Can Clara Tauson Withstand the Winners?

As long as she’s hitting this shot, Clara Tauson will be fine.

Clara Tauson picked up her third career title in Auckland on Sunday. She claimed the trophy after losing the first set when her opponent, Naomi Osaka, retired with an abdominal injury. It isn’t the way she would have liked to have won it, and based on the first 45 minutes of play, she probably wouldn’t have beaten a healthy Osaka. But she earned her spot in the championship match, ousting top-seeded Madison Keys in the quarter-finals.

It was a long wait for the 22-year-old from Denmark. She won two titles and reached a third final in 2021, ultimately climbing to a peak rank of 33 in early 2022. Back and foot injuries derailed her progress, and she languished outside the top 50 for more than two years. Once one of the game’s leading prospects, she still has plenty left to prove.

Tauson’s signature is what tennis people call easy power. She whips through the ball, especially on the forehand, with such impeccable technique that her strokes shoot through the court faster than it looks like they ought to. The Kiwi crowd saw an excellent display of easy power on Sunday, as Osaka possesses the same magic to an even greater extent. Both players hit angled bullets that made their opponent look lazy. But there’s little point in chasing a well-placed groundstroke off the Tauson (or Osaka) racket.

The Dane is nearly as effective from the service line. Standing six feet tall with excellent control, she can break a returner’s spirit with one ball after another on the center line. On Sunday, she served three consecutive down-the-tee aces against Osaka. A fully fit opponent might have gotten a racket on one or two of them, but only a handful of women could have put them back in play. In the last 52 weeks, only Osaka, Qinwen Zheng, and Elena Rybakina have hit aces at a better clip.

The challenge for Tauson is, well, everything else. While her backhand sometimes looks strong, the results on that wing are middling. Her second serve does not befit a six-footer. Most problematic of all, she doesn’t defend well. She piles up plenty of winners, but the women across the net hit more.

Winners take it all

It’s tempting to say that Clara’s big-swinging game is in the high-risk, high-reward Kvitova/Ostapenko/Alexandrova mold. (Okay, no one could ever be like Jelena Ostapenko, but you know what I mean.) It’s easy to picture her smacking a forehand winner or sending a groundstroke wildly astray.

The numbers, however, don’t bear it out. My go-to metric for WTA game style is Aggression Score, which tells us how often–on a per-shot basis–a player ends the point for good or ill. Tauson comes in at +18, more aggressive than average, but barely. (Average is zero, with most players falling between -100 and +100.) That’s only marginally ahead of Jasmine Paolini (+10), in a different territory entirely from Osaka (+108) or Ostapenko (+251) over the last year.

We gain some insight by breaking that number down into its components. The 22-year-old scores often enough on her favorite wing, ending points with a winner (or forced error) with nearly one in five forehands she hits. Over the last 52 weeks, that’s good for 13th out of 75 women for whom we have sufficient data:

Player                    FH Wnr%  
Jelena Ostapenko            33.1%  
Naomi Osaka                 24.8%  
Lulu Sun                    22.2%  
Aryna Sabalenka             22.0%  
Ekaterina Alexandrova       21.6%  
Amanda Anisimova            20.8%  
Katie Boulter               20.5%  
Diana Shnaider              20.4%  
Danielle Collins            20.4%  
Anastasia Pavlyuchenkova    20.3%  
Donna Vekic                 20.1%  
Liudmila Samsonova          19.6%  
Clara Tauson                19.4%

She’s barely above average, however, by the backhand version of the same metric. Many of the women near the top of the forehand list take the same tactical approach off both sides. Ostapenko, Sabalenka, and Anisimova (among others) appear in the top ten by backhand winner rate, as well. Tauson, on the other hand, puts away backhands about as often as Bianca Andreescu or Jessica Pegula.

On the positive side, the Dane’s Aggression Score lags because she doesn’t hit a huge number of unforced errors. She takes more risks than the average WTAer on forehand–13% UFEs versus 11% for the tour as a whole–but fewer on the backhand–9% against 10%. Anisimova, by comparison, hits unforced errors on 14% of her forehands and 13% of her backhands.

Fewer errors is better, all else equal. But when Tauson works the point, her opponents tend to reap the rewards. She is much more successful in short points than long ones: Only a handful of players win fewer points in the 7- to 9-shot category. Prolonging the point has only so much value when you’re unlikely to win it. For someone with the 22-year-old’s skillset, better to swing away, accept more errors, and pick up that many more quick winners in exchange.

Flat-footed

The best illustration of what happens to Tauson in those (relatively) long points is the rate at which players hit winners against her. On average, about 29% of points end with a clean winner by either player, so the typical woman sees a winner fly by about 14.5% of the time. The Dane is near the top of the list:

Player              vs Wnr/Pt  
Angelique Kerber        22.5%  
Clara Tauson            21.0%  
Marie Bouzkova          20.9%  
Emma Raducanu           19.8%  
Elise Mertens           19.3%  
Caroline Wozniacki      18.8%  
Daria Kasatkina         18.6%  
Victoria Azarenka       18.2%  
Yulia Putintseva        18.2%  
Elina Avanesyan         18.0%

This isn’t bad company, exactly. But for a free-swinging forehand expert, it’s the wrong crowd. With the possible exception of Raducanu, these are players who cough up winners because they try to build points and sometimes fail. (Or in some of these cases, opponents feast on weak second–or even first–serves.)

The biggest hitters generally allow their opponents fewer winners than average, even if they aren’t the best movers or their defensive rally skills are subpar. Here are the tour’s top ten in winners per point over the last year. I’ve shown their winners against (vs Wnr/Pt) as well, and added Tauson to the list for comparison:

Player                 Wnr/Pt  vs Wnr/Pt  
Jelena Ostapenko        21.6%      11.5%  
Aryna Sabalenka         20.7%      12.0%  
Naomi Osaka             20.1%      14.8%  
Lulu Sun                20.1%      13.5%  
Elena Rybakina          19.1%      13.4%  
Ekaterina Alexandrova   19.1%      13.2%  
Ons Jabeur              18.9%      11.5%  
Danielle Collins        18.5%      13.1%  
Leylah Fernandez        18.2%      13.5%  
Donna Vekic             18.0%      15.5%  
…                                         
Clara Tauson            15.7%      21.0%

Of the top ten, only Osaka (barely) and Vekic allow more winners than average against them. None is even close to the previous list. One of the main benefits of an aggressive game style is that it takes the racket out of the other woman’s hand, even at the cost of some mishit service returns and wild groundstroke misses. Tauson, so far, has been unwilling to make that trade. It’s unclear whether she has the ability to post consistent wins with her more conservative approach.

Take the gamble

The Dane has some room to build on her current WTA rank of 41, but without unleashing more of her weapons, more of the time, I suspect she’ll get stuck on the wrong side of the top 20. Even if she can’t match the all-around barrage of someone like Sabalenka, she’d do better to follow that example than let herself turn into the next Elise Mertens.

In the 30 Tauson matches logged by the Match Charting Project, her Aggression Score in losses was +16. In victories, it was +36. (I grouped the Auckland final with the losses.) That’s not a slam-dunk case, especially since it lumps together matches from 2019 to today. But it hints that the 22-year-old plays better when she goes bigger.

One counter-example to that trend is instructive. Last week’s quarter-final against Keys was an unusually passive victory: Tauson won in straights despite an Aggression Score of -38. The American was more likely to seize the initiative, hitting exactly twice as many winners (and twice as many unforced errors) as the Dane. Tauson’s salvation was that Keys couldn’t do much against second serves. Keys won a dire 32% of second-serve return points–worse than she did against the Tauson first serve, and enough of a liability to swing the match in her opponent’s favor.

That kind of rescue is something that Clara rarely enjoys. Among the WTA top 50, she ranks 14th by first-serve win percentage. By second-serve win percentage, though, she’s fifth from the bottom. The percentage-point difference between her two numbers ranks with the biggest gaps on tour:

Player                  1st%   2nd%   Diff  
Qinwen Zheng           75.5%  46.8%  28.7%  
Coco Gauff             71.7%  43.8%  27.9%  
Ekaterina Alexandrova  69.5%  42.6%  26.9%  
Katie Boulter          70.8%  45.1%  25.7%  
Clara Tauson           69.2%  43.5%  25.7%  
Donna Vekic            70.7%  45.4%  25.3%  
Danielle Collins       70.5%  45.8%  24.7%  
Karolina Pliskova      67.4%  42.8%  24.6%  
Elena Rybakina         72.0%  48.6%  23.4%  
Naomi Osaka            74.5%  51.6%  22.9%

Qinwen is known for the disconnect between her two deliveries; Gauff spent much of the 2024 season struggling with double faults. More to the point, most of this group cleans up on first serve. Sure, Zheng or Rybakina would love to win more second-serve points, but their first-serve win rates are so high that it hardly holds them back.

Tauson’s first-serve success–even though it pales against that mostly-elite group–implies that she should be able to muster something better off the second delivery. She could take more chances: While her double-fault rate is above average, it is not worryingly high. More likely, she could use her height to push returners wide, then attempt to finish the job on the next shot. She shows us textbook examples of that play in almost every match, just not often enough.

The Dane has physical tools that will take her far in pro tennis. She’s doesn’t, however, have such extravagant gifts that she can get away with suboptimal tactics. Even in the tall-women’s club of the WTA, there aren’t many six-footers. It’s time that Tauson plays like one.

* * *

Subscribe to the blog to receive each new post by email:

 

The 52-Week Ranking Forecast

A healthy Karolina Muchova is a top-tenner. Credit: Hameltion

What will the men’s and women’s ranking lists look like at the end of the 2025 season? A few days ago, I attempted to predict which players would crack the top 100. Today, we’re playing for bigger stakes: The names at the top the table.

As with the top-100-breakthrough forecast, the most important inputs are current Elo rank and current ATP or WTA rank. Elo tells us how well someone is playing, and the official ranking tells us how well that translated into points. After all, ranking points are what will determine the list in a year’s time, too.

The cumulative ATP and WTA rankings reflect whether a player missed time in the previous year; while that isn’t always indicative of whether he or she will be absent again, injuries often recur and some pros have a hard time staying on court. The official ranking also gives some players a head start over others: The 32nd seed at the Australian Open is more likely to reach the second week than the best unseeded player, even if they have roughly the same skill level.

Age is crucial, as well. The younger the player, the more we expect him or her to improve over the course of the year. Later than the mid-20s, however, results trend (usually!) in the other direction.

I tested the usefulness of myriad other variables, including height, handedness, and surface preference. None unambiguously improved the model. I ended up using just one more input: last year’s Elo rank. Current ranks have more predictive value, but last year’s position helps, as it offers a clue as to whether a player’s current level is sustainable.

