Match charting Archives - Page 2 of 10

Anna Kalinskaya At Her Peak

Also today: Upsets, (partly) explained; January 23, 1924

*Anna Kalinskaya in the 2020 Fed Cup qualifying round. Credit:* Nuță Lucian

Should we have seen this coming? Of all the surprises in the top half of the 2024 Australian Open women’s draw, Anna Kalinskaya’s run to the quarter-finals stands as one of the biggest. The 25-year-old was ranked 75th entering the tournament, and she had never reached the third round of a major in 13 previous main-draw attempts.

Had we looked closely before the tournament, we wouldn’t have found a title contender, exactly, but we would have identified Kalinskaya as about as dangerous as a 75th-ranked player could possibly be. She finished 2023 on a 9-1 run, reaching the final at the WTA 125 in Tampico, then winning the title at the Midland 125, where she knocked out the up-and-coming Alycia Parks in the semi-finals. 2024 started well, too: The Russian upset top-tenner Barbora Krejcikova in Adelaide, then almost knocked out Daria Kasatkina in a two hour, 51-minute match two days later.

The only reason her official ranking is so low is that she missed nearly four months last summer to a leg injury that she picked up in the third round in Rome. Her two match wins at the Foro Italico pushed her up to 53rd in the world, just short of her career-best 51st, set in 2022. The Elo algorithm, which measures the quality of her wins rather than the number of tournaments she was healthy enough to play, reflects both her pre-injury successes and the more recent hot streak. Kalinskaya came to Melbourne as the 31st-ranked woman on the Elo list.

These alternative rankings put a different spin on her path through the Australian Open draw so far. Here are the results from her first four rounds, in which she appeared to be the underdog three times:

Elo has some adjustments to make:

Round  Opponent  Elo Rk  Elo vRk  
R16    Paolini       31       37  
R32    Stephens      31       50  
R64    Rus           31      107  
R128   Volynets      31      139

Kalinskaya was hardly an early favorite–Stephens did her the favor of taking out Kasatkina, and Anna Blinkova (who lost to Paolini) eliminated the third-seeded Elena Rybakina. But given how the draw worked out, seeing the Russian’s name in the quarter-finals wasn’t so unlikely after all.

More luck

Kalinskaya has a dangerous forehand and a solid backhand, but she isn’t an aggressive player by the standards of today’s circuit. Her 14 matches logged by the Match Charting Project average 4.2 strokes per point, and that skews low because it includes three meetings with Aryna Sabalenka. Yesterday’s fourth-round match against Paolini took 5.3 strokes per point, and the third-rounder with Stephens was similar.

By Aggression Score, the 25-year-old rates modestly below average, at -17 in rallies and -15 on returns. While she doesn’t have any weaknesses that prevent her from ending points earlier, she’s more comfortable letting the rally develop. When Paolini played along, the results were remarkable: 32 points reached seven shots or more yesterday, and Kalinskaya didn’t end any of them with an unforced error.

The downside of such a game style is that a lot of opponents won’t be so cooperative. Last fall, the Russian lost back-to-back-to-back matches against Ekaterina Alexandrova, Viktoria Hruncakova, and Ashlyn Krueger, three women who opt for big swings and short points. By contrast, consider the Rally Aggression Scores of the quartet Kalinskaya has faced in Melbourne:

Round  Opponent  AggScore  
R16    Paolini         -5  
R32    Stephens       -16  
R64    Rus            -59  
R128   Volynets       -38

Paolini and Stephens have roughly similar profiles to Kalinskaya’s own; Rus and Volynets are even more conservative.

This isn’t just a convenient narrative: Kalinskaya really is better against more passive players. She has played 118 career tour-level matches against women with at least 20 matches in the charting database. Sort them by Rally Aggression Score and separate them into four equal bins, and the Russian’s preferences become clear:

AggScore Range  Match Win%  
57 to 175            35.7%  
0 to 56              46.4%  
-27 to -1            50.0%  
-137 to -27          59.4%

If the whole tour were as patient as she is, the Russian would already be a household name.

Alas, it’s rare to draw four straight players as conservative as the bunch Kalinskaya has faced in Melbourne. And having reached the quarter-finals, her luck has run out. Her next opponent is Qinwen Zheng, who has a career Aggression Score of 27 and upped that number in 2023. It could be worse–fellow quarter-finalists Sabalenka and Dayana Yastremska are triple-digit aggressors–but it is a different sort of challenge than she has faced at the tournament so far.

To win tomorrow, Kalinskaya will need to play as well as she has for the last few months, only a couple of shots earlier in the rally. Otherwise, Zheng will end points on her own terms, and thousands of potential new fans will be convinced that Kalinskaya really is just the 75th best player in the world.

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Why are upsets on the rise?

Only four seeds, and two of the top eight, survived to the Australian Open women’s quarter-finals. Many of the top seeds lost early. This feels like a trend, and it isn’t new.

One plausible explanation is that the field keeps getting stronger. Top-level players now develop all over the world, and coaching and training techniques continue to improve. There are few easy, guaranteed matches, even if Iga Swiatek and Aryna Sabalenka usually(!) make it look that way. I believe this is part of the story.

Another component, I suspect, is the shift in playing styles. I noted a couple of weeks ago when writing about Angelique Kerber is that WTA rally lengths have steadily declined in the last decade. In 2013, the typical point lasted 4.7 strokes; it’s now around 4.3. Shorter points are caused by more risk-taking. Risks don’t always work out, full-power shots go astray, and the better-on-paper player doesn’t always win.

In 2019, I tested a similar theory about men’s results. I split players in four quartiles based on Aggression Score and tallied the upset rate for every pair of player types. When two very aggressive players met, nearly 39% of matches resulted in upsets, compared to 25% when two very passive players met. The true gap isn’t quite that big: given the specific players involved, there should have been a few more upsets among the very aggressive group. But even after adjusting for that, it remained a substantial gap.

It stands to reason that the story would be the same for women. Instead of Aggression Score, I used average rally length. I doubt there’s much difference. I didn’t intend to change gears, I just got halfway through the project before checking what I did the first time.

The most aggressive quartile (1, in the table below) are players who average 3.6 shots per rally or less. The next group (2) ranges from 3.7 to 4.0, then (3) from 4.1 to 4.5, and finally (4) 4.6 strokes and up. The following table shows the frequency of upsets (Upset%) and how the upset rate compares to expectations (U/Exp) for each pair of groups:

Q1  Q2  Upset%  U/Exp  
1   1    40.7%   1.07  
2   1    36.2%   0.99  
2   2    35.7%   0.99  
3   1    35.1%   0.93  
3   2    35.5%   0.97  
3   3    40.9%   1.07  
4   1    37.6%   1.03  
4   2    36.6%   1.02  
4   3    34.6%   0.95  
4   4    34.7%   0.97

(If you look back to the 2019 study, you’ll notice that I did almost everything “backwards” this time — swapping 1 for 4 as the label for the most aggressive group, and calculating results as favorite winning percentages instead of upsets. Sorry about that.)

