Category: Serve statistics

How Coco Gauff Escaped a Trap of Her Own Making

Also today: Jannik Sinner’s near-unbreakability

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

Coco Gauff is not a pusher, but she can do an awfully good impression of one. In yesterday’s Australian Open quarter-final against Marta Kostyuk, the American coughed up 50 unforced errors against just 17 winners. The average rally lasted 4.6 strokes, a modest number that was rescued from marathon territory only by Gauff’s many unreturned serves.

Coco’s forehand, the usual culprit when things get messy, was on full display yesterday. While the stroke has shown signs of improvement–only 9% of them contributed to the unforced error tally, below both tour average and Gauff’s own standard–it remains loopy, and it gets ever-more cautious under pressure. Kostyuk was willing to go after the high-bouncing mid-court groundstrokes, often putting Gauff on the run. Fortunately for the American, her defense rarely deserts her. She eked out a three-hour, 7-6, 6-7, 6-2 victory for a place in the Melbourne semi-finals.

My impression watching the match was that Gauff put an unreasonable number of returns–especially forehand returns–in the middle of the court, not too deep, and that Kostyuk was punishing them. I was partly right: The Ukrainian forced Coco to hit forehand after forehand against the serve, more than two-thirds of her service returns all told. Gauff did indeed send more of those balls down the middle, closer to the service line than the baseline. And Kostyuk attacked… but to little avail.

Let’s get into the numbers. The Match Charting Project divides the court into thirds, both in terms of direction (forehand side, backhand side, and middle) and depth (shallow [in the service boxes], deep [closer to the service line than the baseline], and very deep). All else equal, shots deep and/or to the sides of the court are better, though of course they are riskier. Some returns will inevitably end up down the middle and shallow; the goal is only to avoid it when possible.

Here is how Gauff’s performance yesterday compared to tour average and her own typical rate of service returns that went down the middle and didn’t land close to the baseline:

RETURNS          Middle/Not Very Deep  
Tour Average                    34.0%  
Coco Average                    40.5%  
Coco vs Kostyuk                 43.7%

Indifferent return placement is nothing new for the American, and she left even more hittable plus-ones for Kostyuk than usual. It wasn’t as bad as last year’s US Open final against Aryna Sabalenka, when Gauff put more than half of her returns in the less effective zones, but Kostyuk is no Sabalenka when it comes to imposing her will with the serve.

Return placement matters. On average, tour players win 46% of points when they land a down-the-middle, not very deep return. When they put the ball anywhere else–closer to the baseline or a sideline–they win 56%. Gauff is a little better behind the weak returns, but for her career, the gap is still present: 47% versus 55%.

Except… that isn’t what happened yesterday!

RETURN OUTCOMES  Mid/NVP W%  Better W%  
Tour Average          46.2%      56.3%  
Coco Average          46.9%      54.8%  
Coco vs Kostyuk       60.0%      55.2%

When Gauff placed a return near a line, her results yesterday were typical. But Kostyuk was unable to capitalize on the rest. Among 88 matches logged by the Match Charting Project, Gauff has won 60% of those middle/not-very-deep returns only a dozen times, usually in blowouts.

Judging from the American’s performance on return, she could have made quick work of yesterday’s contest, too. The sticking point came on her own side of the ball, where her non-committal forehands didn’t work out as well.

Minus-ones

On the WTA tour, when the return lands in play, the server has nearly lost her advantage. A good first serve can give her a lingering edge, or a well-placed return can tilt the balance in the other direction, but overall, the point begins again as a neutral proposition. Servers win 52% of those points.

Gauff, on average, does a little better, converting her serve 53% of the time. There are signs she’s improving, as well. In the US Open final against Sabalenka, she won 55%, and in the Auckland final this month versus Elina Svitolina, she picked up 59%. Apart from lopsided matches, the high-50s are the best anyone can do on an ongoing basis: Iga Swiatek’s average is 57%, and Sabalenka’s is 55%.

Coco won 39% against Kostyuk.

Gauff’s lack of confidence in her forehand showed up in multiple ways. First, she didn’t use it as much as a plus-one weapon. She usually hits 57% of her plus-one shots from the forehand side, in line with tour average. Yesterday, that rate was just 51%, something that had more to do with her own choices than any return magic that Kostyuk conjured up.

Then, she didn’t do much with those forehands. The following table shows plus-one forehand rates (3F%), the percentage of plus-one forehands hit down the middle (FH Mid%), and the server’s winning percentage (FH Mid W%) behind those down-the-middle forehands:

PLUS-ONES          3F%  FH Mid%  FH Mid W%  
Tour Average     56.6%    29.9%      45.9%  
Coco Average     57.2%    35.0%      47.0%  
Coco vs Kostyuk  50.7%    39.5%      40.0%

Gauff magnified her own tendency to go back down the middle with her second-shot forehand. It didn’t work, as she won just 40% of those points, compared to her typical rate of 47%.

Even beyond the plus-one, Coco just kept pushing the forehand. She went down the middle with 46% of her forehands, compared with her usual 37% and the tour average of 28%. She won barely one-third of the points when she did so, partly because of the nine unforced errors she racked up playing an already conservative shot. Two of those missed down-the-middle forehands came on back-to-back points when she could hardly afford them, taking her from 15-all to 15-40 when trying to close out the match at 5-3 in the second set.

In the end, as we’ve seen, Gauff’s defense saved her. She won more than half of Kostyuk’s serve points despite lackluster returning. Had she served just a little better–she missed six straight first serves in that 5-3 game–she would have finished the job an hour sooner. Had she attacked a bit more effectively with her second shots, even the off-day from the line wouldn’t have amounted to much.

To state the obvious: She’ll have to play better to beat Sabalenka in tomorrow’s semi-finals. One thing, at least, will work in Coco’s favor: She’ll have many fewer choices to make. The defending champion will dictate play and give her less time to think than Kostyuk did. Gauff withstood the Belarusian barrage in New York, winning the US Open title despite a couple of detours against less aggressive players in the early rounds. The American can’t play tomorrow like she did yesterday, but thankfully, Sabalenka won’t let her.

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Jannik Sinner’s near-unbreakability

Jannik Sinner has lost his serve just twice en route to the Australian Open semi-finals. He has faced 28 break points and saved 26 of them.

Since 1991, when the ATP started keeping the relevant stats, he is the 26th player to reach the final four at a major with so few breaks of his own serve:

Tournament  Semi-finalist       BP Faced  Broken  
2013 USO    Rafael Nadal               6       0  
2018 Wimb   John Isner                 7       0  
2015 Wimb   Roger Federer              3       1  
1994 Wimb   Pete Sampras               9       1  
2015 AO     Novak Djokovic            11       1  
2014 Wimb   Roger Federer             12       1  
1997 Wimb   Pete Sampras              12       1  
2010 USO    Rafael Nadal              14       1  
2012 RG     Rafael Nadal              17       1  
2004 Wimb   Roger Federer             17       1  

Tournament  Semi-finalist       BP Faced  Broken  
2014 Wimb   Milos Raonic               9       2  
2011 RG     Novak Djokovic*            9       2  
2007 USO    Roger Federer              9       2  
2006 Wimb   Roger Federer              9       2  
2006 Wimb   Rafael Nadal               9       2  
2015 USO    Roger Federer             11       2  
2014 AO     Roger Federer             11       2  
1997 USO    Greg Rusedski             11       2  
1993 AO     Pete Sampras**            12       2  
2013 Wimb   JM del Potro              13       2  
2019 AO     Rafael Nadal              15       2  
2008 Wimb   Roger Federer             15       2  
2005 AO     Andy Roddick              15       2  
1998 Wimb   Pete Sampras              17       2  
2000 AO     Yevgeny Kafelnikov        22       2  
2024 AO     Jannik Sinner             28       2

* Djokovic won one round by W/O and another by retirement
** I don't have stats for Sampras's QF, but the final score suggests that he wasn't broken

Pretty good company! As the table makes clear, though, Sinner’s 28 break points faced is not so elite. In fact, the average major semi-finalist faces exactly 28 break points in his first five matches.

The Italian’s accomplishment, then, is saving so many. 26 of 28 is a 93% clip, and that is more rarefied air:

Tounament  Player      Faced  Saved   Save%  
2013 USO   Nadal           6      6  100.0%  
2018 Wimb  Isner           7      7  100.0%  
2012 RG    Nadal          17     16   94.1%  
2004 Wimb  Federer        17     16   94.1%  
2010 USO   Nadal          14     13   92.9%  
2024 AO    Sinner         28     26   92.9%  
2014 Wimb  Federer        12     11   91.7%  
1997 Wimb  Sampras        12     11   91.7%  
2015 AO    Djokovic       11     10   90.9%  
2000 AO    Kafelnikov     22     20   90.9%

Things will get tougher on Friday, when Sinner faces all-time-great returner Novak Djokovic for a place in the final. Then again, Djokovic failed to convert his first 15 break points against Taylor Fritz yesterday–maybe he was just preparing for the matchup with Sinner.

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Andrey Rublev, Grand Slam Quarter-finalist

Also today: Jannik Sinner’s rosy forecast; lopsided fifth sets

Andrey Rublev at Wimbledon in 2023. Credit: aarublevnews

Andrey Rublev is a known quantity. He will hit big first serves, but his second serves can be attacked. He will hit monster forehands, often venturing far into his backhand corner to play them, and his opponents will often be stuck in place, watching them go by. He’ll also miss a lot of them. His backhand isn’t the same type of offensive shot; he can be dragged into long rallies if you pepper that side.