Enough chatter–let’s start with the forecast for the 2025 year-end women’s rankings:

YE 25    Player                     Age  YE 24  Elo 24  Elo 23  
1        Aryna Sabalenka           26.7      1       1       3  
2        Iga Swiatek               23.6      2       2       1  
3        Coco Gauff                20.8      3       3       2  
4        Qinwen Zheng              22.2      5       4       8  
5        Elena Rybakina            25.5      6       6       5  
6        Jasmine Paolini           29.0      4       9      28  
7        Jessica Pegula            30.9      7       8       4  
8        Paula Badosa              27.1     12       5      24  
9        Emma Navarro              23.6      8      16      53  
10       Mirra Andreeva            17.7     16      15      26  
11       Diana Shnaider            20.7     13      12     100  
12       Daria Kasatkina           27.7      9      19      16  
13       Karolina Muchova          28.4     22       7       6  
14       Barbora Krejcikova        29.0     10      22      14  
15       Marta Kostyuk             22.5     18      20      38  
16       Anna Kalinskaya           26.1     14      23      31  
17       Madison Keys              29.9     21      11      12  
18       Beatriz Haddad Maia       28.6     17      17      18  
19       Jelena Ostapenko          27.6     15      29      13  
20       Marketa Vondrousova       25.5     39      10       9  
21       Danielle Collins          31.0     11      31      22  
22       Linda Noskova             20.1     26      35      42  
23       Donna Vekic               28.5     19      27      41  
24       Liudmila Samsonova        26.1     27      26      11  
25       Leylah Fernandez          22.3     31      30      20  
                                                                
YE 2025  Player                     Age  YE 24  Elo 24  Elo 23  
26       Victoria Azarenka         35.4     20      13      29  
27       Elina Svitolina           30.3     23      24      19  
28       Ons Jabeur                30.3     42      14       7  
29       Maria Sakkari             29.4     32      21      15  
30       Katie Boulter             28.4     24      33      62  
31       Amanda Anisimova          23.3     36      28       
32       Anastasia Potapova        23.8     35      36      36  
33       Emma Raducanu             22.1     56      18       
34       Yulia Putintseva          30.0     29      25      55  
35       Magdalena Frech           27.0     25      51      85  
36       Elise Mertens             29.1     34      37      33  
37       Xin Yu Wang               23.3     37      59      57  
38       Ekaterina Alexandrova     30.1     28      48      25  
39       Anastasia Pavlyuchenkova  33.5     30      32      35  
40       Marie Bouzkova            26.4     44      44      30  
41       Elina Avanesyan           22.3     43      60     131  
42       Lulu Sun                  23.7     40      56     182  
43       Peyton Stearns            23.2     47      53     113  
44       Katerina Siniakova        28.6     45      38      40  
45       Olga Danilovic            23.9     51      50      82  
46       Ashlyn Krueger            20.7     64      54      67  
47       Camila Osorio             23.0     59      49      56  
48       Dayana Yastremska         24.6     33     104      96  
49       Clara Tauson              22.0     50      83      64  
50       Karolina Pliskova         32.8     41      40      39

No big surprises here–that’s the nature of a model like this. Where players are predicted to move up or down, it’s usually because their Elo rank is notably higher or lower than their official position, like Muchova or Paolini. Mirra Andreeva, the youngest woman in the top 175, is expected to gradually work her way into the top ten.

Getting fuzzier

Of course, there’s considerable uncertainty. When we check in at the end of the 2025 season, we’ll find some substantial moves, like Paolini in 2024. We can get a better idea of that uncertainty by forecasting the likelihood that players reach certain thresholds.

Here is each top player’s probability of becoming the 2025 year-end number one:

Player              p(#1)  
Aryna Sabalenka     42.3%  
Iga Swiatek         32.6%  
Coco Gauff          21.1%  
Qinwen Zheng         6.9%  
Elena Rybakina       4.3%  
Jasmine Paolini      2.8%  
Jessica Pegula       2.4%  
Emma Navarro         0.9%  
Paula Badosa         0.9%  
Daria Kasatkina      0.9%  
Barbora Krejcikova   0.7%  
Mirra Andreeva       0.7%  
Diana Shnaider       0.5%  
Karolina Muchova     0.5%

This is not the list I would have made. Again, this type of model isn’t going to give you big surprises, and there’s no consideration for things like playing styles. Intuitively, a big breakthrough from Andreeva (or Shnaider) seems more likely than a belated push from Kasatkina, or even Pegula.

In any event, we get an idea of how much the ranking list can shuffle itself in a year’s time. Even beyond these 14 names, the model gives another 20 women at least a one-in-a-thousand chance to end the year at the top.

We can run a similar exercise to get the odds that each player ends the season in the top 5, 10, or 20:

Player                    p(top 5)  p(top 10)  p(top 20)  
Aryna Sabalenka              82.4%      95.8%      99.3%  
Iga Swiatek                  81.0%      94.9%      98.9%  
Coco Gauff                   75.5%      92.7%      98.3%  
Qinwen Zheng                 50.3%      80.3%      95.5%  
Elena Rybakina               32.5%      65.5%      90.3%  
Jessica Pegula               15.5%      42.0%      78.4%  
Paula Badosa                 15.2%      41.5%      81.7%  
Mirra Andreeva               13.7%      34.5%      68.3%  
Jasmine Paolini              13.1%      38.4%      77.7%  
Karolina Muchova             10.6%      30.2%      69.8%  
Diana Shnaider                8.8%      25.7%      64.6%  
Emma Navarro                  7.9%      24.0%      60.2%  
Marketa Vondrousova           6.6%      19.2%      53.8%  
Daria Kasatkina               5.8%      18.3%      49.6%  
Marta Kostyuk                 4.9%      14.9%      43.4%  
Madison Keys                  4.9%      15.8%      49.7%  
Barbora Krejcikova            4.2%      13.5%      40.2%  
Beatriz Haddad Maia           3.8%      12.1%      39.7%  
Anna Kalinskaya               3.5%      11.2%      35.8%  
Jelena Ostapenko              3.0%       9.4%      28.8%  
Leylah Fernandez              2.9%       8.5%      25.8%  
Liudmila Samsonova            2.8%       8.6%      27.0%  
Linda Noskova                 2.8%       8.2%      24.9%  
Ons Jabeur                    2.8%       8.7%      31.7%  
Maria Sakkari                 1.9%       6.1%      23.1%  
                                                          
Player                    p(top 5)  p(top 10)  p(top 20)  
Danielle Collins              1.9%       6.3%      22.5%  
Elina Svitolina               1.7%       5.7%      21.6%  
Donna Vekic                   1.7%       5.4%      21.1%  
Victoria Azarenka             1.6%       5.9%      28.2%  
Anastasia Potapova            1.5%       4.5%      15.8%  
Emma Raducanu                 1.5%       4.7%      21.6%  
Amanda Anisimova              1.1%       3.5%      15.4%  
Yulia Putintseva              1.0%       3.4%      15.1%  
Katie Boulter                 1.0%       3.3%      13.5%  
Marie Bouzkova                0.8%       2.4%       8.8%  
Elise Mertens                 0.8%       2.5%      10.1%  
Xin Yu Wang                   0.8%       2.3%       7.8%  
Ashlyn Krueger                0.8%       2.1%       7.3%  
Camila Osorio                 0.7%       2.0%       7.4%  
Ekaterina Alexandrova         0.7%       2.1%       7.9%  
Magdalena Frech               0.6%       2.0%       8.0%  
Katerina Siniakova            0.6%       2.0%       8.1%  
Olga Danilovic                0.6%       1.8%       6.8%  
Peyton Stearns                0.6%       1.7%       6.6%  
Anastasia Pavlyuchenkova      0.6%       1.9%       8.9%  
Elina Avanesyan               0.6%       1.7%       6.2%  
Clara Tauson                  0.5%       1.4%       4.3%  
Lulu Sun                      0.5%       1.5%       5.9%  
Eva Lys                       0.4%       1.2%       4.8%  
Elisabetta Cocciaretto        0.4%       1.2%       4.1%

Most interesting to me in this table is where the columns diverge. Andreeva, with her unrealized potential, ranks higher on the top-5 list than by top-10 or top-20 probability. Azarenka, though she has little chance of returning to the top ten, is more likely than her list-neighbors to hang inside the top 20.

The same variation means that there are some new names in the table. Eva Lys, for instance, is forecast to land at #65 ahead of the 2026 season. But because she is young and has already posted multiple top-100 seasons by Elo rating, she has an outsized chance of a major breakout. The women who were displaced are either fringy veterans, like Pliskova, or those whose Elo ratings didn’t match their WTA rank, such as Yastremska.

(These forecasts are probably more accurate than the year-end-number-one table above. There haven’t been many year-end number ones, by definition, so there’s less data to draw upon.)

Long may Sinner reign

Now for the men. I’ve extended this list to 51 for obvious reasons:

YE 25  Player                  Age  YE 24  Elo 24  Elo 23  
1      Jannik Sinner          23.4      1       1       2  
2      Carlos Alcaraz         21.7      3       3       3  
3      Alexander Zverev       27.7      2       4       5  
4      Taylor Fritz           27.2      4       6      10  
5      Daniil Medvedev        28.9      5       5       4  
6      Novak Djokovic         37.6      7       2       1  
7      Holger Rune            21.7     13      10      12  
8      Jack Draper            23.0     15       8      19  
9      Casper Ruud            26.0      6      21      16  
10     Alex de Minaur         25.9      9      16      11  
11     Andrey Rublev          27.2      8      18       6  
12     Stefanos Tsitsipas     26.4     11      14       9  
13     Tommy Paul             27.6     12      11      18  
14     Hubert Hurkacz         27.9     16       9       8  
15     Grigor Dimitrov        33.6     10       7       7  
16     Ugo Humbert            26.5     14      17      13  
17     Lorenzo Musetti        22.8     17      20      50  
18     Arthur Fils            20.6     20      25      38  
19     Ben Shelton            22.2     21      22      17  
20     Sebastian Korda        24.5     22      15      22  
21     Tomas Machac           24.2     25      12      33  
22     Karen Khachanov        28.6     19      19      23  
23     Felix Auger Aliassime  24.4     29      28      15  
24     Frances Tiafoe         26.9     18      33      26  
25     Matteo Berrettini      28.7     34      13      14  
                                                           
YE 25  Player                  Age  YE 24  Elo 24  Elo 23  
26     Alexei Popyrin         25.4     24      27      75  
27     Jiri Lehecka           23.1     28      39      46  
28     Flavio Cobolli         22.7     32      30     136  
29     Alex Michelsen         20.4     41      35     134  
30     Jakub Mensik           19.3     48      37     119  
31     Mpetshi Perricard      21.5     31      43     192  
32     Francisco Cerundolo    26.4     30      36      25  
33     Matteo Arnaldi         23.9     37      48      31  
34     Sebastian Baez         24.0     27      67      40  
35     Brandon Nakashima      23.4     38      42      70  
36     Jordan Thompson        30.7     26      29      51  
37     Juncheng Shang         19.9     50      52       
38     Tallon Griekspoor      28.5     40      32      24  
39     Alejandro Tabilo       27.6     23      54     121  
40     Denis Shapovalov       25.7     56      34      34  
41     T M Etcheverry         25.5     39      58      65  
42     Alexander Bublik       27.5     33      59      44  
43     Davidovich Fokina      25.6     61      46      28  
44     Roman Safiullin        27.4     60      38      27  
45     Nicolas Jarry          29.2     35      63      20  
46     Nuno Borges            27.9     36      53      88  
47     Thanasi Kokkinakis     28.7     77      24      61  
48     Luciano Darderi        22.9     44     106     122  
49     Miomir Kecmanovic      25.3     54      65      71  
50     Jan Lennard Struff     34.7     42      26      35  
51     Joao Fonseca           18.4    145      45

The men’s ranking model is more accurate than the women’s version, though that may be because it is built, in part, on the unusually stable Big Three/Big Four era. That stability might be gone, taking the reliability of this model with it. (The men’s model predicted the log of next year’s ranking with an adjusted r-squared of .631, compared to .580 for the women.) So again, if it looks boring, that’s the nature of the beast.

Still: We have Carlos Alcaraz taking back the number two spot, Holger Rune returning to the top ten, and Jack Draper following him in. In the other direction, we see Grigor Dimitrov’s age catching up to him, dropping five spots from his current position.

At the bottom of the list, we find Joao Fonseca bounding up nearly 100 ranking spots in a single season. That already feels conservative, less than one week into his season. All of these numbers are based on 2024 year-end rankings, yet Fonseca is up 18 places in the live rankings with his run to the Canberra Challenger final. He’d gain another 14 with a win tomorrow.

What about Novak?

The table above shows Novak Djokovic in 6th place, a prediction that aggregates a vast range of possibilities. Here are the odds of various players ending 2025 at the top of the list:

Player             p(#1)  
Jannik Sinner     56.4%  
Carlos Alcaraz    22.5%  
Novak Djokovic    14.6%  
Alexander Zverev   3.8%  
Daniil Medvedev    3.4%  
Taylor Fritz       1.3%  
Holger Rune        1.2%  
Jack Draper        1.2%  
Hubert Hurkacz     1.0%  
Grigor Dimitrov    0.7%

No one else is even half as likely as Dimitrov to end the season ranked #1. Sinner is the clear favorite, with virtually every stat in his favor. Alcaraz is expected to improve. Djokovic, though, is the clear number three, far ahead of the other players above him in the previous table.

This is partly to be expected: He ended 2024 in second place on the Elo list. He didn’t play a full schedule, but he posted great results much of the time he played, and Alcaraz wasn’t consistent enough to capitalize on the veteran’s step back. Beyond that, remember that the model considers last year’s Elo rank as well. Twelve months ago, Djokovic still had a strong claim to be the best player in the world. His age counts against him, but he is one of only a few players in the 2025 field who has proven he can reach the top.