Matches between very aggressive players do, in fact, result in more upsets than expected. It’s not an overwhelming result, partly because it’s only 7% more than expected, and partly because matches between third-quartile players–those with average rally lengths between 4.1 and 4.5–are just as unexpectedly unpredictable.

I don’t know what to make of the latter finding. I can’t think of any reasonable cause for that other than chance, which casts some doubt on the top-line result as well.

If the upset rate for matches between very aggressive players is a persistent effect, it would give us more upsets on tour today than we saw a decade ago. An increasing number of players fit the hyper-aggressive mold, so there are more matchups between them. The logic seems sound to me, though it may be the case that other sources of player inconsistency outweigh a woman’s particular risk profile.

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January 23, 1924: Debuts and dropshots

Men’s tennis ruled at the early Australian Championships. The tournament had been held since 1905 (as the “Australasian” Championships), but there was no women’s singles until 1922. On January 23rd, midway through the 1924 edition, the press corps was preoccupied with the severity of Gerald Patterson’s sprained ankle and the question of whether Ian McInnes had been practicing.

James O. Anderson, the 1922 singles champion who would win the 1924 edition as well, introduced what was then–at least to the Melbourne Argus–an on-court novelty:

He has developed a new stroke since he last played in Melbourne, and it has proved successful. On the back of the court he makes a pretence of sending in a hard drive, but with a delicate flick of the wrist he drops the ball just over the net, leaving his opponent helpless 30 feet away.

A veritable proto-Alcaraz, was James O.

For the few fans who weren’t solely focused on Australia’s Davis Cuppers, a superstar was emerging before their eyes. Also on the 23rd, 20-year-old Daphne Akhurst made quick work of Violet Mather, advancing to the semi-finals in her first appearance at the Championships.

Akhurst wouldn’t go any further, unable to withstand the heavy forehand of Esna Boyd in the next round. But it was nonetheless a remarkable debut: She won both the women’s and the mixed doubles titles. The correspondent for the Melbourne Age, recapping the mixed final, could hardly contain his admiration:

Miss Akhurst–an artist to her finger tips–belied her delicate mid-Victorian appearance that suggested that she had slipped out of one of Jane Austen’s books by sifting out cayenne pepper strokes from a never-failing supply.

Daphne and Jack Willard–“who ran for every ball, and continued running after he played the ball”–defeated Boyd and Gar Hone in straight sets.

The pair of championships was a harbinger of things to come. Between 1925 and 1931, Akhurst would win five singles titles (losing only in 1927 when she withdrew), four more in the women’s doubles, and another three mixed. The only thing that could stop her were the customs of the day: She married in 1930 and retired a year later. Tragically, she died from pregnancy complications in 1933, at the age of 29.

Daphne is best known these days as the name on the Australian Open women’s singles trophy. For the next several years, there will be many more Akhurst centennials to celebrate.

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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.

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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.

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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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Can Lorenzo Sonego Hunt Down Enough Forehands?

*Lorenzo Sonego at Monte Carlo in 2022. Credit: si.robi*

This year, Australian Open broadcasts threw a screwball into their traditional post-match statsheet. In the addition to the usual numbers–winners, unforced errors, break points won, and so forth–the graphic shows something called “Hunting 3rd Shot Forehand.” I must have missed a memo. This is the first I’ve heard of such a thing.

A puff piece for the Tennis Australia data group offers something of a definition. The new stat measures “the times the server forehands their first post-serve hit, indicating their desire to dictate the point.” Um, ok. In other words, when the service return comes back, how often does the server hit a forehand with his next shot?

The intention behind the metric is straightforward. You hear a lot these days about the “plus-one”–the server’s second shot. While the serve is the most important stroke in tennis, the plus-one shot is the next-most crucial opportunity to attack. Both because it arises often, and because it offers a chance to define the direction of the rally, even if it’s not yet possible to put the ball away.

It is easier to dictate play with a forehand than a backhand; the potential trajectories of the stroke give a player more options. Beyond that, most men have better forehands than backhands. (The stat appears on broadcasts for both men’s and women’s matches, but today I’m going to talk about the men’s game.) If the goal is to command the rally with the plus-one shot, it’s better to hit a forehand than a backhand. A higher “Hunting 3rd Shot Forehand” number, then, is better.

*The post-match graphic, with new stat second from the bottom*

Before we go further: I simply can’t use this name. It’s long and confusing. (Is the player hunting for the forehand? For a winner? For a silly rabbit?) I’m going to call it “3rd Shot FH%” or “3F%” for short.

(And yes, I promise to get to Sonego eventually.)

The stat is not as straightforward as the intention behind it. The implication of 3F%, I think, is something like, “How hard did the player try to hit plus-one forehands?” A possible further implication is, “How well did the returner prevent his opponent from hitting plus-one forehands?” The second question prompts yet another: “How well did the server keep the returner from sending balls to his backhand?”

It may be possible to separate some of those questions, but there’s a lot more spadework to do before we get there.

What is normal?

(You might doubt whether I am well-situated to answer. Still, we soldier on.)

Your TV screen shows you some “Hunting 3rd Shot Forehand” numbers. Are they good?

The 3F% metric can be calculated from Match Charting Project data, so we have thousands of data points to draw upon. Based on men’s matches since 2014, the average 3F% is 64.7%. The middle third of player-matches falls between 59.3% and 70.9%. Take a little liberty with rounding, and we can say that “normal” is the range from 60% to 70%. Less than 60%, and you’re doing something wrong–or you’d rather hit your backhand, or your opponent had a day. More than 70%, and you were really getting things done in the plus-one department.

Some players consistently land at the far ends of the distribution. Here are career numbers for the top ten active players by this metric, along with 15 more names of interest:

Player                3F%  
Lorenzo Sonego      78.6%  
Rafael Nadal        77.7%  
Joao Sousa          77.6%  
Denis Shapovalov    77.1%  
Albert Ramos        76.0%  
Jeremy Chardy       75.7%  
Milos Raonic        74.6%  
Stefanos Tsitsipas  74.4%  
Casper Ruud         73.9%  
Grigor Dimitrov     73.9%  
* * * * * * * * * * * * *                    
Holger Rune         69.7%  
Dominic Thiem       69.3%  
Hubert Hurkacz      67.5%  
Carlos Alcaraz      67.2%  
Andrey Rublev       64.7%  
Jannik Sinner       62.6%  
Alex de Minaur      61.2%  
Stan Wawrinka       60.9%  
Andy Murray         60.0%  
Taylor Fritz        58.3%  
Diego Schwartzman   56.9%  
Novak Djokovic      56.2%  
Frances Tiafoe      55.8%  
Alexander Zverev    51.1%  
Daniil Medvedev     50.0%

There’s Lorenzo!

