.4%  
Botic van de Zandschulp         3.2%          51.4%  
Frances Tiafoe                  3.2%          54.1%

Bublik may be turning things around: In the Montpellier final last month, he attempted 18 droppers and won the point 14 times. For a consistent high-frequency, high-success combination, though, we’re back to Alcaraz. Only Carlos, Alejandro Davidovich Fokina, Sebastian Baez, and Andy Murray (barely) appear on both lists.

Here are all 60 players in graph form. The top right corner shows players who hit a lot of drop shots and win most of those points. The closer to the bottom, the lower a player’s success rate; the closer to the left, the fewer droppers he attempts:

As a percentage of all points played, Bublik wins the most behind his drop shot. But it comes at a cost, since he hits so many of them, often sacrificing points because of it. If we assume that each drop shot is struck from a precisely neutral rally position, meaning that the would-be dropshotter has a 50% chance of winning the point, Bublik is losing points by going to the drop shot so often.

That’s a big assumption, and it probably isn’t exactly true for Bublik, or for anyone else. But if we stick with that for a moment, we can combine frequency and success rate into one number. Take the difference between success rate and 50% (that is, the gain or loss by opting for a drop shot), multiply that by frequency, and you get the percent of total points that the player wins by choosing the drop. The resulting numbers are small, so here’s the top ten (and bottom five) list showing points gained or lost per thousand:

Player                       Drop Pts/1000  
Carlos Alcaraz                         6.5  
Sebastian Baez                         5.2  
Alejandro Davidovich Fokina            4.9  
Richard Gasquet                        4.5  
Kei Nishikori                          3.8  
Lucas Pouille                          3.0  
Pablo Carreno Busta                    2.3  
Andy Murray                            2.2  
Roberto Bautista Agut                  2.2  
Rafael Nadal                           2.0  
…                                           
Jo Wilfried Tsonga                    -0.8  
Feliciano Lopez                       -1.3  
Aslan Karatsev                        -1.3  
Alexander Bublik                      -3.3  
Benoit Paire                          -4.5

Reduced to one number, Alcaraz is our dropshot champion. Six points per thousand doesn’t sound like a lot, but to invoke the familiar refrain, the margins in tennis are small. Beyond the top five or ten players in the world, one single point per thousand is worth one place on the official ranking list. Stars of Alcaraz’s caliber are separated by wider gaps, but it’s still a useful way to gain some intuition about the impact of these apparently miniscule differences.

The after-effect

In the hands of someone like Carlitos, the drop shot is a reliable way to win points. But the impact can go further than that. All sorts of tactics–drop shots, underarm serves, serve-and-volley–can theoretically be justified by some longer-term effect. If your opponent is camped out six feet behind the baseline and you want him somewhere else, a drop shot will surely give him something to think about.

This is hard to quantify, to put it mildly. How long does the effect of a drop shot last? Does it decay after each successive point? Does it disappear at the end of a game? On the next changeover? Ever? Jarry might need to hit the occasional drop shot to remind his opponent that he can do it, but Alcaraz doesn’t even need to do that. Everybody knows he’ll dropshot them, so he’s probably in his opponent’s head even before he hits the first drop shot of a match.

The evidence is unclear. About two-thirds of drop shots are hit by the server. I looked at the results of points immediately after a point with a drop shot, points two points later, and all the points that followed within the same game. When the server hits the drop shot, his win percentage on those subsequent points is worse than his win percentage on other points throughout the match–that is, non-dropshot points that didn’t follow so closely after he played a dropper:

Situation          Win%  
Next point        63.3%  
Two points later  62.6%  
Same game         62.5%  
All others        64.2%

I suspect that the dropshot effect (if there is one) is swamped by all the other influences at work here. Droppers typically occur in longer rallies, which might tire the server. The server might go for a drop shot when he runs out of ideas, another thing that might go through his mind as he prepares for the next point. This seems to work against Alcaraz more than other servers:

Situation          Win%  
Next point        62.0%  
Two points later  62.1%  
Same game         63.2%  
All others        65.0% 

The same pro-returner bias appears when we look at the results when it is the returner who goes for the drop shot. After seeing the numbers above, it’s tough to say that hitting a drop shot causes the higher success rate on subsequent points, but it is nonetheless a striking effect, especially for Carlitos:

Situation      Alcaraz W%     Tour W%  
Next point          44.0%       38.3%  
Two points later    41.8%       37.6%  
Same game           41.5%       37.9%  
All others          40.1%       35.8%

Whatever the mechanism here, it goes beyond “drop shot good, opponent confused.” More research is needed, and camera-tracking data would help.

Regardless of the after-effects (or lack thereof), the stats support the common contention that Alcaraz possesses a world-class drop shot. He might use it too often in some matches, and certainly there are individual situations in which he should have done something else. In the aggregate, though, the tactic is working for him. It produces more value than any other player’s dropper has done in the last decade. Tennis analytics is hard, but goggling at the game of Carlos Alcaraz is easy.

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Wild cards and doping suspensions

Simona Halep returned to action this week, thanks to a Miami wild card granted immediately after her doping suspension was reduced. Halep is well-liked, and there were few objections to her appearance in the draw. But Caroline Wozniacki, while careful to say she wasn’t specifically targeting Halep, said that she was against dopers getting post-suspension wild cards.

We’ve done this before. In 2017, Maria Sharapova returned from 15-month ban and immediately got a wild card to enter Stuttgart. The tennis world spent a few weeks in a dither about whether she’d get one to the French Open, too. She didn’t.

I wrote about the Sharapova situation at the time. I argued that Sharapova ought to get those opportunities. The reason I gave at the time was that it was better for the sport: She was one of the best players in the game, and fields would be more competitive with her than without her. Another reason is that without wild cards, it’s a long road back. Unranked after more than a year on the sidelines, a player needs to enter qualifying at ITFs, wait two weeks for those points to go on the official rankings (assuming they win!), and then use those rankings to enter (slightly) stronger events, with entry deadlines several weeks in advance of the tournaments themselves.

Climbing back up the ladder can take months. Is that part of the penalty? Is a 15-month suspension supposed to be 15 months of no competition, followed by 3-6 months of artificially weak, poorly remunerated competition? In team sports, this isn’t an issue, because coaches can put returning players in the lineup as soon as they’re ready.

As usual, the problem is that tennis doesn’t have unified governance. None of the various bodies in charge have an applicable policy. Sharapova was fine, and Halep will be fine, because stars get wild cards (if not as many as they would like), while lower-ranked players are stuck heading to Antalya to rack up ITF points. The discrepancy is particularly glaring in a case like that of Tara Moore, who missed 19 months but has been fully exonerated.

The WTA is apparently considering granting special rankings to players who have been cleared of doping charges or had their bans reduced, essentially treating them as if they are returning from injury. That’s better than nothing, but it wouldn’t address the more common scenario illustrated by Sharapova’s return.

I would go further and grant special rankings to any player returning from suspension. The term of the suspension is the penalty, period. Even better, and fairer to the field as a whole: Grant those special rankings in combination with a policy that restricts wild cards. For instance, Halep could have eight or ten entries into tournaments on the basis of her pre-suspension ranking, but no wild cards for her first year back. That way, individual tournament directors don’t need to re-litigate each doping ban, players have a predictable path to follow post-suspension, and superstars aren’t given any special advantages.

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Miami preview podcast

I had a fun conversation yesterday with Alex Gruskin, talking about my recent Iga Swiatek piece and previewing the men’s and women’s draws in Miami. Click here to listen.

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Katie Boulter’s Game of Patience

Katie Boulter in 2021. Credit: Chris Czermak

You can be forgiven if you didn’t have Katie Boulter on your radar going into the 2024 season. Her career-best ranking in the top 60 was a bit misleading, stemming largely from a debut title on the grass at Nottingham, where she picked up the championship without facing a single top-130 player. Nothing she can do about that, of course, but when it came to things she could control, the results were not always so encouraging. She wrapped up 2023, at 27 years of age, with a career total of just 25 hard-court victories.

Since then, it’s been a whole new Katie. She opened her campaign with an upset of 5th-ranked Jessica Pegula at the United Cup, and counting qualifying, she has won at least one match at six straight events. To solidify her new status, she won the title in San Diego last week, knocking out four seeded players in the process. Nothing cheap here: All five of her opponents were ranked in the top 36, and the weakest among them–Lesia Tsurenko–had won each of their three previous meetings.

After years in the ITF wilderness, relying on British grass-season wild cards for tour-level appearances, Boulter has earned a place in the WTA top 30. Thanks to the giant-killing in Southern California, her Elo rating backs it up, placing her 28th on tour, 26th on hard courts. The Brit has always had a first serve and forehand that made it possible to dream big. It has just been a matter of harnessing the big weapons and filling out her game with complementary parts that wouldn’t leave her exposed.

The results from San Diego suggest that she has finally done so. Commentators like to talk about the importance of playing “within” oneself, waiting for opportunities instead of swinging for winners when none are on offer. Boulter hasn’t always done that, and she has the unforced error totals to prove it. She found a better balance against last week’s barrage of top-40 foes, playing a bit more conservatively and cutting down mistakes without sacrificing too many winners. Now, she’s on everyone’s radar.

Katie bolt the door

Boulter ascended through the ranks with what might best be described as low-percentage tennis. In her 100+ matches on tour, she has landed just 57% of her first serves, racking up more double faults than aces. 13% of her groundstrokes are unforced errors, well above tour average. Her typical return point lasts just barely three strokes.

In twelve matches logged by the Match Charting Project before last week’s run in San Diego, a mixed bag ranging from ITFs in 2017 to her final-round victory over Jodie Burrage in Nottingham last year, her Rally Aggression Score worked out to 84, putting her in the same range as free swingers such as Caroline Garcia and Camila Giorgi. Against Burrage, her Rally Aggression Score was 267, a remarkable figure for a stat that I initially scaled so that it would max out around 100. Just about every possible shot–plus a few impossible ones–was a winner or unforced error. The average point in that match lasted just 2.9 shots.

It’s possible to win with numbers like these–just ask Aryna Sabalenka, Petra Kvitova, or Jelena Ostapenko. But the margins are slim. It’s particularly tough to thread the needle while making as few first serves as Boulter does. Surprisingly, she struggled on that front in San Diego, making just 54% of her first deliveries for the week, including a mere 51% against Emma Navarro in the semi-final. When only one-quarter of total points begin with your best shot, you can’t risk missing so much with the rest of your arsenal.

The Brit’s most effective step forward, especially against Kostyuk in Sunday’s final, was to keep herself in more return points. She has traditionally swung big on return, ending 11% of second-serve points with a return winner or forced error, and even finishing 6% of first-serve points that way. She didn’t sustain those numbers in the final, but the tradeoff was worth it. In those previous 12 charted matches, she put just 60% of first-serve returns in play, compared to a tour average closer to 75%. Facing Navarro, she kept the point alive on 65% of first serve returns; against Kostyuk, she put the ball back in play 79% of the time.

The result, more or less by definition, was longer return points. While the Burrage match was extreme, it is not uncommon for Boulter to average in the neighborhood of three strokes per point on return–still in Ostapenko territory. The San Diego semi was a wholly different animal, with her average return point lasting 4.5 shots. In the final, it was 4.1 shots. Such a radical shift would be a bad sign for many big hitters: Ostapenko and her ilk end points early because that’s the way they want to play. Yet Boulter thrived on her newfound patience.

The 27-year-old won 47% of her return points in San Diego, five percentage points better than her tour-level average and about the same as a typical performance from Pegula or Coco Gauff. On Sunday against Kostyuk, Boulter played 81 return points and won 40 of them.

Winners, slightly delayed

Even though she did not smack as many return winners as usual over the weekend, Boulter still won plenty of points from the baseline. She just took fewer risks in the process. Excluding aces and double faults, here’s a top-level comparison of the frequency with which she hit winners (plus forced errors) and unforced errors in her last two matches, compared with her previous charted matches and WTA average:

Match(es)    W+FE  UFE  
vs Kostyuk    14%   9%  
vs Navarro    19%   8%  
Previous      16%  13%  
WTA Average   12%  10%

The Navarro match was an unalloyed triumph, as you might expect from the 6-3, 6-1 scoreline. But even the Kostyuk numbers point to a major step forward. It’s not easy to cut down unforced errors from one side of tour average to the other, especially against someone like the Ukrainian, who feeds opponents an ever-shifting mix of speeds and depths. In the past, the Brit might have lost her rhythm and gone on an error spree. Instead, she was even steadier. On 28 key return points–game point, deuce, or break point–Boulter committed just one unforced error.

Facing women without the weapons to quickly end points themselves, Boulter discovered that a winner on the fourth or fifth shot of the point is just as effective, and less risky, than a big swing on the second or third shot. In her previous charted matches, she won about 49% of points that lasted four to six shots. Against Kostyuk, she won 76%, dictating play the way she has always preferred to do, just one or two shots later.

Presumably, it won’t always be quite this easy. Boulter won’t keep her unforced error rate in single digits forevermore; more aggressive opponents will tempt her into playing her old game. (Though the Brit did straight-set Donna Vekic in the quarters.) Still, she appears to have discovered new capabilities, seven years after her first appearance at Wimbledon. This year, she’ll likely return to the All-England Club as a seeded player, with all the expectations and pressure that entails. A decade into her pro tennis career, Boulter has earned herself a lot more attention.

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