Novak’s 6th-place forecast, then, averages a disproportionately high probability of a resurgence with all the things that can happen to 37-year-old athletes. He’s more likely than, say, (projected) #5 Medvedev or #7 Rune to claim the top spot, but he’s also more likely to fall down the list due to injury or lack of interest.

Djokovic looks like less of an outlier when we see the chances of top-5, top-10, and top-20 finishes this year:

Player                  p(5)  p(10)  p(20)  
Jannik Sinner          95.6%  98.9%  99.8%  
Carlos Alcaraz         84.5%  95.7%  99.2%  
Alexander Zverev       61.7%  88.4%  97.5%  
Daniil Medvedev        38.5%  71.8%  92.6%  
Taylor Fritz           34.1%  72.0%  92.9%  
Novak Djokovic         32.4%  59.8%  86.4%  
Holger Rune            20.3%  52.8%  86.1%  
Jack Draper            15.6%  46.3%  82.2%  
Hubert Hurkacz          9.8%  29.9%  68.2%  
Andrey Rublev           9.8%  31.8%  70.8%  
Stefanos Tsitsipas      9.6%  31.6%  70.6%  
Alex de Minaur          9.5%  32.9%  72.1%  
Grigor Dimitrov         8.3%  27.0%  63.1%  
Casper Ruud             7.7%  31.1%  70.6%  
Tommy Paul              7.1%  26.8%  65.0%  
Ugo Humbert             5.3%  20.2%  56.9%  
Ben Shelton             4.8%  18.5%  55.8%  
Sebastian Korda         4.5%  17.8%  53.5%  
Tomas Machac            4.4%  18.3%  54.3%  
Arthur Fils             3.7%  17.0%  54.0%  
Lorenzo Musetti         3.4%  16.6%  52.3%  
Matteo Berrettini       2.4%   8.7%  32.2%  
Felix Auger Aliassime   2.1%   8.2%  32.7%  
Karen Khachanov         2.0%   8.8%  32.8%  
Frances Tiafoe          1.3%   6.3%  25.9%  
                                            
player                  p(5)  p(10)  p(20)  
Jiri Lehecka            1.0%   5.0%  22.7%  
Alexei Popyrin          0.9%   5.4%  23.1%  
Francisco Cerundolo     0.8%   3.8%  17.3%  
Flavio Cobolli          0.7%   4.5%  20.7%  
Jakub Mensik            0.7%   4.1%  20.0%  
Alex Michelsen          0.7%   4.2%  20.2%  
Matteo Arnaldi          0.7%   3.0%  14.7%  
Tallon Griekspoor       0.6%   2.4%  11.0%  
Brandon Nakashima       0.5%   2.8%  13.9%  
Denis Shapovalov        0.5%   2.2%  10.5%  
Sebastian Baez          0.5%   2.5%  12.6%  
Mpetshi Perricard       0.5%   3.3%  16.2%  
Jordan Thompson         0.4%   2.3%  10.3%  
Davidovich Fokina       0.4%   1.5%   7.6%  
Roman Safiullin         0.4%   1.5%   7.1%  
Juncheng Shang          0.3%   2.0%  10.8%  
Nicolas Jarry           0.3%   1.2%   5.7%  
Thanasi Kokkinakis      0.3%   1.2%   5.7%  
Alexander Bublik        0.3%   1.3%   6.6%  
T M Etcheverry          0.3%   1.4%   7.1%  
Alejandro Tabilo        0.2%   1.5%   7.5%  
Jan Lennard Struff      0.2%   1.0%   4.3%  
Joao Fonseca            0.2%   1.0%   5.7%  
Nuno Borges             0.2%   1.0%   5.2%  
Miomir Kecmanovic       0.2%   0.9%   4.5%

The various models don’t quite agree: It can’t really be the case that if Djokovic cracks the top five (32.4% here), it’s nearly 50/50 whether he ends the season at number one. From outside of the models, we can be particularly skeptical, since we know that Novak isn’t likely to play a full schedule. Still, we can glean something from the juxtaposition: There’s not a lot of middle ground for the all-time-great.

Again, it’s worth peeking at the bottom of the list. Fonseca makes this one, too, with a nearly 6% chance of a top-20 debut this year. (Actually, a debut is even more likely, since this is the stricter probability of a year-end top-20 finish.) It seems a bit crazy to say that the 18-year-old has the same top-20 chances as Nicolas Jarry. On the other hand, Fonseca leads Jarry on the Elo table by a healthy margin. He may already be the stronger player.

Few pros are likely catapult up or down the rankings like Fonseca. Plenty will make moves that these models don’t foresee. With the information available at the beginning of the season, we can get a general sense of how things will change over the next twelve months. Now for the good part: We get to find out how the models were wrong.

* * *

Subscribe to the blog to receive each new post by email:

 

The Pending Breakthroughs of 2025

Eva Lys, probably a top-100 player in 2025. Credit: Nuta Lucian

Every year, Challenger maven Damian Kust lists the players he thinks are likely to join the ATP top 100 in the coming year. He did a typically good job last year, picking 14 of the 20 players who reached the threshold in 2024. We can forgive him for missing Jacob Fearnley, who rose from 646th to the top 90 in less than twelve months.

I’ve yet to meet a forecast that I didn’t want to mathematically model, and this is no exception. An algorithm probably isn’t going to do better than Damian does, as it will miss all kinds of details accumulated by a full-time tour watcher. But the exercise will give us a better idea of what factors make it more or less likely that a player joins the top-100 club.

Let’s get straight to the forecast:

Rank  Kust  Player               Rank  Elo Rk   Age  p(100)  
1     3     Joao Fonseca          145      45  18.4   96.5%  
2     4     Learner Tien          122      74  19.1   92.4%  
3     1     Hamad Medjedovic      114      91  21.5   89.1%  
4     5     Nishesh Basavareddy   138      84  19.7   84.2%  
5     9     Raphael Collignon     121      97  23.0   82.5%  
6     8     Martin Landaluce      151      99  19.0   82.1%  
7     6     Jerome Kym            134     111  21.9   79.6%  
8           Leandro Riedi         135     108  22.9   71.9%  
9     15    Jaime Faria           123     146  21.4   69.0%  
10    7     Jesper de Jong        112     117  24.6   66.8%  
11    12    Tristan Boyer         133     116  23.7   64.0%  
12    2     Francesco Passaro     108     147  24.0   60.9%  
13          Harold Mayot          116     154  22.9   57.6%  
14    10    Alexander Blockx      203     102  19.7   56.8%  
15    16    Valentin Vacherot     140     110  26.1   55.2%  
16    11    N Moreno de Alboran   110     132  27.5   52.5%  
17          Lukas Klein           136     126  26.8   47.0%  
18    19    Elmer Moeller         160     160  21.5   37.4%  
19    18    Duje Ajdukovic        142     171  23.9   36.6%  
20          Terence Atmane        158     174  23.0   35.5%  
21          R A Burruchaga        156     177  22.9   28.1%  
22          Matteo Gigante        141     203  23.0   26.8%  
23    13    Vit Kopriva           130     150  27.5   26.3%  
24          Gustavo Heide         172     190  22.8   24.3%  
25          Coleman Wong          170     238  20.6   24.3%  
            …                                                
35    14    Mark Lajal            229     187  21.6   13.4%  
            …                                                
41    17    Dino Prizmic          292     167  19.4   10.6%  
42    20    James Trotter         193     175  25.4   10.4%

The table shows the 25 men who are most likely to make their top-100 debut this year, plus a few more from Damian’s list. I’ve included Damian’s rankings*, as well as each player’s year-end ATP ranking, year-end ranking on my Elo list, and their current age. The final column, “p(100),” is their probability of reaching the ranking milestone sometime in 2025.

* Damian points out that his numbering wasn’t intended as an explicit ranking, though he did end up picking the more obvious players first, with the long shots at the end.

The three columns between the players and their probabilities are the main components of the logistic-regression model. Age, unsurprisingly, is key. The younger the player, the more likely he’ll improve. Plus, the youngest men may have played limited schedules, causing their official rankings to underestimate their ability levels.

It’s a bit unusual to include both ATP rank and Elo rank, since they are simply different interpretations of the same underlying match results. In this case, though, it makes sense. Elo is better at predicting a player’s performance tomorrow, and it outperforms the official list as a way of predicting rankings a year from now. However, we’re trying to forecast ranking breakthroughs less than a year from now. If Fonseca has a good month Down Under, he’ll crack the top 100 in large part thanks to his eleven months’ worth of ranking points from 2024. In this model, then, the ATP ranking tells us how close a player is to the point total he needs. Elo tells us more about how likely he is pile up the remaining wins.

A player’s existing stock of points turns out to be somewhat more important than his underlying skill level. The model weights ATP ranking about half-again as heavily as Elo rank.

There are innumerable other variables we could include. I tested a lot of them. The only other input I kept was height. Height is only a minor influence on top-100 breakthroughs, but it’s definitely better to be taller. De Jong, for instance, is five feet, eleven inches tall. He ranks eighth on the 2025 list when height is omitted, and falls to tenth when height is included.

This tallies with the Challenger-to-tour conversion stats I worked out for my recent post about Learner Tien. Both short players and left-handers have a harder time making the jump than their taller, right-handed peers. Those conversions don’t address quite the same thing, since it’s possible to crack the top 100 with little to no success at tour level–it just means winning lots of Challengers. For that reason, left-handedness is probably an advantage for players aiming to jump from, say, 122nd to the top 100, as Tien is now. The relationship between left-handedness and breakthrough likelihood was less clear-cut than height, though, so I left it out.

J-wow

Enough mechanics–back to the forecasts. Fonseca’s 96.5% probability might strike you as crazily high or outrageously conservative. It’s certainly confident, but then again the Brazilian is a special player. Barring injury–and immediate injury, at that–a breakthrough seems likely to happen soon.

Whether high or low, the Fonseca forecast is unusual. Like his forehand, it puts him in classy company. Going back to 2000, here are the players about whom the model would have been most optimistic:

Year  Player                 Rank  Elo    Age  p(100)  Y+1  
2021  Holger Rune             103    50  18.7   98.7%   10  
2020  Sebastian Korda         118    48  20.5   97.9%   38  
2024  Joao Fonseca            145    45  18.4   96.5%       
2010  Grigor Dimitrov         106    75  19.6   96.3%   52  
2020  Carlos Alcaraz          141    51  17.7   96.1%   32  
2018  Felix Auger Aliassime   108    89  18.4   95.8%   17  
2023  Hamad Medjedovic        113    66  20.5   95.4%  105  
2000  Andy Roddick            156    52  18.3   94.5%   14  
2020  Lorenzo Musetti         128    68  18.8   94.0%   57  
2019  Emil Ruusuvuori         123    64  20.7   94.0%   84

It’s not so remarkable that eight of the nine other players on the list succeeded in reaching the top 100. The forecast would have expected (at least) that. But even including Medjedovic’s disappointing finish to 2024, the average ranking of these nine guys at the end of the following season (“Y+1”) is 45. Three broke into the top 20. And Fonseca’s forecast places him ahead of most of them.

Medjedovic’s near-miss was due in part to illness. It’s worth remembering that this model only predicts a single year; the young Serbian is still set up for a nice career. (Including, probably, a top-100 debut in 2025.) The model would have given Francisco Cerundolo a 90% chance of breaking through in 2021. He didn’t make it, yet he reached the top 20 a couple of years later. Fernando Gonzalez failed to convert an 80% chance in 2001, but after a few more years, he made the top ten.

Using a simple model–instead of the expert opinion of someone like Damian–exposes us to another type of error. The model is optimistic about the 2025 chances of 22-year-old Leandro Riedi, who possesses both official and Elo ranks on the cusp of the top 100. On paper, he’s a great pick. But he had knee surgery in September. Instead of defending points from two Challenger titles in January, he’s continuing to recover. He may ultimately surpass many of the other guys on the list, but even just regaining his pre-injury form this year is a big ask.

Waiting for Eva

Let’s run the same exercise for the women’s game. Unfortunately I don’t have enough height data, so we can’t use that. The resulting model is less predictive than the men’s forecast (even apart from the lack of player heights), but with year-end WTA rank, Elo rank, and age, it’s almost as good.