The top of the list gives you an idea of what sorts of game styles result in lots of plus-one forehands. Big serves help. Left-handedness works in your favor, perhaps since everyone trains so hard to return to a right-hander’s backhand side. Some clay-courters do well, as they are less likely to think of the serve as a point-ending shot on its own, focusing instead on how it can set up the point.

It also helps to try to hit plus-one forehands. Neither Zverev nor Medvedev seem to think in those terms, so their low 3F% ratings don’t reflect any lack of execution.

Does this even matter?

Some valuable on-screen real estate–and an enormous amount of coaching time–would be wasted if 3F% didn’t correlate with points won. Fortunately for the conventional wisdom, it does: A plus-one forehand is more likely to lead to a point for the server than a plus-one backhand is.

57.5% of plus-one forehands eventually turn into a point won, compared to 50.9% of plus-one backhands. That’s a ratio of 1.13, a number that will be more useful as a reference point in a moment.

The value of a plus-one forehand depends on the player. Matteo Berrettini wins 58.5% of plus-one forehand points but only 44.6% of plus-one backhands. That’s a ratio of 1.31, one of the highest of any active player. For him, 3F% certainly matters: All else equal, more plus-one forehand points leads to better results overall.

(A word of caution, though: The marginal plus-one forehand point–that is, the next return that he might have ran around to hit a forehand, but didn’t–might not have improved his results for the better. Presumably Matteo knows his own capabilities, and he hits forehands only on those points where they improve his odds of winning. The marginal plus-one forehand, for a player like him, is a fairly desperate foray into the doubles alley.)

For others, the plus-one choice barely registers. Zverev wins 56.7% of plus-one forehands and 52.8% of backhands, a ratio of 1.07. Every other top-tenner has a wider split, but there are more extreme examples. Adrian Mannarino wins more points behind his plus-one backhand than forehand, 55.4% to 52.3%.

Sonego, our 3F% champion, gains nearly as much from his plus-one forehands as Berrettini does. He wins 57.1% of plus-one forehand points, against 44.4% for backhands. It isn’t easy to find his backhand, but it’s worth the attempt.

What about first and second serves?

As far as I know, broadcasts don’t separate the “Hunting” metric into first and second serves. But they should! Early in the rally, the effect of the serve retains plenty of influence.

The following table shows some of the tour-wide averages I’ve discussed so far–3F%, plus-one forehand points won, and plus-one backhand points won–broken down into first-serve and second-serve points:

AVERAGES     3F%  FH W%  BH W%   
1st serve  71.1%  60.3%  53.9%  
2nd serve  55.2%  52.2%  48.1%
Total      64.7%  57.5%  50.9%

Bigger serves generate weaker (and less targeted) returns, which invite more forehands. Behind second serves, ATPers only manage to hit forehands on 55% of their plus-one shots. On the other hand, the gap in points won isn’t as wide.

A fascinating outlier is Andrey Rublev. He finds the forehand on over 80% of his first-serve points, one of the highest numbers on tour. Behind the second serve, though, he hits plus-one forehands only 43% of the time–one of the lowest! It’s no secret that his second serve is a liability, but such a gap still comes as a surprise.

Sonego is a more typical case: lots more plus-one forehands on the first serve than the second (83% to 71%), and a wide gap in the results between forehands and backhands regardless of which serve it supports.

Converting from the backhand corner

With a few exceptions like Mannarino, most players want to hit as many plus-one forehands as they plausibly can. If the return goes to their forehand corner, obviously they’ll hit a forehand. If the return comes back up the middle, it’s either a no-doubt forehand or an easy decision to take a couple of steps around the ball and avoid the backhand.

The real decisions happen when the return goes to the backhand corner. Now we’ve moved into true Match Charting Project territory. I don’t know if the Australian Open has the data to drill down this far; either way, it probably won’t show up on your TV screen. In this corner of the internet, though, we’ll dive in.

About one-quarter of in-play returns go to the server’s backhand corner. Ernests Gulbis set the standard for plus-one backhanding, running around just 2% of those balls. On average, players go for the forehand 26.6% of the time. Even Zverev and Medvedev go that route sometimes: 9% for the German and 8% for the Russian.

Here again, Sonego sets the standard. He runs around 49% of those returns, winning 53% of the resulting plus-one forehands versus 47% of the backhands he can’t avoid. No other active player creates so many forehand opportunities. Of retired players in the charting dataset, only Carlos Moya and Leonardo Mayer were more extreme.

Here’s the same tour-averages table as above, now limited to points with returns to the backhand corner:

BH CORNER    3F%  FH W%  BH W%  
1st serve  34.9%  61.3%  53.0%  
2nd serve  16.9%  52.3%  47.3% 
Total      26.6%  58.7%  50.0%

It’s possible that many players–though probably not Sonego–are leaving some points on the table here. I’m surprised to see that the gap in win percentages between plus-one forehands and backhand is bigger for backhand-corner returns than returns in general. Backhand-corner returns are somewhat similar to each other–certainly more similar than returns in general. Thus I would expect that players would find an equilibrium in which they ran around enough shots that their forehand and backhand winning percentages end up closer together. Perhaps some ATPers overestimate the quality of their backhands, or maybe they don’t want to look foolish taking a chance in the doubles alley. Or they might just know what they’re doing, and the guy typing on his laptop should shut up about it.

Hunting Alcaraz

Sonego beat Dan Evans in Melbourne yesterday, earning him a date on Thursday with second-seeded Carlos Alcaraz. While there’s more to the match than Sonego’s hunt to maximize his 3F%, the battle for the Italian’s plus-one court position will play a big part.

Alcaraz is a bit better than the typical tour player at landing his returns in the server’s backhand corner, something he does 30.8% of the time, compared to the norm of 27.0%. But it doesn’t make him particularly effective at avoiding his opponents’ plus-one forehand. They find the preferred shot 64.5% of the time, almost exactly tour average. The story is the same when we look at first and second serves separately: Carlitos neither prevents nor encourages plus-one forehands.

There are, naturally, returners who consistently limit plus-one options; others don’t have the skills to avert a barrage of forehands. Jenson Brooksby allows opponents plus-one forehands on just 57.7% of his returns; Andy Murray and (surprisingly?) Rublev keep opponents’ numbers down around 59%. At the other extreme, Cam Norrie allows servers to hit plus-one forehands almost three-quarters of the time. He’s one of many lefties who struggle by this metric: Since serve returns are disproportionately backhands themselves, left-handers must often go down the line to put a return in a right-hander’s backhand corner. Norrie finds that corner only one-fifth of the time.