There isn’t a lot of subtlety to his game. That isn’t a criticism: Subtlety can win you acolytes and endorsement deals, but it isn’t necessary to win championships. With yesterday’s five-set win in Australia over home hope Alex de Minaur, Rublev advanced to his tenth career grand slam quarter-final. He’s 0-9 so far in those matches, but his consistency in getting there is the bigger story. Alexander Zverev is the only other man under the age of 30 with ten major quarter-finals. Rublev will get on the board eventually.

What you might not know about the 26-year-old Russian is that he has matured into a reliably dangerous returner. He’s always been effective on that side of the ball, and his return numbers have remained steady as the strength of his competition has increased. Last year, he won nearly 39% of his return points, good for 3.2 breaks of serve per match–seventh-best on tour. At the 2023 US Open against Daniil Medvedev, his most recent attempt to reach a major semi-final, Rublev broke serve five times in his straight-set defeat. The return wasn’t the problem.

That day, Medvedev’s return was the problem. (Andrey’s second serve didn’t do him any favors either, but that’s nothing new.) Of Rublev’s 98 serve points, 65 of them lasted four shots on longer. I can’t emphasize enough how bizarre that is–or, seen from another perspective, what a performance it was from his opponent. Medvedev not only got 65 serves in play, he got 65 plus-one shots back. Rublev’s top two weapons were negated.

The standard Rublev performance, at least among the 138 matches logged by the Match Charting Project, involves 59% of his service points ending by the third shot. He wins just over three-quarters of those. (Against Medvedev, he tallied a respectable 70%, but 70% of not very many is still not very many.) Put those numbers together, and 45% of his serve points end in his favor in three shots or less.

That’s a pretty good head start! Last year, the Russian won 66% of his total serve points. The majority of the damage gets done early.

The serves and plus-ones not only account for a decent chunk of the points played–at least on a good day–but they also serve as a proxy for how the longer rallies turn out. When Rublev wins most of his short service points–even when he doesn’t play as many as he would like–he almost always comes out on top. If we sort his charted matches by winning percentage on short service points, then split them into thirds, the difference is stark:

<=3 SPW%       Matches  Match Win%  
81%+                45         87%  
75.5% - 80.9%       44         64%  
up to 75.4%         49         24%

(The buckets are slightly different sizes only because I didn't want to put nearly identical percentages into separate categories.)

When Rublev wins most of the short service points, he wins the match. When he doesn't, he usually loses. If anything, the table understates the contrast; a disproportionate number of the low-percentage victories came on clay, including several on the slow dirt of Monte Carlo.

To some extent, it's obvious that "winning more of some subset of points" correlates with "winning more of all the points" and thus winning the match. But remember, this is the success rate independent of how many points end quickly. The combination of frequency and success--"what percent of total service points end quickly and in the server's favor"--should tell us more about the overall result. But for Rublev, that metric isn't as predictive of final outcomes as the winning percentage alone.

Battling demon

Yesterday against de Minaur, Rublev won 82% of the short service points. The Australian kept it close by reducing the number of short points to just under half of Rublev's serves. But the rule I've just outlined held true, despite a pesky defense. When de Minaur put the fourth shot back in play, he won 57% of return points. That's great, but with Rublev cleaning up the overwhelming majority of the short points, it wasn't enough.

We have shot-by-shot logs for four of the six matches between these two guys:

Tournament        Result  Short%  Short W%  
2024 Australian        W   49.4%     82.0%  
2023 Rotterdam         L   60.3%     75.6%  
2022 Monte Carlo       W   42.7%     73.2%  
2018 Washington        L   53.2%     71.6%

De Minaur did his job yesterday, keeping the ball in play more often than he did in the two previous hard-court meetings. (The Monte Carlo surface presumably helped lengthen points in that match.) The Australian won both of those earlier contests, watching Rublev make more plus-one mistakes and taking care of business when the rallies lasted longer.

In Melbourne, the Russian stayed a bit more within himself. He was able to hit a forehand on barely half of his plus-one shots--below both tour average and his own typical rate. Instead of blasting away with ill-advised backhands--part of what lost him the Rotterdam match--he accepted the invitation to rally. His 43% rate of winning longer service points isn't great, but it's far superior to the 0% chance of claiming the point after smacking an unforced error.

I don't want to overstate Rublev's caution, because he didn't play a cautious match. He probably never should. But getting a few more balls in play and fighting out the ensuing rallies makes his second serve look a lot better. As we've seen, Rublev does well on return. His second-serve points aren't much better than return points... but that's okay! Yesterday he won 55% behind his second serve, a glittering result compared to the 37% and 38% he won against de Minaur in Washington and Rotterdam, respectively.

Is this the one?

Rublev can be forgiven for having a losing record in major quarter-finals; he's been the lower-ranked player in seven of the nine. He's dropped two to Novak Djokovic, one to Rafael Nadal, and three to Medvedev. He should have picked up one (or three) along the way, but as the fifth man on a tour that always seems to have a big three or four, it's an uphill struggle.

Tomorrow's opponent is Jannik Sinner, just one place above him in the ATP rankings. (Elo likes him more than that--a lot more. See below.) This will be their seventh meeting, and history doesn't bode well for the Russian. Sinner has retired twice but won the other four.

Here are the short-service-point stats for Rublev in three of those matches:

Tournament        Result  Short%  Short W%  
2023 Miami             L   62.5%     77.1%  
2022 Monte Carlo       L   41.0%     58.5%  
2021 Barcelona         L   43.8%     85.7%

(Unfortunately we don't yet have a chart of his 7-6, 7-5 loss last fall in Vienna.)

This isn't insurmountable for the Russian: He often wins matches behind 77% of his short service points, and he almost always does with a 86% win rate. He'd like more than 44% of his serve points to end quickly, but that's tougher to execute on clay.

Against Sinner, the first three shots are even more important than usual, because the Italian plays a similar game, and once a rally reaches four strokes, he plays that game better. In Miami, Sinner won two-thirds of Rublev's "long" service points. In Monte Carlo, he won 54%, in the vicinity of what de Minaur did yesterday. In Barcelona, Sinner won a whopping 70% of return points when he got the fourth shot in play--as he more often than not did.

Rublev's second serves tell the story, as they did in the de Minaur match. Those, typically, are the points he can't finish early, when he should be thinking in terms of constructing the point, not grunting and crushing. In the four completed Sinner matches, he won only 37.5% of second-serve points. That's not going to get it done.

To beat an elite opponent, Rublev needs to remember when to bash and when to think. He executed well yesterday, pulling away in the end against a man who never stops fighting. Reaching his first major semi-final, against 22-year-old who seems to get stronger every week, he'll need to play even better.

* * *

Sinner in the hands of a friendly forecast

Jannik Sinner is the favorite tomorrow: According to my Elo-based forecast, he has a 78% chance of advancing to the final four. That's a hefty margin for a match between players adjacent to one another in the official rankings. The difference is more about Sinner than Rublev: My forecast gives Sinner a nearly 30% shot at taking the title, second only to Djokovic.

While the Italian ranks fourth on the ATP computer, he's second according to the Elo algorithm, closer to Djokovic than anyone else is to him. Here is the top of the table entering the Australian Open:

Rank  Player             Elo  
1     Novak Djokovic    2217  
2     Jannik Sinner     2197  
3     Carlos Alcaraz    2149  
4     Daniil Medvedev   2104  
5     Alexander Zverev  2037  
6     Andrey Rublev     2035  
7     Grigor Dimitrov   2032

If you think in terms of major titles, official ranking points, or hype, this probably seems wrong. By those measures, Sinner is the laggard among the top four.

But Elo gives credit based on the quality of opponents beaten, and Sinner built quite a resume in the last quarter of 2023. He beat Rublev, Alcaraz, Medvedev (three times!), and most important, Djokovic twice. Nothing catapults you up the Elo list faster than knocking off the top dog.

The question, then, is whether Elo has overreacted to those two victories. My implementation of the Elo algorithm doesn't differentiate between narrow wins and blowouts. (Other versions use sets, games, or even points, though in my testing, those alternatives don't make the ratings more predictive.) The two Djokovic upsets were nail-biters. The Tour Finals round-robin match was decided in a third-set tiebreak, and each man won exactly 109 points. At the Davis Cup Finals, Sinner took the third set 7-5 despite winning fewer total points than his opponent.

While Sinner certainly deserved those victories--staring down match point against a 24-time major winner is a feat in itself--we might wonder how much they tell us about future results. If the two men keep fighting out such close matches, Djokovic is going to win some of them.

Each of the two upsets were worth a gain of 15 Elo points. Had Sinner lost them, he would've dropped 10 or 11 points instead. Call it a 25-point swing for each match. Thus, if we take the most pessimistic possible route and give both of the dead-heat results to Djokovic, Sinner's Elo rating would stand about 50 points lower, roughly tied with Alcaraz around 2,150.

(That isn't exactly right, because if Djokovic had won the Davis Cup match, Italy wouldn't have advanced to the final, and Sinner would've have beaten de Minaur. But Sinner did beat de Minaur, handily, and if we want to assess his current level, we shouldn't ignore that match.)

Handing both of the close results to Djokovic seems extreme. If we want to measure each player's current level without putting too much weight on the tiny number of points that decided those two matches, we might give one of the two victories to Djokovic. That would knock Sinner down to about 2,172, while boosting Djokovic to around 2,225.

In the Australian Open title-chances forecast, Novak would look a little better, and there would be more daylight between him and Sinner. Still, unless we make the harshest possible adjustment to Sinner's Elo rating, the Italian remains the next most likely Melbourne champion and a heavy favorite against Rublev tomorrow.