Patrick Ding took up the task of a Kust-style list for women. It’s unordered, so I’ve added a “Y” in the “PD” column next to his picks:

Rank  PD  Player                Rank  Elo   Age  p(100)  
1     Y   Eva Lys                131   43  23.0   80.1%  
2     Y   Anca Todoni            118  100  20.2   74.9%  
3     Y   Maya Joint             116  173  18.7   65.8%  
4         Aoi Ito                126  109  20.6   65.4%  
5     Y   Marina Stakusic        125  131  20.1   62.3%  
6     Y   Polina Kudermetova     107  159  21.6   61.8%  
7     Y   Alina Korneeva         177   80  17.5   61.8%  
8     Y   Robin Montgomery       117  155  20.3   61.1%  
9     Y   Sara Bejlek            161   88  18.9   59.9%  
10        M Sawangkaew           130   94  22.5   58.8%  
11        Anastasia Zakharova    112  145  23.0   54.1%  
12    Y   Sijia Wei              134  135  21.1   49.9%  
13    Y   Celine Naef            153  124  19.5   48.8%  
14    Y   Antonia Ruzic          143  105  21.9   48.7%  
15        Maja Chwalinska        128  119  23.2   47.7%  
16    Y   Sara Saito             150  182  18.2   43.1%  
17        Alexandra Eala         148  162  19.6   41.6%  
18    Y   Darja Semenistaja      119  192  22.3   41.5%  
19    Y   Dominika Salkova       151  150  20.5   38.1%  
20        Talia Gibson           140  185  20.5   37.2%  
21        V Jimenez Kasintseva   156  170  19.4   36.3%  
22    Y   Ella Seidel            141  205  19.9   36.2%  
23    Y   Iva Jovic              189  157  17.1   33.8%  
24        Daria Snigur           139  161  22.8   32.0%  
25        Francesca Jones        152  106  24.3   31.5%  
26    Y   Solana Sierra          163  156  20.5   30.2%  
27    Y   Ena Shibahara          137  103  26.9   29.1%  
28        Lois Boisson           204   95  21.6   23.9%  
29        Elsa Jacquemot         159  191  21.7   21.8%  
30    Y   Taylah Preston         170  246  19.2   20.0%  
31    Y   Tereza Valentova       240  127  17.9   19.6%  
32        Elena Pridankina       186  201  19.3   18.9%  
33        Lola Radivojevic       185  186  20.0   18.9%  
34    Y   Oksana Selekhmeteva    176  176  22.0   16.8%  
35        Barbora Palicova       180  202  20.8   16.2%

This isn’t quite a fair fight with Patrick, because he made his picks in early October. Two of his choices (Suzan Lamens and Zeynep Sonmez) have already cleared the top-100 hurdle. He would presumably consider Ito more carefully now, since she reached a tour-level semi-final two weeks after he made his list. I should also note that Patrick picked two prodigies outside the top 300: Renata Jamrichova and Mia Ristic. My model didn’t consider players ranked that low. I had to draw the line somewhere, and Fearnley aside, single-year ranking leaps of that magnitude are quite rare.

The mechanics of the algorithm are pretty much the same as the men’s version. The women’s list looks a bit more chaotic, pitting players with strong Elo positions (such as Lys and Korneeva) against others who are close to 100 without the results that Elo would like to see (Joint, Kudermetova, etc).

Eva Lys is fascinating because this is her third straight year near the top of the list. She finished 2022 ranked 127th, standing 71st on the Elo table. Just short of her 21st birthday, that was good for a 76% chance of reaching the top 100 the following year–second on the list to Diana Shnaider. She rose as high as 112, but no further.

A year older, Lys was fourth on the 2023 list. Her WTA ranking of 136 and her nearly-unchanged Elo position of 72 worked out to a 67% chance of a 2024 breakthrough. Only three players–Brenda Fruhvirtova, Erika Andreeva, and Sara Bejlek–scored higher. She came within one victory of the milestone in September but finds herself back on the list for 2024.

Even beyond Lys’s 80% chance of finally making it in 2025, history is encouraging. I went back 25 years for this study, and only two other players would have been given a 50% or better chance of reaching the top 100 for three consecutive years. Stephanie Dubois was on the cusp from 2005 to 2007, finishing the third year ranked 106th. She finally made it in 2008. More recently, Wang Xiyu was within range from 2019-21. (Covid-19 cancellations and travel challenges didn’t help.) She not only cleared the hurdle in 2022, she did it with style, climbing to #50 by the end of that season.

The same precedents bode well for Bejlek, who had a 52% chance of breaking through in 2023, a 77% chance last year, and a 60% probability for 2025.

Mark your calendars

In twelve months, we can check back and see how the model fared against Damian and Patrick. The algorithm has the benefit of precision, and it is less likely to get overexcited about as-yet-unfulfilled potential. The flip side is that it doesn’t consider the innumerable quirks that might bear on the chances of a particular player.

For now, I’m betting on the humans.

* * *

Subscribe to the blog to receive each new post by email:

 

Joao Fonseca and Damage Down the Line

Joao Fonseca doing what he does best

Joao Fonseca made easy work of last week’s Next Gen Finals. He went undefeated against the world’s best under-21s, dropping just one set in best-of-five semi-finals and finals. The youngest player in the field, he joins Jannik Sinner and Carlos Alcaraz as 18-year-old champions in the seven-year history of the event.

There’s no secret to Fonseca’s success. He already possesses a devastating forehand, a shot with power that invites comparisons to fellow South Americans Juan Martin del Potro and Fernando Gonzalez. Outrageous as it sounds, Fonseca’s might turn out to be even better. The Brazilian has a more compact stroke, making his forehand more flexible–and perhaps ultimately more reliable–than the long-levered Delpo motion.

In his round-robin match against Jakub Mensik, the TennisTV broadcast flashed a stat meant to indicate one way Fonseca excels:

The TennisTV commentators were flabbergasted by these numbers: They’d never seen anything like it. Hugh, responsible for the screenshot here, got straight to the point. If a player with a forehand like Fonseca’s can consistently send the ball to his opponent’s weaker side, it’s game over.

The easiest direction to hit a groundstroke is back the way it came. That’s how we end up with protracted cross-court rallies. It takes impeccable timing to react to a elite-level cross-court forehand and change direction. (Pros drill that specific sequence, but no amount of practice makes it easy.) Down-the-line shots are doubly difficult because the net is higher as it nears the posts. The timing needs to be near-perfect, and there’s a smaller margin for error.

Here’s another way to get a sense of the dangerous risk level of down-the-line groundstrokes. Novak Djokovic, king of the down-the-line backhand, doesn’t hit that many of them. The inherent limitations of tennis rackets and the dimensions of the court are unforgiving. Fonseca, if he can really hit more than half of his forehands down the line, could defy those limitations.

Fact-check

Normally, I’d give you all sorts of numbers to help anchor Fonseca’s stats. How much does his 56% clip exceed tour average, or compare to someone like Sinner? That’s my goal, but first, we need to get into the weeds a bit.

The Match Charting Project has 14 Fonseca matches in the database, including all five of his NextGen Finals contests. Here’s the breakdown of groundstroke direction for the Mensik match:

This is… not the same as the broadcast graphic. We should expect minor differences, both because the 44/56 stat was shown midway through the match, and because reasonable people can disagree about how to classify shots that don’t obviously belong to a specific category. But that’s not what’s going on here. There’s virtually no way to take these numbers and conclude that Fonseca hit more than half of his forehands down the line.

What’s more, Fonseca’s forehand-direction profile is rather pedestrian. That’s not to say that his forehand is ordinary, just that he aims in the same directions as his peers. Here is Joao’s forehand-direction distribution, based on those 14 charted matches, compared with tour average:

DIRECTION      Fonseca  Average  
Cross-court        40%      39%  
Middle             20%      22%  
Down the line      10%      11%  
Inside-out         26%      24%  
Inside-in           4%       4%

Ho-hum, right? Maybe he hits a few more inside-out forehands instead of going back up the middle. Even there, the two-percentage-point gaps between Fonseca and tour average could be an artifact of the matches we’ve charted. The Brazilian’s forehand does plenty of damage, but as a function of how he hits it, not where.

More weeds, sorry

I should probably let the discrepancy go, but let’s give it another minute. I don’t think the broadcast graphic was wrong, but it’s clearly measuring something different than what I count for the Match Charting Project stats. Maybe there’s some important subset of forehands that Fonseca is unusually likely to hit down the line?

One of the more difficult–and damaging–specific shots is the forehand down the line from the forehand corner. The MCP divides the court into three sectors by width: to the (right-hander’s) forehand corner, down the middle, and to the backhand. Maybe Fonseca particularly likes to change direction when he sees a ball in his own forehand corner?

A bit, but not by much. Here are the direction frequencies for Fonseca’s forehands from his forehand corner, for both the Mensik match and the average of his charted matches, along with the frequencies for his opponents:

             To FH  Middle    DTL  
vs Mensik    58.1%   22.6%  19.4%  
Fonseca Avg  49.0%   23.6%  27.5%  
Opp Avg      45.7%   30.9%  23.4%

Nothing really dramatic here, and he went down the line less often in the Mensik match than his typical opponent does.

What about when Fonseca gets a ball down the middle? We saw in the MCP stats above that he hits a lot of inside-out forehands. That includes shots from the middle to the backhand side of a right-handed opponent. Here is the same group of frequencies for the same sets of matches, this time excluding left-handed opponents because they will naturally make different choices from the middle of the court:

              To FH  Middle    DTL  
vs Mensik     29.7%   25.7%  44.6%  
Fonseca Avg   39.7%   20.0%  40.3%  
(RH) Opp Avg  34.2%   25.4%  40.4%

There’s a few more down-the-line shots in the Mensik match. But over 14 matches, Fonseca differs from his opponents only in hitting fewer balls back up the middle.

Maybe you’ve already worked out the underlying discrepancy. Since the 44/56 split adds up to 100%, there’s no “down the middle” category in the broadcast stats. The graphic splits forehands into two buckets, not three. That’s not how I think about tennis, and I suspect it’s not how you do, either. They would have done better to label the columns “to the forehand” and “to the backhand,” or something along those lines. It’s not unusual at all to hit 56% of one’s forehands to the opponent’s backhand side. But a lot of those “to the backhand” shots are not what anybody would normally call “down the line.”

The Fonseca difference

It’s not about tactics, it’s good old-fashioned power and precision. Fonseca’s forehand isn’t innovative, and it doesn’t need to be. If he hits his shots in more or less the same directions that his peers do, he’s probably doing something right. It means that at age 18, he has already internalized pro tactics. The difference is that he’s hitting those forehands harder, and he’s often landing them closer to the lines, something hinted at by his low rate of down-the-middle forehands.

He already shows up near the top of my Forehand Potency (FHP) leaderboard–though I’ll give you some caveats in a minute:

Rank  Player              FHP/100  
1     Andrey Rublev          14.0  
2     Jan-Lennard Struff     11.6  
3     Joao Fonseca           11.3  
4     Stefanos Tsitsipas     11.0  
5     Carlos Alcaraz         10.8  
6     Rinky Hijikata          9.7  
7     Jannik Sinner           9.4  
8     Casper Ruud             9.2  
9     Juncheng Shang          8.6  
10    Novak Djokovic          8.6

FHP combines forehand winners and errors, along with shots that lead to both opponent errors and winners on the player’s next shot. Given the vagaries of estimating the effect of one shot on others, Fonseca effectively sits in a tie for second place, as good or better than everyone except for Andrey Rublev. Which, I’d say, checks out.

The caveats lie in the dataset. The Brazilian has faced only one top-20 opponent, and that was a possibly-unmotivated #20 Arthur Fils last week. The charting data on which FHP numbers are based includes all the NextGen Finals matches, along with some Challenger-level matches and some early rounds at ATPs. After all, he’s 18 and that’s all he’s played. Point being, an 11.3 FHP/100 (per 100 forehands) against that level of competition probably isn’t is good as Alcaraz’s 10.8 or Sinner’s 9.4, amassed against foes like each other.

But don’t take that adjustment too far. Fonseca scored a 11.0 against Fils in Rio, when he was barely 17 and a half. Facing Botic van de Zandschulp in a Davis Cup tilt, he registered a whopping 16.7 FHP/100. The Dutchman is hardly easy pickings: When Sinner played van de Zandschulp twice early in the season, he managed just 1.2 and 7.1 on the same metric.