Well-targeted returns are good; forcing servers to hit plus-one backhands pays dividends. Alcaraz, though, is proof that you can make your money on the fourth shot and beyond. Opponents hit plenty of plus-one forehands against him, yet no matter what they choose for the second shot, they struggle to win the point. First serves, second serves, plus-one forehands, plus-one backhands … Carlitos beats tour average by multiple percentage points in every category. This table shows the difference between how players fare against Alcaraz and the average level, in percentage points:

VS CARLOS  rel FH W%  rel BH W%    
1st serve      -6.9%      -2.5%  
2nd serve      -2.2%      -5.0% 
Total          -5.7%      -3.5%

In other words, a plus-one forehand is 5.7 percentage points less likely to turn out well against Alcaraz than it is against an average ATP player. That’s a hefty margin for something that accounts for nearly half of the typical player’s service points.

It’s fun to know that Sonego occupies the unique position that he does on tour, and it’s entertaining to see some of the far-fetched places from which he’ll smack an inside-out forehand. It might even be useful to see the Italian’s “Hunting” stat at the conclusion of tomorrow’s match.

Alas, “setting up the point” and “winning the point” are two different things. Sonego might hunt down enough forehands against Alcaraz to manage the first, but the second is a considerably bigger ask.

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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 Improbable Rise of Emma Navarro

Also today: New stat leaderboards

*Emma Navarro at the 2023 US Open. Credit: Hameltion*

When Emma Navarro beat Elise Mertens for her first WTA title in Hobart on Saturday, it was only part of a natural progression. For more than a year now, she has shown a knack for winning, regardless of level, surface, or just about anything else. While most fans still don’t know her name, she’s up to 26th in the official rankings and 22nd on the Elo list.

The former collegiate champion–winner of the national title as a Virginia Cavalier in 2021–started her 2023 campaign just inside the top 150. She arrived at the brink of the top 100 with back-to-back ITF titles on clay in April, then cracked the top 60 with a grass-court final in Ilkley. Her first top-ten win came in September on hard courts, against Maria Sakkari in San Diego, and after a busy fall that included another two ITF titles, she broke into the top 40. She’s 8-1 so far in 2024; the only blip is a loss to Coco Gauff.

Altogether, that’s 72 victories since the beginning of last year. Not many women can boast so much success at the W25 level or higher in that span:

Player                   2023-24 Wins  
Arina Rodionova                    79  
Iga Swiatek                        73  
Emma Navarro                       72  
Oceane Dodin                       64  
Jessica Pegula                     62  
Julia Riera                        59  
Aryna Sabalenka                    59  
Martina Capurro Taborda            59  
Yafan Wang                         58  
Carlota Martinez Cirez             57

The remarkable part of Navarro’s rise is not the sheer quantity of positive results; it’s that she rose through the rankings so fast at the age she did. She first cracked the top 100 last May just before her 22nd birthday–hardly old by any rational standards, but nearly geriatric on the youth-driven WTA tour. The 25 players standing in front of Navarro in this week’s rankings broke into the top 100, on average, before their 20th birthday: The median is Aryna Sabalenka’s arrival at 19 years, 5 months. Late developers like Jessica Pegula, Barbora Krejcikova, and Navarro are exceptions to a long-standing rule.

It’s not unusual for a player to finally achieve a double-digit ranking when they are 21 or older, but it’s rare for a future star to do so–and now that Navarro is a tour-level title-holder ensconced in the top 30, she deserves that label. Since 1990, there have been 207 players who finished their age-21 season ranked between 101 and 200 without a previous appearance in the top 100. Only 25 of them reached #100 at the end of the following year; Navarro was only the fourth to crack the top 50.

Of those 200-plus players, only 35 of them ever achieved a top-40 ranking. (A few more, including Katie Boulter and Katie Volynets, could still join the group.) On average, it took them 1437 days–just short of four years–to do so. Navarro needed only 315 days, the second-fastest in the last 30-plus years. Here are the players who made the fastest move from the end of their age-21 season to the top 40:

Player                 Age 21  top 40 debut  Days  
Elise Mertens            2016    2017-08-28   245  
Emma Navarro             2022    2023-11-06   315  
Veronika Kudermetova     2018    2019-11-11   315  
Kurumi Nara              2012    2014-06-09   525  
Jamie Hampton            2011    2013-06-24   546  
Casey Dellacqua          2006    2008-07-28   581  
Tathiana Garbin          1998    2000-09-25   637  
Liudmila Samsonova       2019    2021-11-01   672  
Bethanie Mattek Sands    2006    2008-11-03   679  
Anne Kremer              1996    1999-04-12   833  
Jil Teichmann            2018    2021-04-26   847  
Zi Yan                   2005    2008-05-05   861  
Paula Badosa             2018    2021-05-24   875  
Yone Kamio               1992    1995-06-12   896  
Alison Riske Amritraj    2011    2014-06-09   896  
Johanna Konta            2012    2016-02-01  1127

It’s possible that Navarro could have been ready for the big time earlier had she not spent two years playing college tennis. Her sub-100 ranking at the end of 2022 was partly due to a limited schedule, as she played only a handful of tournaments before leaving school after the spring semester that year. But she wasn’t playing top-100 tennis when she did step on court: Elo ratings respond much more quickly to quality results (and do not reward quantity for its own sake), and her ranking by that algorithm, 148th, was virtually identical to her place on the official list.

Whatever the benefits and (temporary) costs of her stay at the University of Virginia, Navarro seemed to learn from the step up in competition–and quickly. She lost her first 11 matches against the top 50; in the last four months, she has won 5 of 6.

What works

The most memorable victory so far was Saturday’s triumph over Mertens for a debut WTA title. It was a grind, taking two hours, 50 minutes, and spanning 14 breaks of serve en route to a 6-1, 4-6, 7-5 finish. There was little first-strike tennis on display, as the average point ran to 5.5 strokes. 69 points required seven shots or more, and 37 reached double digits.

The battle for openings worked to Navarro’s advantage. In a sample of eleven previous matches logged by the Match Charting Project, she struggled in longer rallies, winning just 46% of points that reached a seventh shot compared to 49% overall. On Saturday, she reversed that trend in a big way, out-point-constructing her veteran opponent and winning a whopping 59% of the longer points. Of 84 charted Mertens matches, it was only the eighth time that she played at least 20 long points and won so few of them. Among the few players to beat her so soundly on rally tactics: Pegula and Simona Halep.

While Navarro’s results have steadily improved, her game plan is still recognizable form her days as a college champion. After defeating Miami’s Estrela Perez-Somarriba for the 2021 NCAA title, she described her approach: “I was able to dictate with my forehand and finish a lot of points with my backhand.” In Hobart, her backhand continued to populate the highlight reel, with seven clean down-the-line winners. But it was the forehand that opened the court in the first place.