* * *

Dessert bagels

The Rublev-de Minaur match had an unusual ending: After splitting four sets, the Russian ran away with the fifth, 6-0.

Typically, if two players are so evenly matched that they reach a fifth set, neither one is going to dominate the decider. For the rare occasions that it happens, it's unique enough that I think it deserves its own name. I propose "dessert bagel."

In grand slam competition since 1968, there have been just 159 dessert bagels, including Rublev's--fewer than one per major. No one has ever recorded a dessert bagel in a final, but it has happened twice in semis. Mats Wilander polished off Andre Agassi in the 1988 Roland Garros semi-final, and Djokovic finished his 2015 Australian Open semi against Stan Wawrinka the same way. Still, second-week dessert bagels are rare: Rublev's was only the 16th in more than a half-century.

It's an oddity piled on oddities: Rublev-de Minaur was the fifth dessert bagel in Melbourne this year:

Round  Winner      Loser       Score                
R128   Mannarino   Wawrinka    6-4 3-6 5-7 6-3 6-0  
R64    van Assche  Musetti     6-3 3-6 6-7 6-3 6-0  
R64    Medvedev    Ruusuvuori  3-6 6-7 6-4 7-6 6-0  
R32    Kecmanovic  Paul        6-4 3-6 2-6 7-6 6-0  
R16    Rublev      de Minaur   6-4 6-7 6-7 6-3 6-0

Five 6-0 deciders is a record for a single slam. There haven't been as many as three since the 2007 Australian, and no major has seen more than one since 2017. If even more dessert bagels start piling up in the quarter-finals, we'll know that something bizarre is going on Down Under.

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Qinwen Zheng’s Serve Under Construction

Also today: The odds of a 42-point tiebreak; January 19, 1974

Qinwen Zheng in 2023. Credit: Hameltion

Qinwen Zheng is one of the top prospects in the women’s game, up to 14th on the WTA ranking list at age 21. She won her first tour-level title in Palermo last summer, then upset Ons Jabeur en route to a quarter-final showing at the US Open. After topping Barbora Krejcikova for a second title in Zhengzhou, she reached the final at the WTA Elite Trophy, falling in a two hour, 52-minute final to Beatriz Haddad Maia.

With yesterday’s upsets of Elena Rybakina and Jessica Pegula at the Australian Open, Zheng’s draw opened up. With only one other seed in the second quarter, she’s the heavy favorite to earn a semi-final date with Iga Swiatek. Potential is poised to become reality.

It’s never been difficult to dream big on the Chinese woman’s behalf. Her service motion–once she gets past a hitchy toss–is a photographer’s dream, and she takes advantage of her five-foot, ten-inch frame to send first serve after first serve into the corners. When she hits a target out wide, returners are lucky to get a racket on the ball, let alone put it back in play. Her forehand is equally powerful.

The results bear out the devastation wreaked by her first delivery. Here are last year’s WTA top ten in first-serve percentage:

Player               1stWon%  
Qinwen Zheng           73.7%  
Elena Rybakina         73.6%  
Aryna Sabalenka        72.8%  
Caroline Garcia        72.5%  
Liudmila Samsonova     71.5%  
Iga Swiatek            70.0%  
Petra Kvitova          69.8%  
Belinda Bencic         69.5%  
Petra Martic           69.5%  
Ekaterina Alexandrova  69.4%

Pretty good company, huh? Her forehand grades well, too. According to Match Charting Data, Zheng hits more winners, induces more forced errors, and commits fewer unforced errors with that shot than the average player on tour. Her forehand potency (FHP) per match over the last 52 weeks is 10.8, placing her in the top ten among tour regulars, just behind Haddad Maia and Madison Keys.

That’s the good news. If you’re going to have just two world-class weapons, those are the ones to pick. They’ve served her well so far: If she justifies her seed and reaches the final four in Melbourne, she could crack the top ten.

The rest of Zheng’s game is–let’s be optimistic here–a work in progress. Today I want to look specifically at her serve as a whole; we’ll save her not-as-problematic backhand for another day.

When the 21-year-old lands her first serve, as we’ve seen, good things happen. She hits more aces than almost anyone on tour, and about half of her first-serve points end with either an unreturned first serve or a plus-one winner. The problem is, she doesn’t make many first serves, and when she misses, her second serve is as erratic as her first serve is imposing.

The average top-50 player on the WTA tour makes about 62% of her first serves. In 2023, Zheng succeeded just 51.8% of the time, almost three full percentage points below anyone else.

Making matters worse, her second-serve results are nearly as bad. The average top-50 WTAer wins 47% of her second-serve points. Zheng won 45.5%, a mark that places her in the bottom third of that group. Among the current top 20, only Jelena Ostapenko and Daria Kasatkina win fewer second-serve points. It’s even worse against a strong opponent. She hung onto just 20% of second-serve points against Swiatek in the United Cup this month, 24% versus Rybakina in Beijing, and a mere 26% against Liudmila Samsonova in Montreal. Zheng’s primary weapon makes her look like an elite server, but the overall picture is more mundane. Her first serve sets her on a level with Rybakina, but she barely holds serve as often as Petra Martic.

What is to be done?

This seems like it should be fixable, especially in so young a player. It’s certainly easy to dream. Imagine the seemingly-modest scenario in which Zheng manages to land her first serves and win second-serve points at the rates of an average top-50 player while maintaining her dominance on firsts. She would then win 63.5% of her service points. Only Swiatek and Sabalenka do better.

Easier said than done, of course. A good first serve is no guarantee of a strong second. On the women’s tour, there almost zero correlation between first-serve and second-points won.

Still, this seems like partly a tactical failure, not entirely a gap in her skillset. If Zheng can win nearly 74% of her first-serve points when she misses almost half of the time, what would happen if she served a bit more conservatively? Perhaps she could make 57% of her first serves and still win 72% of them? If so, that would be a bit better. Could she make 62% of first serves–the tour average rate–and win 70% of them? That would be better still.

Once we assume that these tradeoffs are feasible, the whole thing starts to sound like less of a tactical question and more of a pure math problem. I’m not sure that it is: Players practice various types of “first serves” and “second serves,” not every theoretical delivery on the continuum between them. Maybe a thoughtful veteran could tweak things to increase or decrease her first-in percentage at will, but I’m skeptical that a young player could do th esame. At the very least, it’s a project that would take some time.

Still, it’s worth working out whether Zheng could get more bang for her serve-talent buck. In 2009, Dutch researchers Franc Klaassen and Jan R. Magnus (henceforth K&M) published a paper in the Journal of Econometrics that proposed to answer this sort of question. They worked out the usual relationship between serving risk (how many first serves in, how many double faults) and reward (rate of first- and second-serve points won). My friend Jeff McFarland converted their rather complex algorithm to a spreadsheet, which is why I’m able to publish this today, and not in March. Thanks Jeff!

The following table shows Zheng’s actual 2023 results along with her model-optimized rates:

         1stIn%  1stWon%    DF%  2ndWon%   SPW%  
Actual    51.8%    73.7%   6.0%    45.5%  60.1%  
Optimal   60.5%    70.9%   8.8%    47.5%  61.7%

K&M’s formula estimates that Zheng could get close to a tour-average level of first serves in and still win about 71% of them, a success rate that would keep her in the top five. The more surprising output is that she could do better by taking more chances on her second serve. (This is a kind of light version of the oft-discussed argument that a player should just hit two first serves. The algorithm recommends some degree of this for most pros.) By adopting the more risky second-serve approach, she would in theory win 47.5% of those points despite the increase in double faults.

Altogether, those changes would increase her total service points won from 60.1%–12th among the current top 50–to 61.7%, which would rank her fifth.

Another way of looking at the potential gain is in points per thousand. For every thousand service points played, the fully-optimized version of Zheng would win about 16 more than she does now. If her return game remained the same, that’s an improvement of eight points per thousand overall. A few years ago I stumbled on a neat rule of thumb, that an improvement of one point per thousand translates into a gain of one place in the rankings, except near the very top. If that held in this case, the re-imagined Zheng would be on the cusp on the top five.

Again, this is all theoretical. I have no idea whether a big server could consciously execute a decision to take slightly fewer chances on the first and more on the second, or whether her results would follow the model if she did.

But! This is a potential route to a jump up the rankings without reworking groundstrokes, getting fitter or stronger, or even gaining experience. It’s probably not easy, but it’s likely simpler than the alternatives. As it stands now, Zheng’s second serve–and the frequency she’s forced to hit it–is going to hold her back. Solve that problem, and much of her obvious potential is unlocked.

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The odds of a 42-point tiebreak

“10-point tiebreak, my ***.” Credit: @hardpicstennis

Yesterday, Elena Rybakina and Anna Blinkova played a 42-point tiebreak. It’s the longest breaker in grand slam singles history. Blinkova won it, 22-20.

What are the odds?

Let’s start with simply getting to 9-all. We’ll assume that Rybakina and Blinkova were playing at the same level. Yes, Rybakina was a heavy favorite entering the match, and she won a few more points than Blinkova to get to 6-4, 4-6, 6-all. But the margin was narrow, and the math is simpler if we assume they are equal. They won serve points throughout the match at about a 59% rate. Since players tend to be more conservative during tiebreaks, returners fare better, so we’ll say that whoever is serving had a 55% chance of winning the point.

I ran a Monte Carlo simulation to find the odds of reaching 9-all. Here are those probabilities, along with odds at various other levels of serve dominance:

SPW   Reach 9-all  
55%         10.0%  
60%         10.3%  
65%         11.2%  
70%         12.5%  
80%         17.0%

Roughly speaking, there was a one-in-ten chance that yesterday’s breaker would reach 9-all.

From there, the math is simpler. There are two ways to get from 9-all to 10-all: both women could win their service points, or both could win their return points. Serving at 55%, the chances that one or the other occurs are 50.5%. The same logic applies to the step from 10-all to 11-all, 11-all to 12-all, and so on. So for Rybakina and Blinkova, getting from 9-all to 20-all was roughly equivalent to flipping a coin eleven times and getting heads every time–a one-in-two-thousand shot.

To reach 20-all, then, players need to get to 9-all, then trade points another eleven times. For servers at 55%, that’s a one-in-ten shot followed by a one-in-two-thousand shot, or one in twenty thousand–a 0.005% likelihood–altogether.

Here are the equivalent numbers for servers at various levels:

SPW   Reach 9-all  Reach 20-all  that's 1 in…  
55%         10.0%        0.005%         18357  
60%         10.3%        0.008%         12916  
65%         11.2%        0.014%          7086  
70%         12.5%        0.031%          3201  
80%         17.0%        0.244%           409

You might remember the 24-22 tiebreak that Reilly Opelka won against John Isner in Dallas a couple of years ago. The probabilities are dramatically different depending on how serve-dominant the players are, so the Rybakina-Blinkova result was considerably more far-fetched than what Opelka and Isner produced. Adjusting for the fact that the Dallas tiebreak was first-to-seven and assuming that both players won 80% of serve points (an estimate on the low side), this method gives us a one-in-2,192 chance of that tiebreak reaching 22-all.

There are various ways to tweak the numbers. It might be the case that players perform better facing match point; if so, it’s a bit more likely that they’d reach this sort of outrageous score. Maybe it’s appropriate to give Rybakina a modest edge over Blinkova; if we did that, the odds of drawing even so long would be lower. One-in-18,357 isn’t exactly right, but it gives us a rough idea of just how unusual yesterday’s feat truly was.

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January 19, 1974: Sanctioned

Four months from its proposed opening day, things finally started to look up for World Team Tennis. On January 18th, the USLTA officially sanctioned the league in exchange for a $144,000 fee. Another chip fell the next day, when American co-number one Jimmy Connors signed with the Baltimore Banners.

WTT still had several hurdles to clear. The British LTA continued to object to the league’s attempted takeover of so many weeks of the summer calendar. The ILTF, as well, had yet to give their okay. The ATP, still a nascent players’ union, also held back. A few top men–John Newcombe, Ken Rosewall, and now Connors–had thrown in their lot with the upstarts, but until the union made its stance clearer, the WTT ranks remained dominated by women stars.

Across the country, those women were making the case that they’d be able to draw sufficient crowds on their own. Also on January 19th, the first event of the 1974 Virginia Slims circuit came to a close. 6,000 fans packed San Francisco’s Civic Auditorium to watch Chris Evert take on Billie Jean King for the title. Another 2,000 were turned away at the gates. Traffic was jammed for blocks in every direction, and ticket scalpers worked the rows of stalled motorists.

The Slims tour had been dominated by Margaret Court in 1973, with Billie Jean hampered by injury and Evert competing on a separate tour sponsored by the USLTA. This year, Court was absent, pregnant with her second child. If San Francisco was any indication, the Australian would hardly be missed. The federation had made peace with the one-time rebels of the Slims tour, and now Gladys Heldman’s women-only circuit was the only game in town. Billie Jean was healthy (and the ultimate marquee draw, after defeating Bobby Riggs), and Evert provided new blood.

Chrissie also provided fresh motivation for the Old Lady. King had hinted that she would dial back her tournament commitments in 1974, but she wasn’t one to back down from a challenge. Playing no-ad games for the San Francisco title, Billie Jean kept her younger opponent under constant pressure. Five times Evert reached sudden-death point on her serve; five times she saved it. King finally pulled ahead to take the first set, winning the tiebreak, 5-2. Evert mounted a comeback from 0-4 in the second, but Billie Jean halted her momentum when she chased down a drop shot that Chris didn’t think she could touch.

“She was very gutsy and I once thought I had no chance,” King said after the match. “And thank God for giving me a pretty good pair of wheels on that particular shot.”

Billie Jean was thrilled at both the result and the sellout crowd. Nothing pleased her more than a successful women’s tour–except, of course, for a successful women’s tour with herself on top.

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The Manufactured Attack of Caroline Garcia

Caroline Garcia in 2019. Credit: Peter Menzel

Last night, Caroline Garcia scored what many fans saw as an upset, straight-setting two-time Australian Open champion Naomi Osaka. While Garcia was seeded 16th and Osaka is just beginning a comeback, no one ever knows quite what to expect when the Frenchwoman takes the court. The former champ, for her part, has always been at her best on big stages.

The result was almost pedestrian. Garcia turned in a performance that exemplified the tennis of her late 20s: Serving big, returning pugnaciously, taking risks, and–on the rare occasions that Osaka left her an opening–net rushing. Osaka served well, but the 16th seed out-aced her, 13 to 11. More than three-quarters of points were decided in three shots or less, and Garcia stole a few more of those from her opponent than Osaka did from her. In a contest defined by small margins–one break of serve and a tiebreak–that was all it took.

The strange thing is, Caro didn’t use to play like this. She plays shorter points than any other tour regular, an average of 2.9 shots per point in charted matches from the last 52 weeks. It isn’t just about her powerful first serve: Her return points end even sooner than her serve points do. Back in 2018, when she first reached her career-best ranking of 4th on the WTA computer, she was averaging over four shots per point, a rally length that would put her in the range of Jessica Pegula and Maria Sakkari: in other words, a very different sort of player.

Here is the evolution of Garcia’s rally length, shown as a rolling 10-match average, for the 84 matches in the charting dataset:

Last night’s rally length was a blink-and-you’ll-miss-it 2.5 shots, the second-lowest figure I have on record for Garcia. Only a match against Donna Vekic last year comes in slightly lower, though last week’s match in Adelaide against Jelena Ostapenko may have been even more extreme. Osaka’s big game helped keep the number down, but it takes two to so comprehensively avoid the long-rally tango.

Garcia’s first serve has always been a weapon. But her tactical approach behind it has fluctuated wildly. The career trend of her Aggression Score in rallies illustrates how she has careened from one extreme to another. Aggression Score is scaled so that the most passive players rate around -100 and the most aggressive around 100, though Ostapenko and others have pushed the maximum figures further into triple digits. Here is how Garcia’s score has changed over time, again as rolling ten-match averages:

I don’t think there any other player in tennis–man or woman, past or present–who has followed a path like this. As she established herself as an elite on tour, even as she rose into the top five, she became more and more conservative. For reference, players who posted scores around zero in 2023 were Sakkari and Martina Trevisan, hardly styles that will remind you of Garcia’s. Eventually she reversed course, not only regaining her former style but surpassing it, ranking among Liudmila Samsonova and Aryna Sabalenka as one of the most aggressive players on tour, a rung below the class-of-her-own Ostapenko.

Is it working?

The oddest thing about the multiple phases of Garcia’s career is that she has reached the No. 4 ranking with two different styles. In each of her first three charted matches after achieving the peak ranking in 2018, she posted negative rally aggression scores. In two matches against Sabalenka, she averaged 3.9 and 3.7 shots per point; against Karolina Pliskova in the Tianjin final, the typical point lasted 4.3 strokes. When she returned to the No. 4 ranking at the end of 2022, after years in the wilderness, she was frequently posting triple-digit aggression scores and average rally lengths below 3.

The main effect of Garcia’s current style is that it makes the most of her serve. From 2015 to 2017, she won just over 66% of her first-serve points, a mark that is good but sub-elite. She fell all the way to 62% in 2021 before the big shift; since then, she has won more than 70% of her first-serve points. She ranked fourth in that stat heading into the Australian Open, and she converted nearly 90% of her first serves against Osaka. Her success behind the second serve hasn’t shown the same improvement, but the overall picture is a good one: She won more total serve points in 2023 than ever before.

The return game is a different story. This is where even a casual viewer can’t miss Caro’s new tactics: She’s not afraid to stand well inside the baseline to return serve, and yesterday she net-rushed one Osaka serve, SABR-style. Measured by court position, if not by winners and error stats, Garcia is even more aggressive than Ostapenko.

At her best, the Frenchwoman posted acceptable return numbers, if not great ones. Her best single-season mark, winning 42.7% of her return points in 2017, put her in the bottom third of top-50 players. As she has upped the intensity of her attack, this key number has headed south:

In the last 52 weeks, she has won just 38.3% of return points, worst among the top 50 by two full percentage points. Among the top 20, no one else is below 42%. She can get away with it because her own serve is so rarely broken, but such ineffectual return results will make it difficult to mount another assault on the top five. Breaking serve so rarely dooms her to a career of three-setters and narrow decisions. Those sorts of results can sometimes be encouraging–as in her pair of recent three-set losses to Iga Swiatek–but have a knack for halting winning streaks, too.

It doesn’t have to be this way. Players don’t sign contracts agreeing to deploy the same tactics on both sides of the ball. Garcia won return games far more often in her less aggressive days, breaking 33% of the time in 2017 compared to a dreadful 23% last year.

Some of Caro’s 2017 skills are still in evidence. She is solid enough in long rallies that she doesn’t need to so actively avoid them: In the last year, she has won a respectable 48% of points that lasted seven or more strokes, and if you remove the two Swiatek matches, she breaks even. While the Osaka match was primarily determined by short points, Garcia won 17 of 29 (59%) that went to a fourth shot.

Without any major changes, Garcia will remain the sort of player who aggravates fans and opponents alike, a dangerous lurker capable of delivering upsets, inexplicable marathons, and lame early exits in equal measure. Like any hyper-aggressive player, Caro’s results can be seemingly random, with all the frustration that entails. Unlike Ostapenko, Sabalenka, and the many ball-bashers on tour, though, Garcia has chosen to play this way, rebuilding her game into something that the 2018 version of herself would hardly recognize. If she can somehow join her late-career serve to her earlier return-game tactics, the randomness will disappear, and Caro may make yet another appearance in the top five.

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The Most Exclusive Clubs In Tennis

The new Big Two?

Tireless podcaster Alex Gruskin likes to talk about what he calls the “top-ten, top-15, top-20, and top-25 clubs.” He works out the membership of each one by consulting the Tennis Abstract ATP and WTA stats leaderboards, which display dozens of metrics for each of the top 50 ranked players on both tours.

To qualify for Alex’s “top ten club,” a player needs to be in the top ten in both hold percentage and break percentage–in other words, to be an elite server and returner. Even cracking the top 25 club is no easy task. In 2023, only 11 men were better than half of the top 50 on both sides of the ball. It’s more common to excel at one or the other. In 2022, the best returner (Diego Schwartzman) ranked 50th out of 50 on serve, and the best server (Nick Kyrgios) came in 40th on return.

The top-25 club is a high standard, and the top-ten club is a stratospheric one. This year, only three men–Novak Djokovic, Jannik Sinner, and Carlos Alcaraz–made the cut, and Alcaraz almost missed it, ranking 10th in hold percentage. Daniil Medvedev almost qualified, but he trailed Alcaraz by 0.7% in hold percentage and came in 11th in that category.

Three top-ten clubbers is, as it turns out, an unusual showing. In the 33 seasons for which we have the necessary stats to calculate hold and break percentage (back to 1991), only 13 men have ever managed the feat. Many of them did it several times, so there are a total of 49 player-seasons that qualify. For the two-plus decades between 1991 and 2011, there were only two seasons in which more than one player reached both top-ten thresholds. In 1992, the entire tour fell short.

By “club” standards (and most others), Djokovic’s 2023 season was particularly impressive. Alex usually classifies players into round-number clubs, occasionally giving credit to a near-miss who makes, for instance, the “top 26” club. We can extend the concept a bit further and place every season into its best possible club: If a player ranks in the top three by both hold and break percentage, he’s in the “top-three” club; if he ranks among the top four in both, he’s in the “top-four club,” and so on.

In 2023, Novak led the tour in hold percentage and was bested by only Alcaraz and Medvedev in break percentage. Thus, he’s a member of the top-three club. More exclusive categories are hard to find. Here’s the complete list of top-three clubbers since 1991, along with their ranks in hold percentage (H% Rk) and break percentage (B% Rk):

Year  Player          H% Rk  B% Rk  CLUB  
2023  Novak Djokovic      1      3     3  
1999  Andre Agassi        3      1     3  
1995  Andre Agassi        3      3     3

That’s it.

Sinner’s 2023 campaign was also sneakily great. He finished a deceptive fourth on the official ATP points table, but by ranking fifth in hold percentage and fourth in break percentage, he joined an absurdly elite group of top-five clubbers: only Djokovic, Agassi, Rafael Nadal, and Roger Federer.

Here’s the full list of top-ten club seasons since 1991:

Year  Player            H% Rk  B% Rk  CLUB  
2023  Novak Djokovic        1      3     3  
1999  Andre Agassi          3      1     3  
1995  Andre Agassi          3      3     3  
2021  Novak Djokovic        4      3     4  
2013  Rafael Nadal          4      1     4  
2008  Rafael Nadal          4      1     4  
2002  Andre Agassi          4      3     4  
2023  Jannik Sinner         5      4     5  
2019  Rafael Nadal          5      1     5  
2017  Rafael Nadal          5      2     5  
2015  Novak Djokovic        5      1     5  
2014  Novak Djokovic        5      2     5  
2012  Rafael Nadal          5      1     5  
2007  Rafael Nadal          5      2     5  
2006  Roger Federer         2      5     5  
2003  Andre Agassi          5      3     5  
                                            
Year  Player            H% Rk  B% Rk  CLUB  
2022  Novak Djokovic        6      4     6  
2013  Novak Djokovic        6      2     6  
2021  Daniil Medvedev       7      4     7  
2020  Rafael Nadal          7      2     7  
2019  Novak Djokovic        7      2     7  
2012  Novak Djokovic        7      2     7  
2011  Novak Djokovic        7      1     7  
2010  Rafael Nadal          2      7     7  
2008  Novak Djokovic        7      4     7  
2004  Roger Federer         2      7     7  
2021  Alexander Zverev      8      7     8  
2020  Daniil Medvedev       8      8     8  
2018  Novak Djokovic        8      5     8  
2016  Novak Djokovic        8      2     8  
2015  Roger Federer         4      8     8  
2005  Roger Federer         2      8     8  
2001  Andre Agassi          8      3     8  
1998  Marcelo Rios          8      2     8  
1991  Stefan Edberg         4      8     8  
                                            
Year  Player            H% Rk  B% Rk  CLUB  
2022  Daniil Medvedev       8      9     9  
2020  Andrey Rublev         9      5     9  
2018  Rafael Nadal          9      1     9  
2017  Roger Federer         2      9     9  
2009  Andy Murray           9      2     9  
2007  Roger Federer         3      9     9  
2000  Andre Agassi          8      9     9  
2023  Carlos Alcaraz       10      1    10  
2020  Novak Djokovic       10      4    10  
2019  Roger Federer         3     10    10  
2013  Roger Federer         7     10    10  
1998  Andre Agassi         10      3    10  
1994  Andre Agassi         10      5    10  
1993  Thomas Muster        10      4    10

The list is heavily weighted toward the Big Three and the current era. Whether it’s surface speed convergence or something about the players themselves, it’s tougher to reach the top with a lopsided game these days. Stefan Edberg was a top-eight clubber in 1991 (and might have been as good for several seasons before that), but Pete Sampras didn’t get anywhere close. His best showing by this metric came in 1997, when he cracked the top-14 club. Andy Roddick never even cleared the top 30.

Finally, here are the 15 men who reached both top-30 thresholds in 2023:

Year  Player            H% Rk  B% Rk  CLUB  
2023  Novak Djokovic        1      3     3  
2023  Jannik Sinner         5      4     5  
2023  Carlos Alcaraz       10      1    10  
2023  Daniil Medvedev      11      2    11  
2023  Andrey Rublev        17     11    17  
2023  Karen Khachanov      18     16    18  
2023  Alexander Zverev     15     18    18  
2023  Grigor Dimitrov      19     15    19  
2023  Taylor Fritz          6     19    19  
2023  Casper Ruud          21     17    21  
2023  Holger Rune          20     21    21  
2023  Frances Tiafoe        9     26    26  
2023  Ugo Humbert          29     23    29  
2023  Roman Safiullin      30     24    30  
2023  Sebastian Korda      14     30    30

Women’s clubs

The WTA gets the short shrift on topics like these, because much less historical data is available. I only have the necessary stats back to 2015, and even that season is incomplete.

Still, that doesn’t make some recent individual performances any less impressive. Iga Swiatek’s effort in 2023 predictably stands out: She came in third behind Aryna Sabalenka and Caroline Garcia in hold percentage, and she trailed only Sara Sorribes Tormo and Lesia Tsurenko in break percentage. By finishing third in both categories, she–like Djokovic–is a member of the top-three club.

Depending on how you define a full-season, Iga might be the first ever woman to reach such a standard, at least in the nine-year span for which we can do the math. Here is the full list of top-ten clubbers back to 2015:

Year  Player             H% Rk  B% Rk  CLUB  
2016  Victoria Azarenka      2      1     2  
2023  Iga Swiatek            3      3     3  
2022  Iga Swiatek            5      1     5  
2019  Serena Williams        1      6     6  
2015  Serena Williams        1      7     7  
2016  Serena Williams        1      8     8  
2016  Angelique Kerber      10      6    10

Azarenka’s run in 2016 was really a partial season: She hurt her knee and didn’t play again after retiring from her first-round match at the French. Her first four months of tennis put her on the path toward a historic campaign, but we’ll never know how it would have turned out. Those 29 matches can’t really be set along the same measuring stick as Iga’s 75-plus in each of the last two years. Serena’s three entries on this table were almost as abbreviated, but again we’re reminded of the limited data. Surely the list would be much longer, with many more instances of the Williams name, if we had better data.

Anyway, all hail the great Iga. May her reign last until Sabalenka figures out how to become a top-ten returner.

At least this year, it was slightly harder to crack the top-25 and top-30 clubs in the women’s game than it was in the men’s. Here is the full 2023 women’s list down to the top-32 threshold, which allows us to include a few names of interest who missed out on the top 30:

Year  Player               H% Rk  B% Rk  CLUB  
2023  Iga Swiatek              3      3     3  
2023  Cori Gauff              13      8    13  
2023  Jessica Pegula          16      5    16  
2023  Madison Keys             6     16    16  
2023  Barbora Krejcikova      12     18    18  
2023  Victoria Azarenka       19     17    19  
2023  Aryna Sabalenka          1     20    20  
2023  Marketa Vondrousova     22      6    22  
2023  Karolina Muchova         8     22    22  
2023  Leylah Fernandez        20     27    27  
2023  Jelena Ostapenko        28     12    28  
2023  Marie Bouzkova          29     21    29  
2023  Caroline Dolehide       23     30    30  
2023  Elina Svitolina         31     24    31  
2023  Beatriz Haddad Maia     18     31    31  
2023  Ons Jabeur              32      9    32  
2023  Belinda Bencic           5     32    32

More than ever, a well-rounded game is a necessity for players who hope to reach the top. For fans, “clubs” like these are a useful way to think about which stars are getting the job done on both sides of the ball.

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What If Jannik Sinner Made More First Serves?

Jim Courier thinks he should:

Among the current top 50, there’s actually a negative correlation between height and first-serve percentage–that is, taller guys make slightly fewer first serves, all else equal–but that doesn’t directly contradict what Courier said. There’s a whole lot that we could investigate in that couple of lines, but let’s stick with the question in the headline.

In the 52 weeks going into the current Miami event, Jannik Sinner made 57.3% of his first serves. That’s the lowest rate of the current top 50, and well below the average of 63%. When he makes his first serve, he wins 74.7% of points–slightly better than average–and on second-serve points, he wins 54.7%, which ranks 11th among the top 50. Altogether, he’s winning 66.2% of service points, again a little bit above top-50 average.

Courier presumably meant that Sinner’s first serve needs to be more reliable, not that he should take something off of it. In the hypothetical, then, he’ll continue to win roughly 75% of first-serve points. He’ll just have more of them.

If Sinner made 65% of his first serves instead of 57.3%, and he continued to win first and second serve points at the same rate, he’d improve his overall winning percentage on service points from 66.2% to 67.7%. That’s equivalent to increasing his hold percentage from 84.9% to 87.1%. (He’s currently holding 83.9% of the time, so he might be a bit unlucky.)

One and a half percentage points–how much does that really matter?

For starters, it would improve his position on the top-50 leaderboard from 24th to 11th. Now, he’s winning service points like Frances Tiafoe and Roberto Bautista Agut. Improved by 1.5%, he’d be in another league entirely, equal to Felix Auger-Aliassime and Taylor Fritz.

Another way of looking at it is within my framework of converting points to ranking places. As a rough rule of thumb, winning one additional point per thousand translates into a improvement of one place on the ranking table. That relationship doesn’t hold at the very top of the rankings, where players are not so tightly packed. But when I first introduced the framework in 2017, the relationship among players ranked 2nd to 10th was that–again, approximately–two points per thousand translated into one place in the rankings.

Back to Sinner. If he won 1.5% more service points, that’s a 0.75% increase overall. (We’re assuming his return game is unchanged.) Call it 0.8%, or eight points per thousand. According to the top-ten version of my rule, that’s worth four spots in the computer rankings.

Sinner is currently ranked 11th on the ATP computer, and after advancing to the Miami semi-finals yesterday, he ranks 9th on the live table. He could head back to Europe as high as 6th if he wins the title. From any one of those positions, a four-place jump would be significant.

Yet the Italian might be better even than that. My Elo ratings place him 4th, behind only Novak Djokovic, Carlos Alcaraz, and Daniil Medvedev. There’s no reliable relationship between points per thousand and ranking places at the very top of the table, but Elo hints at what an elite player Sinner already is. Tack on seven or eight more points per thousand and he might not be the number one player in the world, but he’s right there in the mix.

That is, at least as long as no one else improves even faster. Sinner isn’t alone in his 66.2% rate of service points won. Alcaraz entered Miami with exactly the same number. Sinner has more room to improve his first serve percentage than anyone else at the top of the game, but his rivals will hardly stand around and watch while he does.

The Underserved First Point

Not all points are created equal. Ask around, and you’ll get a variety of opinions as to which points are most important. Break points, obviously, are key. Pundits are fond of 15-30.

Then there’s the first point of the game. It’s been conventional wisdom for a long time that the opening points holds disproportionate weight. In a previous study, I disproved that. Of course it’s valuable to move from 0-0 to 15-0, and no one likes to start a game by dropping to 0-15. But the first point doesn’t have any magical effect on the outcome of the game beyond simply adding to one or the other player’s tally.

Yet here I am, talking about the first point again. While there still isn’t any magic, the first point is going to the returner too often. With a slight change in tactics or focus, this is a rare analytical insight that pros may be able to use to win a few more service games.

Point by point

The balance between the server and returner varies a great deal depending on the point score. In men’s singles matches at the US Open between 2019 and 2021, servers won 63.6% of points in non-tiebreak games. Yet at 40-love, the server won 67.7%, and at ad-out, the server won only 59.6%.

The point scores that generated such extremes hint at what’s going on here. If a game has reached 40-love, the server is probably a good one. It’s not always the case, but if you look at all the 40-love games in a large dataset, you’ll get far more John Isner holds than Benoit Paire holds. The opposite applies to ad-out, a score that Isner rarely faces. Thus, the difference in point-by-point serve percentage isn’t (entirely) because of the point score–it’s because of the servers who get there.

Other differences are more prosaic. On average, servers win more deuce-court points than ad-court points. In the same three-year dataset, the difference was 64.2% to 62.9%. There’s no selection bias component here. The typical ATPer is simply stronger in that direction. Some players–particularly left-handers–break the mold, but most will favor the deuce side. Both Novak Djokovic and Roger Federer, for instance, win nearly two percentage points more often when serving to that court.

Unbiasing

Because scores like 40-love and ad-out aren’t randomly distributed among servers, we need to do a bit more work to figure out which scores really do favor the server. The trick here is to compare each service point to the rest of the server’s points in the same match. A point like 40-love has a ton of Isners and Opelkas in it, so we’ll end up comparing it to a lot of other Isner and Opelka points. And in fact, the average player who reaches 40-love wins 65.0% of their service points and 64.3% in the ad court, two numbers that are well above average.

Working through the same exercise for every point score gives us a list of “actual” serve points won, “expected” serve points won, and differences. The “actual” column tells us what really happened at that score, bias and all; “expected” tells us how often that particular set of players won service points during the entire matches in question; and the difference gives us a first look at where servers are over- or under-performing.

The following table shows these numbers for each point score:

Score  Actual  Expected  Difference  
40-AD   59.6%     61.4%       -1.8%  
0-0     63.3%     64.6%       -1.3%  
15-0    62.7%     63.3%       -0.6%  
40-30   61.6%     62.2%       -0.6%  
15-30   62.3%     62.7%       -0.4%  
30-0    64.7%     65.1%       -0.3%  
40-40   62.6%     62.8%       -0.1%  
0-15    63.2%     63.3%       -0.1%  
                                     
Score  Actual  Expected  Difference  
40-15   64.6%     64.5%        0.0%  
30-15   62.8%     62.7%        0.1%  
AD-40   61.6%     61.4%        0.2%  
30-30   64.0%     63.6%        0.4%  
0-30    65.9%     65.2%        0.8%  
15-15   64.8%     64.0%        0.8%  
30-40   63.6%     62.2%        1.4%  
0-40    66.1%     64.7%        1.4%  
15-40   66.9%     64.5%        2.4%  
40-0    67.7%     64.3%        3.4%

The scores at the top of the table are the ones where we would expect servers to win more points. At the bottom of the list are those where the server seems to overperform.

Some of the results lend themselves to easy narratives. Servers really focus at 0-40 and 15-40, while returners know they have more break chances coming. 40-AD (ad-out) seems like a stressful time to serve, and the numbers back that up. Other results are a bit more baffling–shouldn’t 30-30 and 40-40 be the same, since they are logically equivalent? Why are servers performing so well at 30-40 if they ultimately struggle at 40-AD?

And to today’s topic: What about the first point? It ranks second only to 40-AD in how much the server underperforms, despite no obvious reason why it should lean one way or the other.

Second to none

When we consider a few more factors, this first-point underperformance has an even greater impact.

One useful way to measure the importance of a point is with win probability. Given any point score (or set/game/point score), combined with the likelihood that the server will win any given point, you can calculate the probability of a hold (or a match victory). If we assume that the server wins 64.2% of points, he’ll hold 81.6% of the time, so his win probability at the beginning of the game is 81.6%.

* 64.2% was the rate in non-tiebreak games at the 2021 US Open, while the overall rate for this 2019-21 dataset is a bit lower.

The next concept is volatility. A point’s volatility is determined by how much the result could swing the win probability. By winning the first point, the server’s win probability rises to 89.7%, the figure for such a server at 15-love. If he loses, it falls to 67.2%. The difference–22.5%–tells us how much is at stake in that single point.

In volatility terms, the first point isn’t particularly crucial. A 22.5% swing far outstrips, say, the 9.3% volatility at 30-love, but it pales next to the 76.3% volatility at 30-40. When the server faces break point, one swing of the racket can determine whether win probability drops to zero (because he loses the game), or bounces back north of 50% (because he gets back to deuce).

What the first point of the game gives up in volatility, it wins back in volume. The stakes are never higher than at 40-AD, but at the US Open in the last few years, barely one-fifth of games ever get that far. By contrast, there’s a love-love kickoff in every single game.

By combining volatility and volume with the degree to which servers under- or over-perform, we can put together a top-level view of what players are gaining or losing at each point score.

Multipliers gone wild

In a tour de force of mathematical derring-do, I’m going to take these three numbers and multiply them together.

The “difference” from the previous table tells us how much better or worse players are serving at a specific point score, compared to their overall performance. If two differences are similar, the one that matters more is the one with higher volatility, right? So we multiply by volatility. And all else equal, the more often a situation occurs, the greater its impact on the end result. So we multiply by the number of occurrences in the dataset.

The final tally is volatility * occurrences * difference, cleverly dubbed “V*O*D” in the table below. The product of three percentages is tiny, so I’ve multiplied those figures by 10,000 to make the results easier to read.

Here are the results:

Score  Volatility  Occurrences  Difference  V*O*D  
40-AD       76.3%          22%       -1.8%  -29.9  
0-0         22.5%         100%       -1.3%  -29.2  
15-30       44.9%          34%       -0.4%   -5.8  
15-0        16.5%          50%       -0.6%   -4.9  
40-30       23.8%          26%       -0.6%   -3.6  
40-40       42.5%          43%       -0.1%   -2.6  
0-15        33.2%          50%       -0.1%   -2.3  
30-0         9.3%          27%       -0.3%   -0.9  
                                                   
Score  Volatility  Occurrences  Difference  V*O*D  
40-15        8.5%          24%        0.0%    0.1  
30-15       20.7%          34%        0.1%    0.6  
AD-40       23.8%          22%        0.2%    1.1  
40-0         3.0%          16%        3.4%    1.7  
30-30       42.5%          32%        0.4%    5.9  
0-40        31.4%          16%        1.4%    7.1  
0-30        40.0%          27%        0.8%    8.2  
15-15       29.4%          46%        0.8%   11.0  
30-40       76.3%          25%        1.4%   26.3  
15-40       49.0%          24%        2.4%   28.2

With all factors taken into account, we see that servers are giving up about as much on the first point of the game as they are when faced with nerves at 40-AD. Two point scores also stick out at the other end of the spectrum, where 30-40 puzzlingly continues to be a time when servers find their best stuff.

Exploiting the mundane

The exact V*O*D numbers are far (far!) from natural laws, but when I ran the same algorithm on data from other grand slams, the contours were nearly the same. In the 2017 and 2018 US Opens, for instance, 40-AD and 0-0 were again the standout “underperforming” points, and 0-0 was the one that topped the list.

* I took a rudimentary look at this topic very early in the blog’s history, using data from 2011. 0-0 didn’t stick out to the same degree, but I didn’t control for the deuce/ad difference, as I have today. When accounting for deuce-court strength, 0-0 performance looks relatively worse.

All of which is to say: I can’t explain why this is a thing, but it sure looks like it’s a thing. And if it’s a thing, it looks like an opportunity for savvy players and coaches.

I’m perfectly happy to accept that servers struggle to maintain their focus (and perhaps their ability to surprise) at 40-AD. More importantly, I’m sure that players and coaches are very aware of the necessary mental gymnastics so deep in a game.

On the other hand, there’s no good reason that servers should underperform at the start of every game. In fact, I’d be more ready to accept the idea that servers would have the edge. The opponent hasn’t seen a serve for a few minutes (or more), and the server’s arm is (relatively) fresh. While it’s not a recipe for domination, it sounds like a recipe for a tiny edge that the server can build on.

That’s why I believe there’s something to be exploited here. Perhaps players–or at least some of them–are taking a bit off their first-point first serves, using the opening salvo as a mini-warmup. Maybe they are more willing to hit their second-best serve, or aim to the returner’s stronger side, as a tactical move to set up more effective serves later in the game. As I’ve said, I don’t know why the numbers are turning up this underperformance, but it’s clear there’s a gap to be closed.

There’s no magic in the first point, but there’s an awful lot of value. Players who serve up their best stuff at the beginning of the game are getting an edge that their peers ought to be developing, too.

The Best at Getting Better

Here’s a stat you probably didn’t know*. Since the restart, the WTA top five in first-serve points won are Naomi Osaka, Serena Williams, Ashleigh Barty, Jennifer Brady, and … Maria Sakkari.

** unless you’ve been listening to me podcast lately.

The first four names are to be expected: Osaka, Williams, and Barty are probably the top three offensive players in the game, period, and Brady makes her money with big serving. Sakkari is the one who stands out. She does many things well, but I would never have thought to put her in this group, ahead of the likes of Karolina Pliskova, Aryna Sabalenka and, well, everybody else.

Sakkari’s first serve might be the best-kept secret in the women’s game, in large part because it hasn’t been around to keep secret for long. When she started playing tour events, her serve was quite weak, and it has only gradually improved since then. That’s what I marvel at. In six seasons at tour level, all with at least 18 matches played, here are her rates of first-serve points won:

Year     1st Win%  
2016        58.6%  
2017        59.7%  
2018        63.7%  
2019        65.2%  
2020        66.5%  
2021        69.9%

This probably doesn’t need further explanation. Fewer than 60% of first serve points isn’t very good, 70% is excellent, and improving from one to the other is a massive accomplishment. But in case you’re not convinced, here’s the same progression along with percentile rankings, showing that Sakkari started her career better than only 13% of her peers, and this year is outperforming 93% of them:

Year     1st Win%  Percentile  
2016        58.6%          13  
2017        59.7%          20  
2018        63.7%          53  
2019        65.2%          67  
2020        66.5%          79  
2021        69.9%          93

Players can and do improve, but they usually retain the same relative strengths and weaknesses throughout their career. The Greek star has broken that mold, and there’s a natural follow-up question: Has there been anyone else like her?

Meet Kiki

Here’s the simple filter I used to identify players who had substantially improved this aspect of their game. For every player with a full season in which they won fewer than 60% of first-serve points (almost exactly the 20th percentile), I identified those who eventually recorded a full-season in the top half of WTA players, roughly 63.3% or better.

From 2010 to 2021–yes, an awfully short span, due to the limited availability of historical WTA match stats–112 different players posted a sub-60% season. 26 of them went on to an above-average year. One example is Carla Suarez Navarro, who won 59.0% of first-serve points in 2010, and peaked at 64.0% (56th percentile) in 2016. That’s a respectable progression, but far from Sakkari’s standard.

Here are the 10 players who improved on a sub-60% season to eventually manage a season of 65% or better, ranked by the best level they attained:

Player       Weak   1st%  %ile  Strong   1st%  %ile  
K Bertens    2015  59.5%    18    2019  71.9%    97  
M Sakkari    2016  58.6%    13    2021  69.9%    93  
D Kasatkina  2017  59.0%    15    2021  66.4%    78  
S Halep      2012  56.4%     3    2014  66.4%    78  
Y Shvedova   2011  59.4%    17    2016  66.1%    75  
A Cornet     2011  58.9%    14    2020  66.1%    75  
M Linette    2016  59.9%    21    2020  65.8%    73  
Y Wickmayer  2012  60.0%    22    2017  65.8%    72  
A Sasnovich  2016  58.4%    11    2018  65.1%    67  
S Stephens   2011  59.7%    19    2015  65.0%    66

Kiki Bertens wasn’t quite as bad as Sakkari at her worst, but she wasn’t getting much benefit from her first serve. Like the Greek, she had back-to-back seasons below 60%, but unlike Sakkari, her improvement was instant. She leapt from sub-60% in 2015 to almost 68% (86th percentile) a year later. You won’t be surprised to hear that her ranking catapulted upwards as well, from 104th at the end of 2015 to 22nd a year later.

Kiki’s several years since also bode well for Sakkari. Her first-serve winning percentage of 67.4% last year was her worst since crossing the 60% barrier. A slightly less optimistic story comes from Simona Halep, whose 78th percentile mark in 2014 remains her career best. Coming from such an abysmal starting point, it’s remarkable that Halep has improved as much as she has, but she remains firmly in the range of good-but-not-great in this dimension of her game.

Steady improvements

There’s no particular advantage to spreading out one’s gains over a half-decade, like Sakkari has. If she had been given the option of picking up eight percentage points in a single year, like Bertens did, she would’ve taken it.

Still, the fact that the Greek keeps marching upwards is what makes her ascent so fascinating to me. In the decade-plus of data available, no other woman has improved her first-serve win percentage for five years running. Only two players–Yulia Putintseva and Saisai Zheng–have enjoyed positive bumps for four consecutive seasons, and neither situation really compares. Zheng’s improvement took her from 53.2% in 2015 to 59.3% in 2019, and Putintseva rose from 57.9% in 2017 to 62.4% so far this year. While both are making the most of what they have, neither has fundamentally transformed the type of threat they bring on court the way that Sakkari has.

In search of a better comparison–any comparison–with this five-year streak of gains, I turned to the more extensive set of ATP match stats, which go back to 1991. In those three decades, I found exactly 10 players who improved in this department for five (or more) consecutive years. It’s a decidedly diverse group, with a few names you might recognize:

Player            Streak  Start %ile  End %ile  
Renzo Furlan           6           2        73  
Slava Dosedel          6           2        16  
Julien Benneteau       5          16        55  
Arnaud Clement         6          18        70  
Michael Chang          5          18        92  
Roger Federer          5          47        94  
Thomas Enqvist         5          58        94  
Boris Becker           6          79        99  
John Isner             7          82        98  
Marc Rosset            5          87        98

The starting and ending percentiles indicate that this list includes players who began bad and ended a bit less bad, servebots who started great and eked even more out of their biggest weapon, and then a handful of Sakkari-esque figures who steadily went from considerably below average to far above it.

Michael Chang is the closest parallel of the group, even if we don’t have complete match stats for the first few years of his career. In 1991 he was one of the best returners in the game, but winning barely two thirds of his first serve points wasn’t enough to keep him in the top ten in an offense-dominated era. Five years later he was winning 77% of his first deliveries and ended the season at his peak ranking of #2. He couldn’t sustain the elite-level serving stats, but he did have a few more above-average years.

And then there’s Roger Federer. I’ll leave it to Sakkari fans to work out whether his presence on this list can tell us anything about her future.

Ave Maria

This is all just a long way of saying “wow!” There are other aspects of Sakkari’s game that she has improved, though none so consistently and dramatically. Once you start looking at year-to-year trends for individual stats, future projects start to multiply: identifying peak ages for different parts of the game, determining which stats are more or less likely to regress to the mean, finding which ones best predict ranking climbs, and so on.

We’ll get to some of those answers eventually. In the meantime, I’ll be watching Sakkari with new, better-informed eyes.

Jannik Sinner’s Missing First Serve Points

In Sunday’s Miami Open final, Jannik Sinner posted some very odd stats in his straight-set loss to Hubert Hurkacz. He won a respectable 48.4% of his second serve points–three points behind the the ATP top 50’s average since the restart–but only 55.3% of his first serve points. First serve points are the bread and butter of the offensive game, and Sinner got only as much out of that as Casper Ruud derives from his second serve.

It’s not that Hurkacz has magical anti-first-serve powers, either–it was only the second time since the restart that he won more than 40% of first-serve return points. He barely won 30% against Denis Kudla in the Miami first round.

Sinner’s first serve is not typically so ineffectual, but that isn’t to say it’s particularly good. While the tour wins well over 70% of its first-serve points, the Italian won only 63.5% in the quarter-finals against Alexander Bublik (another man who would never be confused with Andre Agassi), and 64.6% in his semi-final match with Roberto Bautista Agut. In both of those contests, he held on to 57% of his second serves–an outstanding mark for a player’s weaker offering.

I keep returning to second-serve points won and the difference between firsts and seconds to emphasize that Sinner is doing a lot of things right. Winning so many second-serve points suggests that he understands the tactics that go into playing service points when the ball comes back. Yet he hardly reaps any extra benefits from landing his first serve.

If it looks like a clay-court specialist…

I calculated the difference between first-serve and second-serve points won–let’s call it WinDiff–for every men’s tour-level player-season between 2000 and 2021 with at least 15 completed matches. That gives us almost 2,500 data points. At one extreme is 2019 Sam Querrey, who won over 80% of his first serve points but only 47% of his seconds, for a WinDiff of 33.2 percentage points. At the other end is Juan Carlos Ferrero 2011 campaign, when he won 65.5% of his firsts and 57.0% of his seconds, for an 8.5-point WinDiff.

Querrey’s season was mediocre and Ferrero’s was pretty good, suggesting that there’s a sweet spot somewhere in the middle. Yet it’s possible to have outstanding seasons near either end of the spectrum. Last year, Alexander Zverev’s WinDiff was 32 (77%/45%), and he won 28 of 39 matches. And in 2008, a young Rafael Nadal had a WinDiff of 11.5 (71.9%/60.4%), which was good enough to give him his first year-end #1 ranking.

Finding Ferrero and Nadal in Sinner’s neighborhood starts to give us an idea of what kind of players have low WinDiffs. Out of 2,460 player-seasons, only 33 had smaller WinDiff’s than Sinner’s 11.4 percentage points for 2021 so far, and you might be able to identify a few common traits among the players who posted narrower gaps:

Yoshihito Nishioka, Juan Monaco, Filippo Volandri, Potito Starace, Flavio Cipolla, Albert Montanes, Pablo Cuevas, Diego Schwartzman, Damir Dzumhur…

Clay courters, short guys, Italians… you get the idea. Ferrero and Nadal offer profitable career paths for Sinner, but I’m not sure that “be like Rafa” is practical advice for anyone, no matter how talented.

Room for improvement?

When I mentioned the extreme stat from Sunday’s final in my Expected Points podcast yesterday, I concluded on an optimistic note. Sinner is 19, he just reached a Masters final, he’ll continue to work on his first serve, and as we’ve seen, the rest of his game is already top-notch.

But does the data bear out such a rosy outlook? Are there players who have emerged from the purgatory of a low WinDiff to get more out of their first serves?

The average WinDiff of the top 50 since the restart is about 21.5 points. The bad news is that only a few low-WinDiff players eventually reach that level. The good news is that a disproportionately weak first serve is apparently correctable, or–at least–the stat is noisy enough that some players regress toward the mean.

Going back to my set of 2,460 player-seasons, the 5th percentile was a WinDiff of about 14 points. 71 different players had at least one season below that threshold, and 20 of those guys have played at least 10 full seasons since 2000. Drawing the line at a decade’s worth of play is some serious selection bias, but if Sinner doesn’t stick around for another 7.5 seasons of 15 or more matches, that’s probably a sign of something else gone very wrong.

The following table shows those 20 players. For each, I’ve shown their highest single-season WinDiff since 2000 and the average across their 21st-century career. Remember that tour average is a bit above 20 points, and Sinner’s 2021 so far sits at 11.4.

Player                 Seasons MaxWD  AvgWD  
Juan Martin Del Potro       10  24.8   21.2   
Pablo Cuevas                11  22.5   20.0   
Fernando Verdasco           17  23.0   20.0   
Albert Montanes             15  24.1   19.5   
Philipp Kohlschreiber       16  23.9   18.2   
Juan Ignacio Chela          13  22.1   17.7   
Tommy Robredo               15  21.1   17.6   
Jarkko Nieminen             14  21.4   17.4   
David Nalbandian            12  22.2   17.1   
Fabrice Santoro             10  21.0   17.1   
Nikolay Davydenko           14  20.3   17.0   
Dudi Sela                   10  21.9   16.4   
Albert Ramos                10  19.6   16.3   
David Ferrer                17  19.2   16.2   
Juan Carlos Ferrero         13  18.3   15.1   
Mikhail Kukushkin           10  18.0   14.9   
Rafael Nadal                18  17.5   14.8   
Olivier Rochus              12  17.8   14.7   
Filippo Volandri            10  16.2   13.2   
Juan Monaco                 13  15.9   12.7

Juan Martin Del Potro offers the brightest path, if one can emulate the results without the injuries. His WinDiff as as 17-year-old tour newbie was roughly 13 points, but he quickly landed near tour average. Sinner isn’t nearly as tall, so a better comparison might be David Nalbandian, who didn’t win nearly as many first-serve points as his fellow Argentine, but held on to enough. It’s certainly easier to look at Sinner and imagine a Nalbandian-like future than it is a Monaco- or Volandri-like one.

Another reason for optimism is that Sinner himself has already posted a 21-point WinDiff season last year, and this year’s weirdness is in large part due to his improvement against second serves, not a drastic drop in first-serve effectiveness. Maintaining his 56.5% rate of winning second-serve points seems unlikely only because it is so good. If he can manage that, he can survive with a modest first delivery so long as it’s in his typical high-60s range instead of the mid-50s that proved his undoing against Hurkacz.

Finally, the clay-centricity of the list above might be reason to pause before pegging Sinner as an eventual #1. But it also suggests that the teenager is developing exactly the right kind of game to excel on dirt. For the next couple of months, Italian fans will have plenty to get excited about.

Hsieh, Errani, and a Match That Broke Everybody

In their third round match today at the Australian Open, Sara Errani and Su Wei Hsieh played 232 points. The fastest serve either one hit registered at 93 mph (149 kmh), Hsieh’s first serves averaged 85 mph, and Errani’s mean first serve speed was 75 mph. I use the word “mean” here as more than just a way to avoid saying “average” so many times.

The two veterans are crafty–dare I say tricky–players with an arsenal of weapons once the ball is in play. But the serve is mostly just a stumbling block to make the best of. Hsieh won 62 of her 115 return points, good for 54% of Errani’s serves. This is more impressive than it sounds–the Italian double faulted only four times today. It’s fairly common for a winner on the women’s tour to win more than half of her return points, but what makes this match so weird is that Errani did the same. She won 63 of her 117 return points, also a 54% clip.

About half of WTA losers fail to convert better than 50% of their service points. But only 2.4% of winners miss the mark. And there’s a huge gap between 50%–mediocre and survivable–and Hsieh’s 46%. A 46% rate of service points won translates to a 40% likelihood of holding. Coincidentally, that’s exactly what both players did, each hanging on to their service games in 6 of 15 tries.

I have the relevant stats for just under 25,000 tour-level, main draw women’s matches since 2010, and only about 80 winners–0.3%, or less than once per 300 contests–won service points at a lower clip than Hsieh did today.

** I say “about” because the stats I have from the early 2010s aren’t perfect. A match with 60% of return points won is a prime candidate to be a mistake. I checked these 80 for obvious errors, like matches with a small number of service breaks, but those numbers aren’t perfect either.

There’s no grand analytical insight to be gleaned from a match like this. It’s just a glorious oddity that reminds us how many different ways there are to win matches. (And to be honest, you only need to watch Hsieh for about 90 seconds to recognize that.) In that spirit, here’s some more trivia:

  • Since 2010, this is only the 12th Australian Open main draw match in which neither player won half of her service points.
  • The only AO match in which neither player won 46% of their service points was the 2018 third-rounder between Anett Kontaveit and Jelena Ostapenko. They both held about 45.5% of their points, and 68% of total games (17 of 25) were breaks.
  • There have been about 400 tour-level matches since 2010 in which neither player wins half of their service points. Before today, 21 of those involved Errani, and she won 17 of them.
  • The other players who have been involved in at least 12 such matches are Monica Niculescu (16), Alize Cornet (14), and Carla Suarez Navarro (13). Today was only Hsieh’s 5th appearance on the list.

Perhaps oddest of all, this the first time in four tries that Hsieh avoiding getting bageled by Errani. Last time they played, in Istanbul in 2017, the Italian won, 6-0 6-1, needing only 55 minutes and a total of 87 points. Errani was so on-form that day that she won a whopping 66% of her service points. Hsieh finally turned the tables, even if she still hasn’t figured out how to stop this dogged opponent from breaking her serve.