Damage (not just) down the line

Fonseca doesn’t hit an unusual number of forehands down the line, but when he does, opponents barely stand a chance. Among the 200-plus players with as many down-the-line forehands in the MCP database as Fonseca has, he ranks sixth in points won when he hits the shot. Admittedly, it’s an odd list:

Rank  Player                   W/FE%   UFE%  inPtsWon%  
1     Juncheng Shang           33.6%  13.1%      66.4%  
2     Nishesh Basavareddy      29.4%  10.3%      65.1%  
3     Luca Van Assche          22.9%  11.0%      62.4%  
4     Hyeon Chung              30.1%  19.9%      61.8%  
5     Bjorn Borg               26.3%   7.3%      61.6%  
6     Joao Fonseca             31.1%  17.6%      61.3%  
7     Rafael Nadal             28.9%  12.8%      61.2%  
8     Camilo Ugo Carabelli     10.3%   9.6%      60.9%  
9     Corentin Moutet          29.4%  15.6%      60.6%  
10    Zhizhen Zhang            22.8%  15.9%      60.3%  
11    Guillermo Garcia Lopez   20.3%   5.9%      60.1%  
12    Roberto Carballes Baena  10.1%   5.8%      59.7%  
13    Carlos Alcaraz           26.7%  14.3%      59.7%  
14    Grigor Dimitrov          23.8%  13.4%      59.3%  
15    Juan Martin del Potro    26.8%  12.7%      59.2%  
                                                        
      Average                  20.1%  15.2%      53.4%

The 2024 Next Gen field is bizarrely well-represented, with Shang, Basavareddy, and Van Assche leading the way. Is this the age of the deadly down-the-line forehand? Some of the same caveats apply here as with the FHP list: The youngsters have played a different sort of opponent than Nadal, Alcaraz, or (!) Borg. The clay-courters on the list also make for awkward comaprisons. For dirtballers, the down-the-line forehand is a way to build points, not end them.

It’s clear that Fonseca loves this play. He ends points in his favor (with a winner or forced error) more than anyone on this list except for Shang.

Here’s the scary thing: A few clay-court matches are severely dragging down the Brazilian’s numbers. On hard courts, he moves up to second on the list, winning 68% of points in which he hits a down-the-line forehand. The shot ends points outright an incredible 48% of the time. Delpo’s numbers, though of course against stronger competition, pale in comparison, at 60% and 39%, respectively.

Some of the difference between Fonseca and the field is that his forehand is great, period. If you’ve got an extra ten miles per hour that the average player doesn’t, that’s going to show up in every direction, not just one. And for the most part, that’s what we see in Joao’s points won when hitting each category of forehand:

FH Pts Won     Fonseca  Tour  
Cross-court        58%   54%  
Middle             52%   46%  
Down the line      59%   53%  
Inside-out         57%   57%  
Inside-in          54%   59%

He’s better than average in all but the rarest of the five forehand directions. Even that isn’t really a negative: On hard courts he does better than tour average with the inside-in forehand.

The eye-catcher on that chart is 52% of points won when hitting a down-the-middle forehand. The typical player is likely to lose a point when hitting that shot. That’s not necessarily because down-the-middle forehands are bad, but because if you need to hit one, the point probably isn’t going your way. Unlike the other categories of forehands, it’s usually a defensive shot.

Of the 220-plus players with as many down-the-middle forehands as Fonseca in the MCP database, only 23 win more than half of those points. The Brazilian ranks fourth by points won when hitting down-the-middle forehands. It’s another oddball list, with Pablo Andujar, Tim Smyczek, Gilles Simon, and Carlos Berlocq rounding out the top five. (Yes, really.) To the extent we can group them together, those four men played a different brand of tennis, winning points with conservative shots as they wore down their opponents.

The more telling stat is that Fonseca actually ends points by clubbing forehands down the middle. The average player hits a winner or induces a forced error with less than 2% of these strokes. Joao comes in at 6.4%, better than anyone else in the dataset:

Rank  Player               W/FE%  inPtsWon%  
1     Joao Fonseca          6.4%      52.8%  
2     Fernando Gonzalez     6.0%      43.2%  
3     Christopher Eubanks   5.7%      38.8%  
4     Thanasi Kokkinakis    5.0%      46.1%  
5     Tomas Machac          4.9%      43.8%  
6     Nicolas Jarry         4.7%      41.7%  
7     Alexei Popyrin        4.4%      41.8%  
8     Sam Querrey           4.3%      41.8%  
9     Max Purcell           4.0%      38.5%  
10    Lorenzo Sonego        3.9%      46.0%  
11    Matteo Arnaldi        3.8%      49.5%  
12    Lucas Pouille         3.4%      42.9%  
13    Jan-Lennard Struff    3.3%      45.6%  
14    Matteo Berrettini     3.3%      42.1%  
15    John McEnroe          3.3%      44.0%  
16    Otto Virtanen         3.2%      35.8%  
17    Boris Becker          3.2%      44.1%  
18    Nick Kyrgios          3.2%      43.2%  
19    Roger Federer         3.2%      47.6%  
20    Carlos Alcaraz        3.2%      50.2%

When you can end points with your forehand twice as often as Federer did, you’re doing something right. The only players even close to the Brazilian’s winner rate end up losing far more points, probably because they need to take many more risks to get that small sliver of positive outcomes.

One more time for the road: Fonseca’s numbers are probably inflated due to his level of competition. In 2025, we’ll see how his forehand holds up against the elites. If we revisit these numbers twelve months from now, he’ll probably come down a notch. But raw power plays at every level. No matter who stands across the net, Fonseca’s forehand is fearsome–in all directions.

* * *

Subscribe to the blog to receive each new post by email:

 

Can Learner Tien Hang With the Big Boys?

Learner Tien at the 2024 US Open. Credit: Hameltion

Learner Tien has done little in 2024 except win. He reeled off a 28-match streak from May to late July, collecting five titles, including his first at the Challenger level. He reached the quarter-finals at the tour event in Winston-Salem. After picking up two more Challenger crowns and another final, the young American opened his NextGen Finals campaign yesterday with a victory over top-50 player Jakub Mensik, 21st on the Elo list.

If you don’t follow prospects, you can be forgiven if you’ve only recently learned the name. Tien is only two weeks removed from his 19th birthday. He opened the year only barely inside the top 500. There were plenty of reasons to expect big things from the young man–a national 18s title at 16, two junior slam finals–but it would have been foolish to predict so much, so soon.

One reason to moderate expectations is simply age. For those not named Alcaraz or Sinner, it takes time to develop into a top player. Only one man under the age of 21–the cutoff for this week’s event in Jeddah–is ranked inside the top 40. Before Tien turned 19 this month, he was the top-ranked 18-year-old in the world, even with a triple-digit number next to his name.

The climb to the top is even more challenging for youngsters who can’t rely on pure power. Mensik, the highest-ranked teenager, is six feet, four inches tall, with weapons that make him seem bigger. Novak Djokovic recently called him “one of the best servers we have in the game.” The Czech has plenty to learn, and he will surely continue to refine his game. But to compete at the top level, he doesn’t have to.

Tien doesn’t have that luxury. He stands five inches shorter than Mensik. While he may have a bit more growth coming, five-eleven is near the bottom edge of what can be managed on the ATP tour. Only 15 members of the top 100 stand less than six feet, and even that list is skewed toward clay-court specialists. Sebastian Baez is the only five-foot-anything ranked above 45th.

The playing styles available to shorter athletes are limited, especially on hard courts. Tien has already demonstrated his mastery of many of those tactics. He can use his left-handedness to swing serve after serve wide, to a righty’s backhand. He is sturdy from the baseline, and you can take that literally: He’s unafraid of claiming territory right up to the line itself, taking advantage of both his quickness and raw speed. Fearless counterpunching has paid dividends for smaller stars from Olivier Rochus to Kei Nishikori to Alex de Minaur. As a lefty, the American has options those men didn’t.

Still, Tien’s transition from the Challenger tour to the big leagues could be rocky. Good defense and well-executed tactics are enough to clean up against top-200 competition. The combination was (just barely) sufficient against Mensik yesterday. But a full-time spot on the ATP tour requires more.

The game plan

For such a middling server, Tien wins a remarkable number of serve points. He ranks among the top quarter of Challenger tour regulars by serve points won, though his number is helped a bit by spending the entire year on hard courts. He does even better–64.6% compared to a tour norm below 62%–when aces and double faults are taken out of the equation. When the returner gets a racket on the ball, only ten players were better on hard courts.

It’s not surprising, then, that Tien excels on return. Among Challenger players with at least ten matches at the level in 2024, only two men–Dalibor Svrcina and his fellow American in Jeddah, Nishesh Basavareddy–topped Learner’s 42.5% clip. Tien is particularly effective converting second-serve return points.

He’s even better–or at least, he has been better this season–with more on the line. His rate of return points won rises to nearly 47% on break point chances, and he’s just as clutch on the other side of the ball. He saved 65.6% of the break points he faced, second at Challenger level to Mikhail Kukushkin. Here, he has already learned how to use the lefty serve, alternately forcing opponents far out wide and sticking them with uncomfortable body serves when he catches them leaning left for the slider.

The overall package is something between those of two other left-handers, Adrian Mannarino and Cam Norrie. Mannarino, also a sub-six-footer, throws the kitchen sink at opponents, keeping them off balance to compensate for his own lack of power. Norrie is considerably taller and has more firepower at his disposal. But he, too, refuses any rhythm to the man across the net. He alternates a loopy forehand with a flat backhand–except when he doesn’t, if you ever think you’ve found a groove.

Tien serves like Mannarino out of necessity. Even if he doesn’t get taller, the American will surely get stronger, so his 90-mile-per-hour first serves from this year’s US Open probably won’t tell the story of his entire career. But at the moment, he relies on angles and variety. Mannarino has overcome his limitations to the tune of a top-20 peak ranking. On the other hand, his playing style (and the comically loose string tension it relies on) is so unique he hardly provides an example to follow.

In the Las Vegas Challenger final back in September, Tien looked particularly like Norrie. Fighting the wind, he spun forehands and zinged backhands, a combination that made it impossible for the bigger-hitting Tristan Boyer to get comfortable. In other settings, though, the youngster is increasingly using his forehand as a (flatter) weapon, building points one sharp angle at a time.

The most instructive element of these comparisons, though, is the way in which the American differs from his fellow lefties. Mannarino reached Tien’s current ranking when he was 21, after more than 250 pro matches. Norrie–who ultimately peaked inside the top ten–played three years of college tennis and didn’t approach the top 100 in the world until he was 22. Tien, by contrast, is clearing all these hurdles on the first try. Deploying a brainy playing style that normally takes years to refine, the American is making it look natural.

The projection

Aside from size and serve speed, Tien’s future looks bright. The 19-year-old has won 61 of 73 matches across all levels this year. Within a few months, he is likely to crack the top 100. At Challenger level, his serve hasn’t held him back: As we’ve seen, he wins more service points than most of his peers, despite gaining fewer free points with the serve itself.

The question, then, is what effect Tien’s attributes have on career trajectory. Everyone wins fewer points at tour level than at Challengers–the competition is better, so it would be weird if it were otherwise. But the ratio isn’t uniform. Mannarino has won about 7% fewer serve points at tour level than he did in hard-court Challenger matches, while Marcos Giron (another sub-six-footer) lost less than 1% in the transition.

These Challenger-to-tour conversions offer some insight into Learner’s future. Since he has played almost all of his pro matches on hard courts, we’re going to calculate something a bit quirky. How do serve and return win rates change from hard-court Challenger matches to all tour-level matches? That’s what we want to know for the 19-year-old: He’ll need to play on all surfaces soon, probably starting in 2025. This transition he’s about to make–how did it go for other players?

The first-pass answer is that pros are able to retain something like their hard-court Challenger serve win percentage, seeing that number drop by 2%. But they lose a lot against tougher competition on return, winning 7.1% fewer return points. The following table shows those numbers (“Conv%”), along with Tien’s career record at hard-court Challengers (“Tien CH”), along with what the conversion factors suggest for his tour-level win rates (“Tien Adj”):

        Conv%  Tien CH  Tien Adj  
Serve   98.0%    63.3%     62.0%  
Return  92.9%    42.3%     39.3%

Those are awfully respectable numbers. 62% serve points is marginal for a tour regular, but combined with 39.3% return points, it’s enough. The combination is about what Francisco Cerundolo managed this year, and he’s ranked 30th in the world.