She played, essentially, a clay-court match, using the forehand to create opportunities for the next ball. She hit winners with 7% of her forehand groundstrokes, slightly below tour average. But when she was able to hit a forehand, she won the point 62% of the time, an outstanding figure for a close match. One point serves as an illustration of the rest: At 2-all, 15-all in the third set, Navarro converted a return point with a down-the-line backhand winner on the 14th shot of the rally. After a deep forehand return, Navarro was forced to hit two backhands. When she was finally able to deploy the forehand on the 8th shot, she stabilized the point by going down the middle. The 10th shot took advantage of a let cord with a heavy crosscourt forehand, a weapon that worked in her favor on Saturday more than two-thirds of the time. Her next forehand went the other direction, creating the space for–finally–a backhand out of the Belgian’s reach.

While not every point was quite so tactical, point construction always lurked. Mertens frequently attempted a pattern where she would go the same direction with two consecutive groundstrokes then, having wrong-footed Navarro with the second of them, go for a winner. The sequence doesn’t work against a big swinger because the points don’t last long enough. That wasn’t a problem against the American, but Navarro’s resourcefulness nullified the tactic nonetheless. Unlike many players her age, Navarro is able to use slices off both wings to neutralize points, and she often did so on the second shot of Mertens’s would-be pattern. The Hobart champion hit 40 slices over the course of the match, ultimately winning the point on 20 of them. For a defensive shot, rescuing 50% of those situations counts as a victory.

There is little in Navarro’s game that advertises her as a world-beater: The weapons I’ve described work best as part of a carefully-managed package. She may prove to be most dangerous on clay, where aggressive opponents will have a harder time keeping points short. She might also develop yet another level. Twelve months ago, only a reckless forecaster would have predicted she could rise so high, so quickly. We still haven’t seen her peak.

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Deep leaderboards

Among the cult favorites on the Tennis Abstract site are the tour leaderboard pages, which contain nearly 60 sortable stats for the top 50 players on each circuit. Many of those stats aren’t available anywhere else, including things like average opponent ranking and time per match. It’s also possible to filter the matches for each calculation to determine things like the best hold percentages on clay.

Last week I introduced three new pages that extend the same concept:

Here’s just one example of what’s possible, the best WTA players outside the top 50 by ace percentage:

These are a great way to identify standout skills of lesser-known players. All of the leaderboards update every Monday.

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Jelena Ostapenko In the Hands of Fate

Also today: Deciding tiebreaks, a MCP milestone, and assorted links.

*Jelena Ostapenko in 2023. Credit: Hameltion*

If you’ve ever spent five minutes watching Jelena Ostapenko play tennis, you know she’s as aggressive as it gets. She swings for the fences and sometimes knocks them over. Get her on a hot streak, and opponents can only hope its ends before the handshake. When she’s off her game, spectators in the first few rows duck for cover.

What you might not realize is just how aggressive she is. A few years ago I tuned Lowell West’s Aggression Score metric so that the numbers fell in a range between 0 and 100. In theory, 0 is maximally passive; 100 is go-for-broke, all the time. Ostapenko’s career Aggression Score in rallies is 175.

This sort of extreme style lends itself to all sorts of narratives. She can beat anybody, any time, as she showed when she won the 2017 French Open as an unseeded player, and again last year when she upset Iga Swiatek at the US Open–her fourth win in as many matches against the Pole. That makes her a perennial dark horse pick at majors. Even though she hasn’t reached a semi-final since 2018, neither Iga nor Coco Gauff–who exited the Australian Open after an Ostapenko barrage last year–would like her find her in their section.

(Sorry Iga: Guess who you might face in the quarters!)

Hyper-aggressive players also appear to be works in progress. Especially early in Ostapenko’s career, commentators would talk about her stratospheric potential if she could only improve her footwork, or play a bit more “within herself.” That is, not quite so many winners, not quite so soon, more point construction, fewer unforced errors. But players rarely change much, and as they age, they are more likely to become more aggressive, not less. The Latvian is now 26 years old, beginning her ninth year on tour. What you see is what you get.

What you get, it turns out, is a lot of close matches. Ostapenko played 30 three-setters last year, including four in a row to reach the Birmingham final and another four straight to start the US Open. Alona’s apotheosis came at Indian Wells, when she faced fellow super-aggressor Petra Kvitova in the third round. Both women tallied exactly 75 points; Kvitova won, 0-6, 6-0, 6-4. Tennis ball fuzz could be seen floating over the desert for days afterward.

That particular scoreline was an oddity, but the margin of victory was not. Ostapenko’s tight matches are not a result of streakiness, flightiness, or anything of the sort. They are an unavoidable function of her game style. It’s almost impossible to hit lots of winners without also committing piles of unforced errors. (We’ll come back to that.) When you do both in such numbers, you personally account for a substantial majority of point outcomes. The winners and errors (very approximately) balance each other out, and unless your opponent does something remarkable–or remarkably bad–with the limited influence you leave her, you end up winning about half the points played.

No one takes the racket out of an opponent’s hand like Ostapenko does. Once the return is in play, the Latvian ends nearly two-thirds of points herself, with a winner or unforced error, or by forcing an error. No one else comes close. Drawing on Match Charting Project data, I’ve listed the active players who end the most rallies:

Player                 RallyEnd%  
Jelena Ostapenko           65.9%  
Petra Kvitova              61.6%  
Madison Keys               60.8%  
Liudmila Samsonova         60.0%  
Camila Giorgi              59.7%  
Aryna Sabalenka            59.7%  
Veronika Kudermetova       57.5%  
Danielle Collins           57.5%  
Ekaterina Alexandrova      57.2%  
Ons Jabeur                 56.8%  
Peyton Stearns             56.5%  
Caroline Garcia            56.2%  
Naomi Osaka                56.2%  
Varvara Gracheva           55.0%  
Iga Swiatek                55.0%

Here’s another way to look at Alona’s extreme position on this list. The only other woman to grade out so far from 50% is Madison Brengle, who ends fewer than 34% of rallies. Ostapenko’s power turns the rest of the tour into Brengle.

Give and take

Ending even 57% of points on your own racket requires a lot of big swings. When you aim for a line, you might feel confidence about your chances, but you are taking a risk. A few players, like Swiatek, can generate winners without paying the unforced-error penalty, but that takes an unusual combination of patience and power that most players do not possess.

The 66% of points that Ostapenko ends on her own racket divides into roughly 37% winners (and forced errors) and 29% unforced errors. That’s worse than Aryna Sabalenka, who hits nearly as many winners with only a 23% error rate, but compared to the tour as a whole, the ratio is a solid one. For every unforced error she commits, she ends 1.25 points in her favor. Average among players represented in the Match Charting Project is 1.16, and the true mean is probably lower than that, since the MCP is more heavily weighted toward the best players.

The ratio varies among players, but there is a fairly strong relationship. Here are the winner/forced error and unforced error rates–each as a percentage of all points where the return came back in play–for 140 current and recent players:

The correlation between the two rates (r² = 0.3) would be even stronger if it weren’t for net-rushers like Tatjana Maria–and to some extent Leylah Fernandez–who force their passive opponents into more aggression than they would otherwise produce.

As Sabalenka shows, it’s possible to seize as many points as Ostapenko does without giving quite so many away, but even that may be a mirage: Sabalenka racks up winners behind an overpowering serve that the Latvian can’t match. If the plot above is any indication, it would be difficult to bring her error rate down without also sacrificing some winners, not to mention the élan that she has ridden to seven tour-level titles.

So we’re left with something of a paradox. A hyper-aggressive player has more control over her fate than her peers do, but that control comes at a cost of a towering error rate, which keeps matches close. One result is a week like this one in Adelaide, where Ostapenko has reached the final by slipping through perilously tight battles with Sorana Cirstea (51.7% of points won) and Caroline Garcia (50.2%). Both matches could’ve gone the other way, something that is true so often when the Latvian steps on court. My tactical advice for Daria Kasatkina in tomorrow’s final: Cross your fingers.

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Deciding-set tiebreak records

AbsurDB asks:

[A]m I right that Hurkacz’s 15 deciding sets going into tie-breaks in one calendar year is a historical record in ATP (10 such tie-breaks won is also probably a record?)?

Indeed, both are records. According to my data, the previous records came from Ivo Karlovic’s 2007 season, when he reached 11 deciding-set tiebreaks, winning eight of them. Here are all the player-seasons with nine or more.

Player              Season  Dec TB  Record  
Hubert Hurkacz        2023      15    10-5  
Ivo Karlovic          2007      11     8-3  
John Isner            2011      11     4-7  
John Isner            2018      11     6-5  
Ivo Karlovic          2014      10     7-3  
John Isner            2017      10     5-5  
Kevin Anderson        2018      10     6-4  
Mark Philippoussis    2000       9     5-4  
Marat Safin           2000       9     5-4  
Ivan Ljubicic         2002       9     2-7  
Ivan Ljubicic         2007       9     8-1  
Ivo Karlovic          2008       9     5-4  
Sam Querrey           2018       9     1-8  
Borna Coric           2019       9     6-3  
Hubert Hurkacz        2022       9     3-6

(Yes, I checked before 2000, as well, but no one reached nine until Philippousis did so that year. The first player-season with eight deciding-set tiebreaks was Tom Gullikson’s, in 1984.)

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MCP Milestones

Earlier this week, the Match Charting Project recorded its two-millionth point:

The milestone match was the Auckland second-rounder between Ben Shelton and Fabian Marozsan, which I charted as a warm-up for my article on Wednesday. We’re not resting on our laurels, of course: We’ve added another five matches (and 800 or so points) in the 48 hours since.

Also worth mentioning is another round number we reached in the offseason: 1,000 different ATP players. Apart from the name syou’d expect, it’s a healthy mix of lower-ranked active players and former tour regulars. #1,000 was Martin Jaite, via his 1987 Rome final against Mats Wilander. We’ve also now charted 800 different WTAers.

We stand about 200 charts away from 13,000 matches overall: approximately 7,000 men’s and 6,000 women’s. 2023 was our most productive year yet, and 2024 would be a great time to start contributing.

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Assorted links

Earlier this week I appeared on Alex Gruskin’s Mini-Break Podcast, in which he got overexcited about a number of week one trends, and I tried to talk him down from all the ledges.
I wrote about how GPT4 helped me make Tennis Abstract’s new navbar, because you had to know I didn’t do it myself.
The tours have introduced a new policy on late matches. I’m underwhelmed: There are an awful lot of exceptions, and there’s no acknowledgement of the underlying problem of longer and longer matches.
Two student projects worth a look: Pramukh’s Evaluating Tennis Player Styles in Relation to Tour Averages, based on MCP data, and Amrit’s Aces over Expected model.
If you can’t wait until Sunday for grand slam tennis, here’s the Clijsters-Henin 2003 US Open final.

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How Grigor Dimitrov Unbalanced Holger Rune in Brisbane

*Grigor Dimitrov. Credit: Bradley Kanaris / Getty*

Grigor Dimitrov was long known as “Baby Fed,” but yesterday, Holger Rune was the one trying to do a Roger Federer impression. Facing break point at 3-all in the second set, Rune kicked a second serve wide, got a cross-court slice reply, then ran around his backhand to smack an inside-in forehand: a high-risk, high-reward shot, especially if you aim for the line. Rune went big and he pulled it wide. That was the only break of the match.

The 20-year-old had already missed one of those in the same game: The first error dug him a 15-40 hole. Over the course of the match, he attempted seven inside-in forehands, a shot that usually wins him two out of three points. Against Dimitrov, he blew four of them.

The errors are a symptom of one of something separating Rune from the top of the game. In his eagerness to maintain an aggressive position at the baseline–a willingness that defines his style and, in fairness, often pays off–he tries a bit too hard. He swings to end points in three shots that probably need to go five. He keeps a toe on the baseline when he ought to be one step further back.

This isn’t a secret, and Dimitrov exploited it. The Bulgarian landed 82% of his returns behind the service line, compared to a tour average of 70%. 39% of Dimitrov’s returns fell in the back quarter of the court, beating the 28% that players typically face. In rallies, the veteran kept pummeling Rune’s feet, prioritizing depth over direction.

The strategy worked. Take the other pivotal juncture of the match, early in the first-set tiebreak. Serving at 0-1, Rune pushed Dimitrov off the court with an inside-out forehand, which came back as a deep slice. Nothing special, but as Rune stepped back to accommodate it, he hit an equally indifferent reply. Dimitrov came back with another middle-deep backhand and Rune hit the tape with as pedestrian an error as you’ll ever see. At 0-2, Rune’s plus-one forehand forced Dimitrov deep and set up the point for an easy finish–or so he thought. Dimitrov managed to get his defensive forehand deep enough that Rune stepped in–his back foot on the baseline–and the result was another miss that would leave a club player berating himself.

On both points, a slightly more conservative court position, or a better last-minute adjustment step, would have let Rune continue the rally with his opponent on the run. Most players tread more carefully in tiebreaks. Instead, he missed twice and fell to 0-3. He got one point back but couldn’t close the entire gap and lost the first set, 7-6(5).

Middle-deep mediocrity

Yesterday wasn’t the first time that Rune misreads a neutral opportunity as a chance to go big. His own-the-baseline strategy is a mixed bag, the best example of which is how he responds to service returns that land at his feet. The Match Charting Project codes every return by direction (cross-court, middle, or down-the-line) and by depth (shallow–in front of the service line, deep–behind it, or very deep–in the back quarter of the court). Dimitrov placed 13 of his returns in the middle-deep region, and Rune saved just 5 of those points.

When a return lands middle-deep, the point is fully up for grabs. Counting both first- and second-serve points, the server wins roughly 49% of the time from that position. (Once a deep return is in play, any lingering effect of a big serve is mostly erased.) A top player should do better, but Rune does not. Here are the career outcomes of those points for the current ATP top four, plus the two Brisbane finalists:

Player             W/FE%   UFE%  PtsWon%  
Novak Djokovic      6.8%   7.1%    53.8%  
Jannik Sinner       5.7%   6.0%    51.6%  
Daniil Medvedev     5.3%   5.9%    50.6%  
Carlos Alcaraz      8.0%   6.2%    50.1%  
Grigor Dimitrov     9.6%   7.9%    49.6%  
--Average--         7.4%   8.7%    48.9%  
Holger Rune        11.5%  10.9%    48.0%

Rune is much more aggressive than his peers in these situations. It may feel like it pays off, since he ends more points with winners (or forced errors) than unforced errors. But the bottom line tells another story: He wins fewer points than average, and trails the best players in the game by a sizeable margin. As Djokovic, Sinner, and Medvedev can tell you, from a neutral position, immediate outcomes don’t matter as much as point construction.

It’s the same story later in the rally. Dimitrov won those two crucial tiebreak points by putting his second shot near the baseline. The serve return isn’t unique: Any stroke that lands in the middle-deep region turns the point into a 50-50 proposition. The above table showed how players fare from that position on the plus-one shot. Here are the numbers for everything after that:

Player           Winner%   UFE%  PtsWon%  
Carlos Alcaraz      8.2%  12.8%    55.3%  
Grigor Dimitrov     6.6%   6.3%    54.7%  
Novak Djokovic      6.2%   8.0%    54.6%  
Jannik Sinner       7.2%  10.5%    52.3%  
Daniil Medvedev     4.7%   6.8%    52.0%  
--Average--         7.1%  10.2%    49.3%  
Holger Rune         9.4%   9.7%    49.0%

The order changes, and Rune’s aggression doesn’t stand out like it does earlier in the rally. But the message is the same, only with a wider margin. Given the mix of players represented in the Match Charting Project, “average” is better than tour average, but it’s still a number Rune needs to surpass.

The second table, finally, brings us back to Dimitrov. If he hadn’t played yesterday, I wouldn’t have thought to include him on the list with the top four, but in this type of situation–one that demands both patience and tactical soundness–he rates with the best in the game.

Faced with an over-aggressive, slightly erratic opponent, the 32-year-old took advantage and turned in a workmanlike performance. That isn’t a dig: Dimitrov didn’t need fireworks, just steadiness. By my count, he racked up just 10 unforced errors to Rune’s 29, and just one of them–serving for 4-0 in the tiebreak–came a critical moment. It’s nothing so flashy as the “Baby Fed” moniker once promised, but Dimitrov’s mature game has gotten him up to 7th place on the Elo list, and a return to the official top ten is not far away.

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Angelique Kerber in the New World

*Angelique Kerber in 2020. Credit: Rob Keating*

Angelique Kerber’s return to the tour has, so far, been a rocky one. She began Germany’s United Cup campaign with a narrow defeat to Jasmine Paolini, in which the Italian earned 21 break points against the German’s serve. Kerber took a set from the free-swinging Caroline Garcia but lost in three. Today, Maria Sakkari blew her off the court, winning nine games in a row before Kerber got on the board and split the remaining six.

The United Cup, in its new design, is not an easy place to make a comeback: The German faced top-30 players all three rounds. (Compare that to the tour event in Brisbane, where fellow returnee Naomi Osaka scored an opening-round victory against a player ranked 83rd.) Kerber surely didn’t expect to dominate immediately. It’s hard to get rolling again after an 18-month layoff, and she hasn’t been a truly elite player since early 2019. She turns 36 years old this month, a tough age even for players with three majors to their credit.

The Garcia match, in particular, highlighted another dimension of the challenge. The tour that Kerber rejoins is different from the one where she collected so many laurels. Angie is the very definition of a counterpuncher, a clever defender who uses anticipation and racket control to convert her opponent’s pace into winners of her own. It’s tough to counterpunch against someone like Garcia, who aims to end the point with nearly every shot.

The reckless Frenchwoman is hardly alone. Based on data from the Match Charting Project, here is the average rally length on the WTA tour since 2013:

It looks a bit fluky, but it’s noteworthy to find a peak in 2016, Kerber’s best year. Rally length has been essentially flat since 2021, perhaps since 2019 if we set aside the Covid-affected 2020 season. The German is plenty familiar with the landscape, having competed on tour until Wimbledon in 2022, but she developed her game back when the power of Serena Williams was an outlier. Now, Serena’s late-career bashing is the model for a new generation.

There are a number of ways to illustrate the trend. While the year-to-year differences are minor, the arrows all point in the same direction. In 2016, 49.6% of points were decided in three shots or less. Last year, it was 53.0%. (In 2021 and 2022, it was a bit higher still.) At Kerber’s peak, nearly 24% of points lasted at least seven strokes. Last year that figure had declined to 20.8%.

This is probably worse news for someone like Caroline Wozniacki than it is for Kerber. Woz keeps points alive and waits for errors, skills that Garcia (or Aryna Sabalenka, or Elena Rybakina, or dozens more players she might draw in the first round of the Australian Open) render meaningless. While Angie isn’t going to pile up aces–she’s hit a grand total of two in three United Cup matches–she is fully capable of redirecting a serve for a return winner, as she did a couple of times against Sakkari. Still, the shorter the point, the less likely that Kerber finds an opportunity to work her magic.

Throughout her career, the German lefty has rarely had a problem picking spots to end points with winners or forced errors. Match Charting data shows that 6% of her groundstrokes go for winners, right in line with tour average.

The catch, though, is when she hits them. Kerber is one of 58 players for whom the Match Charting Project has recorded at least 2,000 winners and forced errors since 2013. Only four of those players unleash their winners later in the rally. The average shot number of Kerber’s point-enders is 4.9–bad news in an era when nearly two-thirds of points are finished in four shots or less.

Here are the twelve players in the dataset whose winners occur latest in the rally:

Player                Avg Winner Shot#  
Daria Kasatkina                    5.1  
Viktorija Golubic                  5.0  
Yulia Putintseva                   5.0  
Carla Suarez Navarro               4.9  
Angelique Kerber                   4.9  
Sloane Stephens                    4.9  
Agnieszka Radwanska                4.9  
Simona Halep                       4.8  
Svetlana Kuznetsova                4.7  
Anastasija Sevastova               4.6  
Caroline Wozniacki                 4.6  
Su Wei Hsieh                       4.6

This isn’t a table where you want to find your name north of Wozniacki’s. It’s possible to survive on today’s tour playing this way, as Daria Kasatkina has proven, but it is much less likely to translate into a major title. Wimbledon champ Marketa Vondrousova didn’t miss the list by much, coming in at 4.4, but her aggression varies wildly from one match to another. Iga Swiatek and Coco Gauff appear closer to the middle of the pack, at 4.2, and Aryna Sabalenka ranks as the fourth most aggressive of the 58, at 3.4.

At the risk of belaboring the point, here’s another way of seeing the difference between Angie’s style and the brands of tennis that currently top the rankings. The following chart shows what percent of Kerber’s winners (and forced errors) happen at each point in the rally, compared to the same figures for Swiatek and Sabalenka:

The “1st shot” and “6th+” columns are virtual mirror images of each other. Even that understates the difference between the veteran and the two youngsters, because a point-ending serve from Kerber is more likely to be at least partially the fault of the returner–those errors are conventionally scored as forced regardless of the strength of the serve.

I don’t want to say that Kerber can’t succeed on her return to the circuit, but it’s clear that she faces a challenge. The tennis world of the mid-2010s is long gone, and even if she regains the form that took her to number one in 2016, it may not give her the same results in 2024. A new era requires a new Angie; we’ll see if she can produce one.

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How Coco Gauff’s Defense Won the US Open Final

Defense, as they say, wins championships. Coco Gauff has a big serve, a strong backhand, and a high tennis IQ, not to mention a new guru in Brad Gilbert. All of that got her to the US Open final and gave her a shot against new No. 1 Aryna Sablenka. But defense was what won her the match.

If you watched the final, you already know this. Over and over again, Gauff rescued a sure winner, hanging in the point long enough for Sabalenka to miss. In a close contest, as this one was, a handful of points can determine the result.

It’s tough to say exactly how many points Gauff saved with her exemplary defense. Sometimes she made multiple digs in the same point; other times she averted disaster just to lose the point a couple of strokes later. Still, we should try to quantify the effect she had on the normally imperious Sabalenka game.

My stat of choice is something I’m going to call, simply, Defense. For any match with charting-based stats, it’s a simple calculation: The percentage of the opponent’s groundstrokes that resulted in winners or forced errors. (I introduced it in my Andy Murray essay as part of the Tennis 128 project last year.) In other words: How often does the player get herself in a position to put a groundstroke back in play?

Among tour regulars on hard and grass courts, the range of the Defense stat runs from about 7%–the backboards that are Lesia Tsurenko and Sloane Stephens–to 15%, where you’ll find the less nimble Evgeniya Rodina and Linda Noskova. Lower is better! Tour average is around 11%. Gauff, over the course of her young career, has averaged 10.8%.

Average doesn’t carry much weight, though, when it comes to Sabalenka. Aryna’s groundstrokes end the point in her favor–with a winner or forced error–17.3% of the time. Only Jelena Ostapenko, at 18.0%, scores higher, and just a few other women are as high as 15%. Turning in an “average” performance against Sabalenka–that is, keeping her to 11%–is a massive step toward victory.

On Saturday, Gauff held her to 9.8%.

Sabalenka hit 285 groundstrokes in the final. 15 went for winners; another 13 turned into forced errors. Had she converted at her usual rate, those numbers would’ve been nearly twice as high: 49 points won off the ground instead of 28.

Gauff’s actual margin of victory was a mere seven points. By the Defense measure, she saved 21 solely with her superlative handling of Aryna’s groundstrokes. Again, it doesn’t quite work that way; she dug out multiple would-be winners on some points, for instance. On the other hand, it isn’t the only way Coco salvaged desperate situations. This measure doesn’t take into account quick-footed service returns or defense against the smash.

It’s almost impossible to overemphasize the magnitude of Gauff’s achievement. In 48 hard and grass court matches since last year’s US Open, just two of Sabalenka’s opponents managed a Defense stat better than 11.6%. The only other exception was Veronika Kudermetova, against Aryna’s limp performance in Berlin. Sabalenka’s average over the last 52 weeks is 19.7%, probably one of the highest marks posted by any baseliner, ever.

Gauff simply cut it in half. She effectively turned one of the most imposing players in women’s tennis history into a frustrated journeywoman–or at least the statistical equivalent of one. Gilbert might call it Winning Ugly, but it looked awfully good to me.

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10,000 Charted Matches

The Tennis 128 will return tomorrow with player #89.

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I introduced the Match Charting Project to the world in November 2013. I had no idea whether it would ever draw the interest of anyone outside of a tiny group of tennis-obsessed friends. I was okay with that. The project was designed to be valuable even if we only ended up charting a few matches.

Eight and a half years later, that group of tennis obsessives has grown. Over 140 of you have learned my detailed charting notation and worked through an entire match. A dozen of you have logged every shot of 100 matches or more. One indefatigable contributor, Edo, is now over 1,300 matches. Another super-charter, Zindaras, is also closing in on four digits.

Yesterday, another all-star contributor, Ludo, sent in charts of two John Isner matches. They were the 9,999th and 10,000th charts for the project. We’ve logged six million shots, over one and a half million points, and yes, ten thousand matches. The 10,001st chart appeared in my inbox as I was writing this post.

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Ten thousand matches is hardly a complete record of professional tennis, but it gives us a remarkably detailed view of both the men’s and women’s game.

In the last few years, we’ve come close to finishing many ongoing sub-projects. We have a chart for every grand slam final back to 1980, and many from the 1970s. We have most grand slam semi-finals back to the mid-1980s. We have nearly every Masters 1000 final back to 1990, when the Masters series began, and we have most Masters semi-finals in that span as well.

We’ve charted every match between members of the Big Four. We have almost every tour-level final ever played by the Big Four. We’ve collected charts of the major WTA events back to the 1990s, and we’ve racked up dozens of Evert-Navratilova matches before that. More recently, we’ve charted every single tour-level final (and a fair number of challengers and ITFs) from the last several years.

We have a shot-by-shot log of nearly every point Simona Halep has played back to the birth of the project, and near-complete sets of Aryna Sabalenka and Bianca Andreescu matches. We have charts of 543 Roger Federer matches, and over 400 each for Novak Djokovic and Rafael Nadal. We’ve charted at least ten matches for most players who have reached the men’s or women’s top 50 in recent memory. We have one hundred matches or more for 34 different players, and we’ll add Iga Swiatek and Diego Schwartzman to that list any day now.

You can always check in on the state of the project, along with a full list of charted matches, here. Raw data from more than half of the charts is available for research purposes and updated monthly, here.

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The best part about this project, to me, is that there is value in every single contribution. It may feel like a drop in the ocean to submit, say, the 544th Federer chart, but even that gives us a fuller historical record of Fed’s career and a more detailed statistical summary of his performance that season–not to mention more data on his opponent. If you’re more interested in breaking new ground, there are always interesting young players who are barely represented in the dataset.

Most of all, it’s fun–at least for the right kind of person. Maybe you think it’s bonkers that some of us enjoy typing alphanumerical codes into a spreadsheet as we watch tennis. Put it that way and … well, I get it. But once you get the hang of charting, it forces you pay more attention and learn more about this endlessly complex sport. While watching tennis. Which I suspect you enjoy quite a bit.

Learn how to get started here. I hope you’ll contribute as we march on to the next 10,000 matches.