A word of caution: This type of conversion is not suggesting that Tien’s level is the same as Cerundolo’s now. The calculation involves taking each active player’s career records in tour and Challenger main-draw matches. That probably underestimates Tien’s potential, because most men play the majority of their Challenger matches after their 19th birthday. But a player’s career numbers will include their peak, which typically comes much later. At the very least, these numbers suggest Tien could reach Cerundolo’s level (or better) eventually.

The (other) adjustments

That’s just a first-pass number, because we haven’t gotten to height and handedness. Taking those into account does not help Learner’s case.

Lefties, it turns out, have a rougher transition than right-handers do. Here are the serve and return conversion factors, separated by hand:

        Lefties  Righties  
Serve     97.3%     98.1%  
Return    92.1%     93.0%

Not a huge difference, but hey, the margins in tennis are small. I suspect it is slightly harder for left-handers to move up a level for two reasons. First, the less experienced the opponent, the more valuable it is to be unusual, and lefties are certainly that, making up barely one-tenth of the player pool. At tour level, the novelty is gone: ATP regulars generally know how to handle left-handers.

Second, lefties are more likely to get by with what we might call “crafty” tennis, rather than power. (That’s related to the first reason: They’ve reached Challenger level because they’ve outsmarted inexperienced opponents thus far.) Craftiness might be enough against #180 in the world, but against, say, the Hurkacz serve, all craftiness gets you is a few more tuts of approval in the press box.

Whatever the reason, Tien’s left-handedness means we need to update our tour-level forecast:

    (L) Conv%  Tien CH  Tien Adj  
Serve   97.3%    63.3%     61.6%  
Return  92.1%    42.3%     39.0%

Not a huge hit, but ~0.4% of total points won is roughly equivalent to four places in the rankings. A small number here ultimately translates to much bigger ones when denominated by tour-level prize money.

And then, size. Here are the conversion factors for players in three height categories: under six feet, from six feet to six-foot-three, and above six-foot-three:

        under 6'0  6'0 to 6'3  over 6'3  
Serve       97.0%       97.9%     99.0%  
Return      92.0%       93.4%     92.6%

Again, craftiness doesn’t convert. Players under six feet tall lose the most points between hard-court Challengers and tour level. The tallest players remain almost as effective on serve, while the middle category retains the most of their return effectiveness.

Here’s the Tien update, using the sub-six-feet conversion rates:

        (< 6') Conv%  Tien CH  Tien Adj  
Serve          97.0%    63.3%     61.4%  
Return         92.0%    42.3%     38.9%

Not much of a difference from the left-handed numbers, though we keep going down. This is increasingly the profile of a clay-court specialist, and we might be outside the top 40 now.

Of course, Learner is both left-handed and (relatively) small. My mini-study of active players doesn't give us a big enough pool of data to extrapolate from the small group of small lefties. Instead, a back-of-the-envelope combination of the two factors gives us conversion factors of 96.3% for serve and 91.3% for return:

        (L&Sm) Conv%  Tien CH  Tien Adj  
Serve          96.3%    63.3%     61.0%  
Return         91.3%    42.3%     38.6%

For the first time, the adjusted versions of Tien's Challenger-level stats are underwater, summing to less than 100%. Winning 61% of service points would rate fourth-worst in the current ATP top 50, just ahead of Sebastian Baez. 38.6% on return is respectable, though not enough to consistently challenge for titles when combined with such a mediocre serve.

The exact numbers are not important: For one thing, we don't have enough recent data to know exactly how size and handedness interact. Maybe it's not quite that bad. Suffice it to say that both lefties and undersized players are more likely to struggle in the transition from Challengers to the full tour. A player who fits both categories should not expect a smooth trip up the ladder.

For Tien to beat these projections, all he has to do is improve more than the average pro does. As noted above, he already has something of an edge: He posted most of his excellent Challenger numbers as an 18-year-old. That's Alcaraz territory. At the same age, Mannarino was struggling at Futures level, and future top-tenner Norrie was headed off to college. If for some reason Tien plays a lot of Challenger matches in 2025, his stats will probably look better, and the tour-level predictions would change as well.

As Learner and his team are undoubtedly aware, those improvements need to center on the serve. The youngster probably already has what it takes to break serve once or twice a set on tour. But without a bigger first-strike weapon, he'll struggle to get those opportunities. Yesterday he withstood Jakub Mensik's event-record 24 aces, winning in a fifth-set tiebreak despite losing 14 more total points than Mensik did. The American played brilliant tennis, yet it took luck and brilliant timing to pull out the victory. For a five-foot-eleven left-hander among the giants of the professional game, it's not the last tightrope he'll have to walk.

* *

Subscribe to the blog to receive each new post by email:

 

The Tensions of Exhibition Tennis

The 2019 Laver Cup. Credit: Sportsfan77777

2024 was a good year for exhibition tennis. The Saudi-banked Six Kings Slam set a new standard for prize money. Rafael Nadal and Carlos Alcaraz took the long tradition of Las Vegas tennis challenges to Netflix. The Ultimate Tennis Showdown made three glitzy stops. Novak Djokovic helped Argentina celebrate Juan Martin del Potro. Even Scandinavia got involved, with a home-and-home duel showcasing Casper Ruud and Holger Rune.

The tennis season is long. Put enough money on the table, though, and it can always get longer.

Exhibitions tend to highlight the gaps between the game’s haves and have-nots. Even the official tours are headed in that direction. The ATP and WTA aim to trim the number of small events to better focus attention on longer, 1000-level tournaments. Rumors persist of a Premier League-style “super tour” that would go even further.

It’s a delicate balance. You can’t hold exhibitions without bona fide stars. You can’t have stars without universally recognized events like Wimbledon. And you can’t have Wimbledon without a thriving ecosystem of tournaments that both identify contenders and allow future champions to develop. The Six Kings Slam was about as far as you could possibly get from an ATP 250 in Santiago, but one relies–however indirectly–on the other.

These tensions are not new. There has always been a scarcity of megastars whose celebrity transcended a couple dozen standard tour stops. Though the ultra-bankable Big Four is fading into history, other trends–exemplified by Saudi money and Netflix-style starmaking–will continue to raise the incentives for exhibition-style tennis. It’s too early to tell whether things will get better or worse, but they’ll almost certainly get different.

How did we get here?

For nearly as long as there have been tennis champions, there have been promoters trying to put them in front of more fans for more money. In 1926, Suzanne Lenglen, the greatest woman player up to that time, became the first superstar to go pro. Her 40-stop series was more like a modern concert tour than anything in the tennis world. She made $100,000 for three months’ work, the equivalent of nearly $2 million today.

Lenglen soon hung up her racket, but the template had been proven. For the final four decades of the amateur era, a rotating cast of standout players from Bill Tilden to Rod Laver slogged through grueling barnstorming tours. Apart from occasional appearances in New York, London, and Australia, it wasn’t glamorous. But it was a more reliable living than taking under-the-table “expense money” from organizers of amateur events.

It didn’t take long before the business model became clear. A pro tour could support four athletes: Two big names (preferably rivals), plus two more who could play a warm-up match, then later join their colleagues for doubles. The tour did best when one of the headliners was a recent Wimbledon champion. It wasn’t unusual for the newly-minted titlist at the All-England Club to sign a contract within days of collecting his trophy.

Attempts to broaden the base of professional tennis usually failed–or, at least, didn’t become any more than another quickie tour stop. To fill out a proper tournament field, promoters had to invite retired champions and teaching pros. The would-be pro “majors” had an appeal not unlike a senior tour event, giving fans a chance to see, say, Don Budge far past his prime.

Amateur officials, as you might expect, detested this state of affairs. Wimbledon was turned into a glorified qualifying tournament, the winner to receive a six-figure check to never appear at SW19 again. While they could have stopped the exodus by offering prize money, it’s easy to sympathize. The pro tour was a parasite, trading on the fame of stars it did nothing to create.

Won’t get fooled again

The Open era kicked off in 1968, quickly consigning amateur tournaments to also-ran status. A few players began to get rich, and it was possible to make a living as a second-tier tour regular. Within a decade, though, exhibition tennis threatened the burgeoning pro circuit.

The tennis boom of the 1970s created vast numbers of fans, and with the help of television, the era’s stars became more famous than ever before. The 1973 Battle of the Sexes was not just a turning point for women in sport. It proved the potential of a one-off spectacle. Why bother with a whole tournament when you could pit Jimmy Connors against Rod Laver at Caesar’s Palace?

In the early 70s, there wasn’t much tension between the tours and exhibitions, because the unified tours didn’t exist. A national federation might gripe about a big name skipping a circuit stop in favor of a bigger payday elsewhere, but federations were losing their grip on the sport. There was little they could do about it.

Soon, though, battle lines formed. World Team Tennis muscled their way onto the stage in 1974, offering players guaranteed contracts to play up to 60 dates from May to September. WTT was expansive enough to accommodate lesser names alongside the box office draws, but the very nature of the league made the pecking order clear. Superstars demanded six-figure deals and often forced trades so that they could play for a chosen franchise. WTT could be nearly as grueling as the old pro tours, but it beat the procession of smaller events between Wimbledon and the US Open.

By the end of the decade, the ATP and WTA had organized themselves into circuits that resemble what we have today. Stars like Chris Evert and Bjorn Borg were raking in prize money. The problem was, on the exhibition market, they were worth even more. Borg, in particular, would cash in at any opportunity, sometimes playing dozens of exhibition matches in a single season.

The men’s tour eventually responded by requiring that players enter a minimum number of sanctioned events each year, one factor in Borg’s early retirement at the age of 26. But most players were willing to compromise, entering a couple dozen official tournaments, then jetting from Europe to Japan and back to pad their bank accounts.

The compromise

Six Kings aside, we’re still far from the peak era of exhibition tennis, when Borg and Ivan Lendl played one-nighters for well-heeled fans around the globe. The ATP has steadily tweaked its rules–no exhibitions that clash with bigger tour events, for instance–while upping its own prize money.

The tours have also indirectly limited exhibitions by their own natural growth. One of the biggest exho markets in the 70s and 80s was Japan, where an increasingly rich population wanted a taste of what Westerners could enjoy at home. As the tours gave more prominence to sanctioned tournaments in Tokyo, Osaka, and elsewhere, there was less demand for one-off player appearances.

That, in short(?), is how we got here. Stars are able to play non-tour events, but only sometimes. They hardly need to, since an athlete with any kind of box office value is making seven figures in prize money, not to mention endorsements. Most localities that can support a top-tier event have got one, within the framework of the official tours.

However, it wouldn’t take much to render this equilibrium unstable.

Threat models

The biggest immediate danger to the existing structure of pro tennis is Saudi money. The nation’s Public Investment Fund basically blew up golf, poaching stars for a rival tour and leaving the sport fractured.

Fortunately, tennis officials were able to watch and learn. The Saudis have been welcomed as partners, hosting the WTA Finals and the ATP NextGen Finals, as well as sponsoring both tours’ ranking systems. The Six Kings Slam doesn’t seem like so much of a threat in the context of so much collaboration.

If the Saudis decide to make a bigger move, even that will likely be in partnership with the majors–the so-called “super tour” proposal. The resulting circuit would probably have fewer, higher-paying tournaments. By extension, it would support a smaller group of players. Breaking onto the tour would be more lucrative than ever, but many currently-fringe competitors would be stuck on an expanded version of the Challenger tour.

Maybe a super tour is imminent. I have no idea. It would certainly change the face of the sport, though not beyond recognition.

The bigger threat, as I see it, is in the longer term. Sports–not just tennis–have learned to promote their biggest stars, earlier and more persistently than ever before. Think of all the “NextGen” hype tennis fans have been subjected to for more than a decade now, since Grigor Dimitrov was a teenager. Now we’ve entered the “Drive to Survive” era, where every sport wants Netflix to do what it did for Formula 1. To grow the game–the thinking goes–stars need to develop into global icons, thus attracting new fans. Can’t just sit around and wait for the next Federer to manage it himself.

The risk is that by marketing a superstar, the value accrues to the superstar, not the sport. If more people tune into Wimbledon to watch Sinner play Alcaraz, Wimbledon reaps the benefit of the ratings and sponsorships. Yes, Sinner and Alcaraz get paid well, too, and maybe prize money goes up next year. But at what point does Wimbledon have less status than the stars themselves? When Alcaraz has his own Netflix doc and Sinner is the most popular man in Italy, who cares about the strawberries and cream?

Put another way: Imagine that the Saudis were looking to elbow their way into sport in 2008. After the epic Federer-Nadal Wimbledon final, they offered both men a ten-year, billion-dollar contract to tour the globe (with frequent stops in the Gulf), playing head to head in one sold-out arena after another. Is the offer so implausible? Are we sure that Roger and Rafa wouldn’t have taken it?

Sinner and Alcaraz are hardly Federer and Nadal–at least not yet. But their agents, and the tour’s marketing team, and a film studio or three, are trying very hard to raise them to that status. If it isn’t Sinner and Alcaraz, it’s the next generation of superstars after that. Eventually, someone, or some small group of players, will be big enough that they can sell a two-man product. Team sports don’t have to worry about that; even golf would have a hard time selling much match play. But tennis has sold two-player rivalries for a century.

That, to me, is the logical extension of exhibition tennis, the worst-case scenario that guts the sport as we know it.

Events like the Six Kings Slam, Laver Cup, and UTS are fine when there is a deep, thriving tennis ecosystem for 45 weeks a year. (I’d even settle for 35!) We are quite far, I think, from the point where the number of exhibitions threatens the tour itself. But we are closer to the more dangerous point where a small group of superstars don’t need the tour at all. Any athletes who ultimately cash in their celebrity to go it alone will do very well in the deal. But the rest of us will be left with a much less compelling sport.

* * *

Subscribe to the blog to receive each new post by email:

 

Mirra Andreeva’s Many Happy Returns

Mirra Andreeva at the 2024 Paris Olympics.
Credit: Like tears in rain

Mirra Andreeva is the best teenager on the WTA tour, and it isn’t close. She’ll finish 2024 ranked 16th on the official points table, more than one hundred places ahead of her closest teenage competitor, Maya Joint. Andreeva is a year younger than Joint, and she’s two years younger than Ella Seidel, third on the under-20 list.

Players who outpace their fellow teenagers typically go on to notable careers. Here’s the list of top teenagers at the end of each season this century:

Year  Player                    Rank  
2000  Serena Williams              6  
2001  Kim Clijsters                5  
2002  Kim Clijsters                4  
2003  Vera Zvonareva              13  
2004  Maria Sharapova              4  
2005  Maria Sharapova              4  
2006  Maria Sharapova              2  
2007  Nicole Vaidisova            12  
2008  Agnieszka Radwanska         10  
2009  Caroline Wozniacki           4  
2010  Anastasia Pavlyuchenkova    21  
2011  Christina McHale            43  
2012  Sloane Stephens             38  
2013  Eugenie Bouchard            32  
2014  Madison Keys                30  
2015  Belinda Bencic              14  
2016  Daria Kasatkina             26  
2017  Catherine Bellis            46  
2018  Dayana Yastremska           58  
2019  Bianca Andreescu             5  
2020  Iga Swiatek                 17  
2021  Emma Raducanu               19  
2022  Coco Gauff                   7  
2023  Coco Gauff                   3  
2024  Mirra Andreeva              16

There’s no such thing as a can’t-miss prospect in women’s tennis, but showing up on this list gets you pretty close. Andreeva’s case is particularly extreme, because she is still just 17 years old.

In the under-18 category, the young Russian has virtually no competition. Only three other under-18s rank among the top 200, none closer than Alina Korneeva at 176th. No woman so young has finished inside the top 20 in almost two decades, going back to Nicole Vaidisova’s top-ten showing in 2006.

Here’s another way to look at what Andreeva has accomplished. With four victories to reach the Ningbo final in October, she increased her career tour-level main-draw win count to 48. Take a look at the list of all women, post-Vaidisova, to post even 30 such wins before their 18th birthday:

Wins  Player              Last Win as 17yo  
32    Victoria Azarenka         2007-07-30  
47    Caroline Wozniacki        2008-06-23  
42    Tamira Paszek             2008-09-15  
32    Donna Vekic               2014-06-23  
33    Amanda Anisimova          2019-07-29  
64    Coco Gauff                2022-03-07  
48    Mirra Andreeva            2024-10-14

Again, good company, and think of all the stars who aren’t here. You know, everybody (besides Vekic) for a decade. In this entire time span of about 17 years, Andreeva has done more at her age than anyone except Coco Gauff. The Russian might even erase that caveat. She doesn’t turn 18 until the end of April, and this year, she had won 12 matches by that time. 17 wins–enough to surpass Gauff–is hardly out of reach.

Let’s turn now to how Andreeva is achieving so much success, and why she might soon lop a digit off of her age-defying ranking.

Returns first

Forget about all this under-18 and teenager stuff for a minute. Mirra is already one of the best returners in the game. Here are the top dozen WTA tour regulars, ranked by return points won:

This isn’t a perfect measure. For one thing, Andreeva faced one of the weaker schedules of players on this list. Her median opponent was ranked 58th, compared to 30th for Iga and 42nd for Coco. It would take considerably more work to suss out whether Andreeva’s 47.3% of return points won, against her set of opponents, is better or worse than, say, Aryna Sabalenka’s 45.3% against competition nearly as stiff as Swiatek’s.

The quibbles mean that we can’t quite proclaim the Russian a top-three returner. The point, though, is that she’s in the conversation. In fact, if we narrow our view to matches against top-20 players–limiting if not eliminating the influence of each woman’s schedule–Andreeva hangs on to her position:

(We’re not talking about Iga today, but… 47% of return points won against top-20 opponents? My word.)

Where Andreeva shines even brighter is against first serves. She won first-serve return points at a higher clip than any other woman on tour this year:

Player               1st RPW%  
Mirra Andreeva          42.6%  
Coco Gauff              42.1%  
Marketa Vondrousova     40.8%  
Iga Swiatek             40.8%  
Daria Kasatkina         40.7%  
Marta Kostyuk           40.5%  
Elina Avanesyan         40.0%  
Jasmine Paolini         40.0%  
Katerina Siniakova      39.5%  
Karolina Muchova        39.5%

Put that in perspective: Andreeva wins more first-serve return points than Barbora Krejcikova (to pick one name from several) wins all return points.

Again, the Russian’s stats are influenced by her level of competition. Against top-20 opponents, Mirra falls to third place, behind Swiatek and just back of Gauff. But you get the idea. To say, “Well, actually, she’s not quite up to Gauff’s standard” is to say we’re dealing with a special player.

Precocious patience

Andreeva’s serve is good for a 17-year-old, but as we’ve seen, it’s not the side of her game that has put her in the top 20. Her returns, and by extension, her baseline play, are responsible for that.

Among top players, Mirra is currently most similar to countrywoman Daria Kasatkina. The two Russians, according to Match Charting Project data, post average rally lengths of 4.9 strokes, more than anyone else in the top 40. Both women are effective off both wings; Andreeva’s backhand is the better of the two, while Kasatkina’s forehand scores more points. The teenager is a bit more likely to force the issue: While both rank well below average in Rally Aggression Score, Mirra is closer to the norm.

A key difference shows up in their rally breakdowns. Again based on the subset of matches logged by the Match Charting Project, here are each woman’s percent of points won at various rally length categories:

Player     1-3 W%  4-6 W%  7-9 W%  10+ W%  
Andreeva    49.8%   48.6%   51.8%   53.8%  
Kasatkina   48.0%   45.6%   51.0%   52.5%

The first thing that pops out here is that Andreeva is better in every category, something that reflects both the vagaries of the uneven tennis schedule and the non-random nature of Match Charting Project samples. However you slice it, Mirra won more points, though my Elo rankings agree with the official formula that Kasatkina was the better player.

To get a better idea of what we’re looking at, let’s normalize each woman’s rally-category splits as if they won exactly half of their overall points:

Player     1-3 W%  4-6 W%  7-9 W%  10+ W%  
Andreeva    49.5%   48.3%   51.5%   53.5%  
Kasatkina   49.6%   47.1%   52.7%   54.2%

The teenager holds the edge in the 4-6-stroke category, while Kasatkina looks better in the longer rallies.

That 4-6-shot category tells us more than it lets on. Andreeva’s 48.3% (or the un-normalized 48.6%) doesn’t look very impressive. Points in this group account for one quarter of all the points she plays, and she loses more than half.

But consider her playing style. Medium-short rallies are often determined by the lingering influence of the serve: The returner might withstand a plus-one attack, only to leave a sitter for the server to put away. Or a strong return doesn’t finish the point, but the returner’s next shot–the fourth stroke of the rally–does the job. 4-6-shot rallies go disproportionately to big hitters: Aryna Sabalenka led the category this year.

For someone like Andreeva or Kasatkina, the task is to limit the damage. Get the serve back, try to neutralize the point. Place serves where aggressive returners won’t do too much damage. If a big return comes back, play the same defense that works against the serve. Kasatkina has all of those skills, but there is only so much she can do. Mirra, with her flatter strokes and somewhat bigger weapons, can keep opponents from running away with these medium-short points. She’ll lose sometimes to the likes of Sabalenka, but unless they catch her on an off day, she won’t be blown off the court.

Growth potential

If Andreeva could be characterized as a younger, somewhat more aggressive Kasatkina, that would be a pretty good compliment for a 17-year-old. But the teenager promises to become much more.

One of my favorite bits of counterintuitive tennis wisdom is that return stats rarely improve. Returning is based on a set of skills–anticipation, quickness, speed–that, on net, decline with age. Whatever tactical savvy a player picks up as she ages will, at best, cancel out the age-related decline. This isn’t an iron law, but it’s surprising how often players reach their peak return effectiveness very early in their careers.

The same is not true for the serve. 17-year-olds (or, hey, 23-year-olds) have the capacity to get stronger. Footspeed and reaction time don’t figure into the serve, so with better coaching or targeted practice (think late-career Djokovic), serve stats can improve even as the rest of a player’s game declines. A couple of examples: Maria Sakkari steadily improved her first-serve win rate from the 13th percentile to the 93rd percentile in five years. Simona Halep’s first-serve was in the top quarter of tour regulars in 2014; two years earlier, it had been one of the WTA’s worst.

The implications for Andreeva are clear. We don’t need to wishcast an improvement in her return game: She’s already one of the best returners in the game. Instead, the road to the top ten and beyond goes through her serve. Her results so far are adequate. She won 58.4% of her serve points in 2024, compared to a top-50 average of 58.7%. When we consider how much she played on clay, that number looks a bit better. On hard courts, she won more serve points than average.

Mirra, then, doesn’t face the same uphill struggle that Sakkari and Halep overcame. Her potential trajectory is more like, say, Victoria Azarenka’s. Vika arrived on the scene as a killer returner with a good-enough serve. In 2009 and 2010, she won nearly half of her return points against 58% to 59% of her service points. That combination earned her two top-ten finishes. (She was a few years older than Andreeva at that point, yet another reminder of how unique the Russian’s early success has been.)

Two years later, Azarenka boosted her rate of serve points won to 61%. Combined with the same results on return that had gotten her into the top ten, the bigger serve earned her six titles–including her first major–and the year-end number one ranking. 59% to 61% may not sound like much, but for an elite returner, that’s all it takes.

If Andreeva did the same, lifting her 58.4% serve-point win rate to 61%, she’d be the ninth-best server on tour. Remember how she’s just a tick behind Coco Gauff on return? A Vika-like serve boost would put her ahead of the American in that category, outweighing Coco’s narrow edge on return. Shorter version: She’d be a top-three player, maybe more.

None of this is guaranteed. It may not–it probably won’t!–happen right away. For every Azarenka, there’s a Nicole Vaidisova or, worse, an injury victim like Catherine Bellis. Still, few paths to the top are marked so clearly. For Mirra Andreeva, a modest, achievable set of improvements are all that stand between her and the top.

* * *

Subscribe to the blog to receive each new post by email:

 

How Does Jannik Sinner’s Season Stack Up?

Jannik Sinner, defying gravity

Jannik Sinner just wrapped up a season for the ages. He won both hard-court majors, three Masters 1000s, and the Tour Finals. He led Team Italy to a Davis Cup championship and ended his campaign on a 26-set winning streak.

By November, the Italian was no longer competing against the field: He was gunning for a place in the record books. He went undefeated against players outside the top 20. Not a single player straight-setted him: He won at least one set in each of his 79 matches. Only Roger Federer, in 2005, had ever managed that.

After Sinner won the Australian Open, I wrote that Yes, Jannik Sinner Really Is This Good. Since then, he got even better. In the seven-month span ending in Melbourne, the Italian held 91.1% of his service games, a mark that not only led the tour but put him in the company of some of the greatest servers of all time. For the entire 2024 season, he upped that figure to 91.5%–including thirteen matches on clay.

He also defied the most powerful force in all of sport, regression to the mean. Sinner’s hold percentage was aided by some sterling work saving break points. He won tons of service points, of course, but he was even better facing break point. The average top-50 player is worse: Good returners generate more break points, so it’s a tough trend to defy.

In the 52 weeks ending in Melbourne, Sinner had won three percentage points more break points than overall service points. I wrote then: “I can tell you what usually happens after a season of break-point overperformance: It doesn’t last.” In the Italian’s case, though, it did. In 2024 as a whole, he won 71.1% of service points, and 73.6% of break points. He would have enjoyed a productive season without repeating his break-point overperformance, but those two-and-a-half percentage points explain much of the gap between very good and historically great.

Clubbable

Most players who serve so effectively are middling returners. The Italian has bucked that trend as well.

Late in 2023 I wrote about tennis most exclusive clubs–Alex Gruskin’s method for identifying standout players by their rankings in the hold and break percentage categories. It’s rare for anyone to crack the top ten in both. In 2023, Sinner signaled what was coming by finishing in both top fives. He ranked fifth by hold percentage and fourth by break percentage. Most seasons, that would have been enough for a year-end number one, but Novak Djokovic was even better, finishing in the top three on both sides of the ball.

Sinner, as we’ve seen, served even better this year. His 91.5% hold percentage was well clear of the pack, even with the resurgence of countryman Matteo Berrettini and increased time on tour from rocket men Ben Shelton and Giovanni Mpetshi Perricard. Last season, Djokovic led the tour by holding 88.9% of his service games. That’s impressive, especially for a guy known for other parts of his game, but it wouldn’t have cracked the 2024 top three. The Italian set a new standard.

At the same time, his return barely flagged. He fell out of the the top five by the narrowest of margins, winning nearly as many return games as he did in 2023 but falling to sixth place. Still, a “top-six club” showing is plenty rare. The only players who have posted one since 1991 (when these stats became available) are Djokovic, Nadal, Federer, and Andre Agassi. Federer only managed it once. Sinner has now done it twice.

The Italian’s return skills are even more impressive when we compare him the other season-best servers of the last thirty-plus years. The following table shows the hold-percentage leader for each year, along with his break percentage and his rank (among the ATP top 50) in that category:

Year  Player             Hold%   Brk%  Rank  
1991  Pete Sampras       87.3%  25.4%    40  
1992  Goran Ivanisevic   88.8%  20.4%    48  
1993  Pete Sampras       89.6%  27.7%    19  
1994  Pete Sampras       88.4%  29.3%    19  
1995  Pete Sampras       89.0%  26.0%    25  
1996  Pete Sampras       90.8%  20.8%    43  
1997  Greg Rusedski      91.6%  16.7%    50  
1998  Richard Krajicek   89.2%  21.4%    41  
1999  Pete Sampras       89.7%  21.7%    44  
2000  Pete Sampras       91.7%  18.4%    49  
2001  Andy Roddick       90.4%  19.7%    45  
2002  Greg Rusedski      88.5%  17.6%    48

Year  Player             Hold%   Brk%  Rank    
2003  Andy Roddick       91.5%  20.9%    43  
2004  Joachim Johansson  91.9%  14.5%    48  
2005  Andy Roddick       92.5%  20.8%    45  
2006  Andy Roddick       90.5%  22.4%    43  
2007  Ivo Karlovic       94.5%   9.8%    50  
2008  Andy Roddick       91.2%  19.2%    40  
2009  Ivo Karlovic       92.2%  10.3%    50  
2010  Andy Roddick       91.1%  17.6%    47  
2011  John Isner         90.7%  12.9%    50  
2012  Milos Raonic       92.7%  15.1%    49  
2013  Milos Raonic       91.4%  15.7%    49  
2014  John Isner         93.1%   9.3%    49  

Year  Player             Hold%   Brk%  Rank  
2015  Ivo Karlovic       95.5%   9.6%    50  
2016  John Isner         93.4%  10.9%    49  
2017  John Isner         92.9%   9.6%    50  
2018  John Isner         93.8%   9.4%    50  
2019  John Isner         94.1%   9.7%    49  
2020  Milos Raonic       93.9%  18.0%    44  
2021  John Isner         91.1%   8.8%    50  
2022  Nick Kyrgios       92.9%  19.3%    40  
2023  Novak Djokovic     88.9%  28.8%     3  
2024  Jannik Sinner      91.5%  28.3%     6

If it hadn’t been for Djokovic’s appearance at the top of last year’s list, Sinner’s 2024 campaign would be hardly recognizable. Even Pete Sampras struggled to hold on to a spot in the break-percentage top 20. Circuit-best servers simply aren’t supposed to win so many return games, yet Sinner threatens to make it the new normal.

Carrot yElo

The Italian’s 73 wins, including 18 against the top ten, took his Elo rating to new heights. He began the year with a career-high rating of 2,197, second on the circuit to Djokovic. He quickly took over the top spot, ultimately clearing the 2,300 mark with his victory at the Tour Finals.

Elo is not a perfect measure to compare players from different eras, but in my opinion, it’s the best we’ve got. It’s the basis of my Tennis 128, which Sinner will join as soon as I get around to updating the calculations. 2,300 is rarefied air: In the last half-century, he is only the twelfth player to reach that mark. With three singles victories to secure the Davis Cup, he nudged his rating up to 2,309, surpassing Mats Wilander and establishing the eleventh-highest peak since the formation of the ATP.

A stratospheric Elo is an indication of an outstanding player at the top of his game, but the metric is not designed to rate seasons. The alternative is yElo, a variation I devised for exactly this purpose. yElo works the same way as Elo does, adding or subtracting points based on wins, losses, and the quality of opposition. But unlike the more traditional measure, each player starts the season with a clean slate.

By regular Elo, Sinner holds a 150-point lead over second-place Carlos Alcaraz. By yElo, with its narrower focus, the Italian is even more dominant:

(The won-loss records are a bit different from official figures because my Elo and yElo calculations exclude matches that ended in retirement.)

The two-hundred-point gap between Sinner and Djokovic is one of the largest ever. Again going back to 1973, it ranks fourth. Only 2004 and 2006 Federer (over Lleyton Hewitt and Nadal, respectively) and 1984 John McEnroe (over Wilander) outpaced the competition by such a substantial margin.

By raw yElo, Sinner’s 2024 isn’t quite so historic. It’s the 26th best of the last half-century: An impressive feat, but not as close to the top of the list as some of the other trivia suggests. Here’s the list:

Year  Player              W-L  yElo  
1979  Bjorn Borg         84-5  2499  
1984  John McEnroe       82-3  2476  
2015  Novak Djokovic     82-6  2458  
1985  Ivan Lendl         82-7  2440  
2016  Andy Murray        78-9  2416  
2013  Novak Djokovic     74-9  2408  
1976  Jimmy Connors      97-7  2406  
1977  Bjorn Borg         78-6  2403  
1977  Guillermo Vilas  133-13  2401  
2006  Roger Federer      91-5  2399  
1980  Bjorn Borg         70-5  2395  
1981  Ivan Lendl        96-12  2383  
1987  Ivan Lendl         73-7  2381  
1982  Ivan Lendl        105-9  2380  
1978  Jimmy Connors      66-5  2379  

Year  Player              W-L  yElo  
2013  Rafael Nadal       74-7  2373  
1986  Ivan Lendl         74-6  2369  
2011  Novak Djokovic     63-4  2367  
2005  Roger Federer      80-4  2364  
2014  Novak Djokovic     61-8  2363  
2012  Novak Djokovic    73-12  2360  
1978  Bjorn Borg         79-6  2359  
2008  Rafael Nadal      81-10  2352  
1986  Boris Becker      69-13  2347  
1982  John McEnroe       71-9  2341  
2024  Jannik Sinner      72-6  2339  
1983  Mats Wilander     80-11  2338  
1974  Jimmy Connors      94-5  2332  
1989  Boris Becker       64-8  2329  
2015  Roger Federer     62-11  2329

One factor holding back Jannik’s 2024 is the number of matches played. Elo, in part, reflects the confidence we have in a rating. Winning 90% of 100 matches (or almost 150, in the case of Vilas) gives us more confidence in an assessment than 90% of 80 matches.

Another issue is that Elo has opinions about strong and weak eras. Going 70-5 in 1980 doesn’t look much different than 72-6 today, but Elo considers Bjorn Borg’s peers to have been stronger than Sinner’s. If Sinner and Alcaraz continue to improve and a couple of their peers emerge as superstars in their own right, then a 72-6 season might rank much higher.

The asphalt jungle

A couple of months ago, pundits started mulling where Sinner’s 2024 stood among the greatest hard-court seasons of all time. Since then, he piled on so many more wins that the qualifier wasn’t needed. Yet it remains a valid question.

The Italian’s highlights came almost entirely on hard courts. He won 53 of 56 matches, 42 of them in straight sets. He’s plenty skilled on natural surfaces, but given a predictable bounce and conditions that emphasize his power and penetration, opponents don’t stand a chance.

I don’t publish surface-specific yElo ratings, because they have limited usefulness for much of the year. For our purposes, though, hard-court yElo–same algorithm, limited to matches on one surface–is just the ticket. By this measure, Sinner’s 2024 is the eighth-best of all time:

Year  Player          Hard W-L  Hard yElo  
2015  Novak Djokovic      59-5       2426  
2013  Novak Djokovic      53-5       2413  
2012  Novak Djokovic      48-5       2377  
2005  Roger Federer       49-1       2374  
2006  Roger Federer       59-2       2373  
1995  Andre Agassi        52-3       2370  
2016  Andy Murray         48-6       2363  
2024  Jannik Sinner       52-3       2353  
2010  Roger Federer       45-7       2338  
2014  Novak Djokovic      40-6       2334 

Year  Player          Hard W-L  Hard yElo   
2014  Roger Federer       56-7       2333  
1985  Ivan Lendl          29-3       2332  
1987  Ivan Lendl          33-2       2325  
1996  Pete Sampras        46-4       2319  
2015  Roger Federer       38-6       2318  
1981  Ivan Lendl          41-3       2317  
2011  Roger Federer       45-7       2314  
2009  Novak Djokovic     53-10       2309  
1985  John McEnroe        25-1       2309  
1986  Ivan Lendl          30-2       2298

So, um, peak Djokovic was pretty good, huh?

Even though Elo doesn’t hold the rest of the 2024 field in particularly high regard, Sinner’s season was so dominant that he does well by this measure. A year that would rate as Djokovic’s fourth-best, Federer’s third, or Agassi’s second, is truly something worth celebrating.

The Italian still has some ground to cover before he challenges Novak, Roger, and the rest for all-time hard-court dominance. But he has already upped the standard for the 2020s and posted one of the most remarkable two-year spans in the game’s history. Sinner has built an enormous gap between himself and the field, and it is increasingly difficult to see how his peers will close it.

* *

Subscribe to the blog to receive each new post by email:

 

Jasmine Paolini’s High-Wire Act

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

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

Paolini is 28.

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

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

Then she started winning.

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

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

Opportunistic effects

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

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

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

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

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

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

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

The new game plan

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

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

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

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

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

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

The plus-two forehand

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

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

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

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

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

And the no-fearhand

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

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

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

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

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

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

The way forward

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

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

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

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

* *

Subscribe to the blog to receive each new post by email:

 

The Riddle of the Ruud-Rublev Reversal

Andrey Rublev and Casper Ruud

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

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

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

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

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

Not so fast

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

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

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

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

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

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

Stoppable

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

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

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

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

When it works…

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

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

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

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

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

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

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

* * *

Subscribe to the blog to receive each new post by email: