Category: Serve statistics

Anatomy of Alex de Minaur’s Serving Masterclass

The ATP Atlanta event is typically packed with big servers. John Isner won five titles in six years between 2013 and 2018, during which time the only man to stop him was Nick Kyrgios–in two tiebreaks, naturally. The last champion before Isner took over was Andy Roddick. It’s a fast hard court and the weather is often scorching, so the tournament tends to be a week-long ace festival.

The 2019 titlist posted another wave of eye-popping service numbers, winning four matches without facing a single break point, and winning more than 90% of his first serve points in each match. Those positively Isnerian numbers didn’t belong to the big man himself, nor were they posted by heir apparent Reilly Opelka. The serve king in Atlanta this year was the “six-feet tall” (sure, buddy) Australian grinder, Alex de Minaur.

Unlike many of his peers, de Minaur doesn’t make his money with a big serve. In the last 52 weeks, both Isner and Opelka have hit aces on one-quarter of their serve points. The Aussie’s 52-week rate is a mere 4.5%. He posted a tour-level career best of 14.8% against Taylor Fritz in the Atlanta final (excluding a Bernard Tomic retirement), but failed to reach double digits in second round against Bradley Klahn, or in the semi-final against Opelka. Last week, de Minaur proved that there are a lot of ways to win serve points without necessarily piling up the aces.

Strike one

The easiest non-ace route to victory is the unreturned serve. Players don’t have the same level of control over the rate of unreturned serves that they do with aces. But many great serves are reachable–if not effectively returnable–so they don’t go down in the ace column. The unreturned-but-not-ace category was de Minaur’s bread and butter in Atlanta.

According to the point-by-point log of the final in the Match Charting Project dataset, Fritz put only 57% of the Aussie’s serves back in play. Across over 1,300 MCP-charted hard court matches from the 2010s, the ATP tour average is 70% returned serves, and de Minaur’s opponents have traditionally done even better than that. De Minaur’s unreturned-serve rate of 43% is exceptionally good, ranking in the 90th percentile of service performances. He was even better against Opelka. Only 5 of his 93 service points went for aces, but 38 more didn’t come back. That’s an unreturned-serve rate of 46%, a 94th-percentile-level showing.

Strike two

De Minaur was even better when the serve wasn’t quite as good. Coaches and commentators like to talk about the “plus one” tactic: Hit a strong serve and get in position to make an aggressive play on whatever comes back. This is where the Aussie truly excelled in the title match.

In addition to the 43% of unreturned serves against Fritz, another 26% of his service points fell into the “plus one” category: second-strike shots that his opponent couldn’t handle. Tour average is 15%, and again, de Minaur hasn’t always been this good. His average over 15 charted hard-court matches in 2018 was only 12.6%. His 26% rate on Sunday ranks in the 98th percentile among charted hard-court matches. Of the 67 single-match performances on record that were better than 26%, 15 were recorded by Roger Federer. Most players never have such a good day in the plus-one category.

Strike three

Even the best servers have to deal with the occasional long rally. In our sample of charted hard-court matches, 40% of points see the returner survive the plus-one shot and put the ball back in play. From that point, the rally is more balanced, and returners win a bit more than half of points. (That’s partly because 4-shot rallies are more common than 5-shot rallies, and so on, and because a 4-shot rally, by definition, is won by the returner. Put another way, once you exclude 3-or-fewer-shot rallies, you bias the sample toward the returner; if you excluded 4-or-fewer-shot rallies, you would bias the sample toward the server, because 5-shot rallies make up a disproportionate amount of the remaining points.)

Serving like de Minaur did, he didn’t see nearly so many “long” rallies. 22% of his service points against Fritz, and 29% against Opelka, reached four shots. Facing the typical one-dimensional big server, this is the returner’s chance to even the score. But de Minaur is known more for his ground game than his service. In the final, he won 58% of these points, good enough for the 83rd percentile in our sample.

De Minaur’s performance on longer rallies didn’t really move the needle on Sunday, mostly because he so effectively prevented points from lasting that long. But the fact that he won more than half of the extended exchanges is a reminder that a great serving performance depends on more than just the serve. On a good day, even a six-footer can post numbers that leave Isner and Opelka in the dust. It isn’t always about the aces.

The Effect of Serena’s Serve Speed

Italian translation at settesei.it

Yesterday at FiveThirtyEight, Tom Perrotta highlighted the relationship between Serena Williams’s first serve performance and her chances of winning. According to the article, Serena has won only (“only”) 74% of her first serve points over the fortnight, compared to an outlandish 87.5% when she won the title in 2010. She has never won Wimbledon while winning fewer than 75% of her first-serve points, and even the three-quarters mark is no guarantee, as she topped 77% last year en route to a second-place finish.

A lot of factors go into first-serve winning percentage, including serve placement, serve tactics, and all the shots that a player hits when the return comes back. The most obvious, though, is another category in which Serena has often topped the charts: serve speed. When Williams beat Garbine Muguruza to win the Championships in 2015, her average first serve clocked in at 113 miles per hour, the third straight match in which her typical first delivery topped 111 mph. Over her last 13 matches, she has averaged only (“only”) 106.4 mph, never exceeding 109 mph in a single contest.

How much does it matter?

It seems fair to assume that, all else equal, a faster serve is more effective than a slower one. Complicating things is the fact that all else is rarely equal: wide serves are often deadly despite requiring less raw power, more conservative serves can be easier to place, andwe haven’t even scratched the surface of the effect of spin. A faster serve isn’t always better than a slower one. But on average, the basic assumption holds true.

For each of Serena’s 23 matches at Wimbledon 2014, 2015, 2018, and 2019 (she didn’t play in 2017, and I don’t have the relevant data at hand for 2016–don’t ask), I split her first serve points into quintiles, ranked from fastest serves to slowest serves. This is a crude way of controlling for the effects of different opponents and giving us an initial sense of how much Serena’s serve speed influences the outcome of first-serve points:

Quintile     1SP W%  Avg MPH  
Fastest       80.6%    116.9  
2nd fastest   73.7%    112.2  
Middle        79.5%    108.0  
2nd slowest   73.7%    103.7  
Slowest       74.9%     98.1

Clearly, serve speed doesn’t tell the whole story. At the same time, it looks like a 117 mph serve–or even a 108 mph one–is a better bet than a 98 mph offering.

Another way to isolate the effect of serve speed is to ignore the influence of specific opponents and simply sort first serves by miles per hour. From these 23 matches, we have 43 first serves recorded at exactly 100 mph, with a corresponding winning percentage of 72.1%. Serena hit 33 first serves at 101 mph, of which she won 72.7%. While the winning percentages don’t usually move so neatly in lockstep with first serve speed, there is a general trend:

The correlation is a loose one: winning percentages at 99 mph and 103 mph are better than those at 116 mph and 117 mph, for example. We could attribute that to the possibility that the slower serves are tactically savvier, or more approximate placement of the faster deliveries, or just dumb luck, because our sample size at any specific speed isn’t that great. Still, we can draw an approximate conclusion:

Each additional two miles per hour of first-serve speed is worth an additional one percentage point to Serena’s 1st serve winning percentage.

To take it one step further: Serena usually lands about 60% of her first serves, and roughly half of total points will be on her serve, so each additional two miles per hour of first-serve speed is worth an additional 0.6 percentage points of total points won. In a close match, like her 2014 loss to Alize Cornet–in which she averaged only 104 mph on her first serves and won exactly 50% of the points played–that could be the difference.

Serena in context

The same general rule cannot be applied to all women. (Several years ago, I took a similar look at ATP serve speeds, and–perhaps foolishly–I didn’t break it down by player.) I ran the same algorithm on the recent Wimbledon records of the nine other women for whom I have at least 15 matches worth of data. The effect of serve speed varies from “quite a bit” for Johanna Konta to “not at all” for Venus Williams and “I don’t understand the question” for Caroline Wozniacki.

The following table shows two numbers for each player. The “Addl MPH =” column shows the effect of one additional mile per hour on first serve winning percentage, and the “_ MPH = 1% SPW” column shows how many additional miles per hour are required to increase first serve winning percentage by one percentage point:

Player               Addl MPH =  MPH = 1% SPW  
Johanna Konta             0.89%           1.1  
Angelique Kerber          0.56%           1.8  
Serena Williams           0.48%           2.1  
Garbine Muguruza          0.47%           2.1  
Simona Halep              0.41%           2.5  
Petra Kvitova             0.29%           3.5  
Agnieszka Radwanska       0.28%           3.6  
Victoria Azarenka         0.02%          50.9  
Venus Williams            0.00%             -  
Caroline Wozniacki       -0.40%             -

Konta’s serve speed is almost twice as important to her first-serve success as Serena’s is. Her average first-serve speed in her quarter-final loss to Barbora Strycova was 99.9 mph, her lowest at Wimbledon since a first-round loss in 2014.

At the opposite extreme, we have Victoria Azarenka and Venus, for whom serve speed doesn’t seem to matter. (Venus, for one, excels at the deadly wide serve, which she converts into aces regardless of speed.) Wozniacki apparently lulls her opponents into confusion and illogic, giving her better results on slower first serves.

Serena vs Simona

These are small effects, so even the range between Serena’s slowest serving performance this fortnight (105 mph first serves against Carla Suarez Navarro) and the 2015 final against Muguruza would only have effect Serena’s total points won by about 2.5 percentage points. Nine out of ten times Williams and Halep have gone head to head, Serena has come out on top, always with more than 52.5% of total points, usually with more than 55%. That’s an ample margin of error–or, more precisely, margin of slow serving.

On the other hand, the most recent Serena-Simona contest, the only time they’ve played since 2016, was the closest of the lot. Halep is a great returner, but she is not immune to powerful serving: her rate of return points won is affected by serve speed just as much as Williams’s serve stats are. The gap between the finalists could be narrow, and Serena’s serve speed is one of the few tools completely in her own power that she could deploy to tilt the scales in her favor.

Yep, Wimbledon is Playing Slower This Year

Italian translation at settesei.it

The players are right. Wimbledon’s surface–or balls, or atmosphere, or aura–has slowed down in comparison with recent years. We’ve heard comments to that effect from Roger Federer, Milos Raonic, Boris Becker, Rafael Nadal, and many others. Raonic attributes the change to the grass, and Nadal to the balls. Regardless of the reason, the numbers back up their perceptions.

Here is an overview of several surface-speed indicators for the first three rounds of singles matches at Wimbledon, 2017-19:

                     2017   2018   2019  
Aces (Men)           8.9%  10.0%   8.5%  
Aces (Women)         4.1%   4.2%   4.1%  
                                         
Unret (Men)         36.0%  36.6%  33.3%  
Unret (Women)       25.9%  27.6%  25.2%  
                                         
<= 3 Shots (Men)    65.2%  65.6%  61.9%  
<= 3 Shots (Women)  55.3%  57.9%  55.0%  
                                         
Avg Rally (Men)       3.4    3.5    3.7  
Avg Rally (Women)     4.0    3.8    4.1

The second set of rows, "Unret," is the percent of unreturned serves. The next set, "<=3 Shots," is the percent of points that ended in three shots or less. For all four of the stats shown, including aces and average rally length, men's numbers point to slower conditions. The women's numbers are less clear, but to the extent that they point in either direction, they concur.

Not just 2019

Aggregate numbers such as these usually give us an idea of what's going on. But we can do better. The numbers above do not control for the mix of players or the length of their matches. For instance, 2019's rates would be different if John Isner, instead of Mikhail Kukushkin, had played a third-round match. The surface speed might have affected that result, but if we're going to compare ace rate from one year to the next, we shouldn't compare Isner's ace rate with Kukushkin's ace rate.

That's where my surface speed metric comes in. For each tournament, I control for the mix of servers and returners (yes, returners affect ace rate, too) to boil down each event to one number, representing how the tournament's ace rate compares to tour average. While there's more to surface speed than ace rate, aces are a good proxy for many of those other indicators, and more importantly, aces are one of the few stats that are available for every match.

The resulting score usually ranges between 0.5--50% fewer aces than average, usually on a slow clay court like Monte Carlo--and 1.5--50% more aces than average, on a fast grass or indoor hard court, like Antalya or Metz. Over the last decade, Wimbledon's conditions have drifted from the high end of that range to the middle:

Year      Men    Women  Average  
2011     1.26     1.37     1.31  
2012     1.27     1.06     1.17  
2013     1.29     1.04     1.17  
2014     1.35     1.19     1.27  
2015     1.20     1.16     1.18  
2016     1.06     1.03     1.04  
2017     1.03     1.07     1.05  
2018     1.14     0.98     1.06  
2019     1.04     0.96     1.00

The men's numbers are usually more reliable measurements, because they are based on many more aces, which means that the ace rate for any given match is less fluky. Ideally, we'd see the men's and women's speed ratings move in lockstep, but there is some noise in the calculation, and the ratings are also relative to that year's tour average, which depends in turn on the changing speeds of dozens of other surfaces.

Caveats aside, the direction of the trend is clear. There isn't a substantial difference between 2019 and the last few years, but the gap between the first and second half of the decade is dramatic.

What is less clear--and will require considerable further research--is how much it matters. In 2014, Nick Kyrgios upset Nadal in four sets, while last week, the result was reversed. How much of that can we attribute to the surface? Would faster conditions have allowed Isner to outlast Kukushkin? Kevin Anderson to hold off Guido Pella? Jelena Ostapenko to withstand Su Wei Hsieh?

For now, those questions remain in the speculation-only file. Now that we can conclude that the grass really has gotten slower, we can focus that speculation on the fates of several grass court savants, including Federer, Raonic, and Karolina Pliskova. By the end of the fortnight, they--like Kyrgios--might be wishing it was 2014 again.

Do Rallies Get Longer as Matches Progress?

Italian translation at settesei.it

Yesterday at the New York Open, Paolo Lorenzi battled through three sets to defeat Ryan Harrison. It was a notable result for a number of reasons, starting with the fact that Lorenzi is rarely seen on a hard court when there’s any other option. The 37-year-old Italian is one of the many men defying the aging curve these days, and with the victory, he’ll play at least one tour-level quarter-final for the eighth year in a row, despite not reaching his first until he was 30.

The way in which Lorenzi won the match was almost as unique as his career trajectory. Take a look at the average rally length per set:

Set  Avg Rally  
1          3.2  
2          4.0  
3          4.9

You probably don’t need me to tell you which set Harrison won. The opening frame was serve-dominated, typical of American indoor hard court events. As the match progressed, the points increasingly resembled the clay-court sparring that Lorenzi surely would have preferred.

Theorizing

The Lorenzi-Harrison match was extreme, but it tracks with what I believe to be the conventional wisdom. Throughout a match, players get better at reading their opponents’ games, cutting down on unreturned serves and making it more likely that each point will turn into a more protracted exchange. That’s the theory, anyway. There are some countervailing forces, such as fatigue, which work in the other direction, but in general we expect points to get longer.

Yesterday’s contest didn’t exactly follow that script, though. The rallies might have gotten longer because the two men better predicted each other’s shots, but it doesn’t show up so neatly in aces–Harrison hit aces on between 18% of 21% of his points in each set–or the more inclusive category of unreturned serves:

Set  Points  Unret%  
1        47   42.6%  
2        65   32.3%  
3        73   37.0%

While serve recognition may explain the rally length jump from set 1 to set 2, it goes in the opposite direction from set 2 to set 3. Yes, these are small samples, and yes, unreturned serves don’t tell the whole story. But there are signs that our initial theory is missing something.

More matches

As interesting as Lorenzi is, we’re going to need more players, and more data, to better understand what happens to serve returns and rally length over the course of a match. Let’s start with the main draw singles matches from the 2019 Australian Open. Not only are there are a lot of them, but since they are best of five, we have an opportunity to see how these trends unfold over several sets per match.

For each match, I measured the average rally length and rate of unreturned serves for each set, and then made set-by-set comparisons for the length of the match. For instance, in Lorenzi-Harrison, rally length increased by 25% from set 1 to set 2. Then, for each set, I aggregated all the matches of sufficient length to figure out how much the tour as a whole was changing from one set to the next.

The results are considerably less eye-catching than those of the Lorenzi match. In the following table, the “Avg Rally” and “Unret%” columns show the change in ratio form: If the baseline rate in the first set is 1.0, the rally length in set 2 increases by 0.8% and the number of unreturned serves goes up by 2.4%. I’ve also included example columns, showing realistic rally lengths and unreturned-serve rates for each set based on tournament averages of 3.2 shots by point and 34% of serves unreturned:

Set  Avg Rally  Ex Rally  Unret%  Ex Unret  
1            1      3.20       1     34.0%  
2        1.008      3.23   1.024     34.8%  
3        1.019      3.26   1.033     35.1%  
4        0.987      3.16   1.155     39.3%  
5        1.021      3.27   1.144     38.9%

The set-to-set differences in rally length are barely enough to qualify for the name. The shift in the rate of unreturned serves, however, is much more striking, all the more so because it moves in the opposite direction that we expected.* Perhaps fatigue–or strategic energy conservation–plays a bigger role than I thought, or servers gain more from familiarity with their opponent than returners do.

* You might wonder if the effect is an artifact of the data, that players who reach 4th and 5th sets are bigger servers. That may be true, but it’s not what we’re seeing here. I’m comparing the stats in each set to the previous set in the match itself, and then averaging the set-to-set changes, weighted by the number of points in the sets. A John Isner 5th set, then, is compared only to an Isner 4th set.

WTA to the rescue

The results are completely different for women. Here is the same data for the 127 main draw women’s singles matches at the Australian Open:

Set  Avg Rally  Ex Rally  Unret%  Ex Unret  
1            1      3.40       1     27.0%  
2        1.035      3.52   0.974     26.3%  
3        1.103      3.75   0.915     24.7%

Still not as dramatic as Harrison-Lorenzi, but the trends are more marked than for the men. The number of unreturned serves drops quite a bit, and rally length increases by an amoun that an attentive spectator might notice. Those two are related–if there are fewer unreturned serves, there are more shots per point, even if we only consider the second shot. Beyond that, there are more opportunities for longer exchanges. In any case, the set-by-set trends for women fit closer to the intial theory than the men’s results did.

As with every aggregate stat, I’m guessing that there is a huge amount of variation among players. Perhaps players who are particularly good in third sets really do return more serves or, as Lorenzi did, shift their tactics in the direction of a more favorable style of play. Looking at these types of numbers for individual competitors is a reasonable next step, but it’s one that will need to wait for another day.

Break Point Serve Tendencies on the ATP Tour

Italian translation at settesei.it

Every player has their “go-to” serve, their favorite option for high-pressure moments. At the same time, their opponents notice patterns, so no server can be too predictable. Let’s dive into the numbers to see who’s serving where, how it’s working out for them, and what it tells us about service strategies on the ATP tour.

Specifically, let’s look at ad-court first serves, and where servers choose to go on break points. For today’s purposes, we’ll focus on a group of 43 men, the players with at least 20 charted matches from 2010-present in the Match Charting Project dataset. For each of the players, we have at least 85 ad-court break points and another 800-plus ad-court non-break points. (I’ve excluded points in tiebreaks, because many of those are high-pressure as well, but it’s less clear cut than in other games.) For most players we’ve logged a lot more, including nearly 1,000 ad-court break points each for Novak Djokovic and Rafael Nadal.

First question: What’s everybody’s favorite break point serve? On average, these 43 men hit about 20% more “wide” first serves than “T” first serves on break points. (Body serves are a factor as well, but they make up only about 10% of total first serves, and comparing two options is way more straightforward than three.) That 20% difference isn’t quite as big as it sounds, since on non-break points in the ad court, players go wide about 10% more often. So while the wide serve is the typical favorite, it’s only a bit more common than on other ad-court points.

Tour-wide averages don’t tell us the whole story, so let’s look at individual players. Here are the ten men who favor each direction the most when choosing an ad-court first serve on break point:

Player                       BP Wide/T  
Philipp Kohlschreiber             2.58  
Pablo Cuevas                      2.46  
Denis Shapovalov                  1.94  
Rafael Nadal                      1.87  
Jack Sock                         1.84  
David Goffin                      1.78  
Nick Kyrgios                      1.69  
Alexandr Dolgopolov               1.66  
Dominic Thiem                     1.64  
Pablo Carreno Busta               1.58  
…                                       
Gilles Simon                      0.94  
Alex De Minaur                    0.94  
Gael Monfils                      0.90  
Feliciano Lopez                   0.83  
Tomas Berdych                     0.83  
Karen Khachanov                   0.82  
David Ferrer                      0.81  
Fabio Fognini                     0.77  
Diego Schwartzman                 0.69  
Borna Coric                       0.67

You’re probably as unsurprised as I was to find Rafael Nadal near the top of the list. The combination of Rafa and Denis Shapovalov suggests that lefties all follow the same pattern, but Feliciano Lopez swats away that hypothesis, as one of the players who most favors the T serve on break points. The other two lefties in our 43-player set, Adrian Mannarino and Fernando Verdasco, both hit more wide serves than average, so perhaps Feli is the odd man out here. We don’t have a lot of data on other contemporary lefties, so it’s tough to be sure.

Second question: How do break point tendencies compare to ad-court tendencies in general? We’ve already seen that players opt for wide first serves about 10% more than T deliveries in non-break point ad-court situations. That difference doubles on break points. These modest shifts lend themselves to an easy explanation: Most players serve a little better wide to the ad court, and under pressure, they’re a bit more likely to go with their most reliable option.

For some guys, though, there’s no “little” about it. We’ve already seen that Philipp Kohlschreiber goes wide every chance he gets on break points, more often than anyone else in our group. Yet on non-break points in the ad court, he splits his deliveries almost fifty-fifty. That’s a huge difference between break point and non-break point tendencies. He’s not alone. Borna Coric is similar (albeit less extreme) in the opposite direction, splitting his ad-court first serves about fifty-fifty in lower-pressure situations, then heavily favoring T serves when facing break point.

The next table shows the players who shift tactics most dramatically on break points. The first two columns show the ratio of wide serves to T serves on break points and on other ad-court points. The rightmost column shows the ratio between those two. At the top of the list are the men like Kohlschreiber, who go wide under pressure. At the bottom are the men like Coric. I’ve included the top ten in both directions, as well as the three members of the big four who aren’t in either category. Djokovic, for example, doesn’t let the situation alter his tactics, at least in this regard.

Player                 BP W/T  Other W/T  Wide BP/Other  
Philipp Kohlschreiber    2.58       1.04           2.49  
Nick Kyrgios             1.69       0.74           2.28  
Juan Martin del Potro    1.52       0.81           1.87  
Jack Sock                1.84       1.05           1.75  
Pablo Cuevas             2.46       1.50           1.64  
Kevin Anderson           1.18       0.74           1.59  
David Goffin             1.78       1.13           1.58  
John Isner               1.43       0.91           1.58  
Grigor Dimitrov          1.41       0.94           1.49  
Dominic Thiem            1.64       1.11           1.48  
…                                                        
Andy Murray              1.19       0.86           1.39  
Rafael Nadal             1.87       1.51           1.24  
Novak Djokovic           1.20       1.16           1.03  
…                                                        
Stan Wawrinka            0.99       1.15           0.87  
Roberto Bautista Agut    1.38       1.60           0.86  
Fabio Fognini            0.77       0.91           0.85  
Roger Federer            1.08       1.35           0.80  
Benoit Paire             1.36       1.73           0.78  
Adrian Mannarino         1.45       1.86           0.78  
Diego Schwartzman        0.69       0.89           0.78  
Feliciano Lopez          0.83       1.09           0.76  
Borna Coric              0.67       0.97           0.69  
Karen Khachanov          0.82       1.25           0.66

Some of the tour’s best servers feature near the top of the list. While many of them favor the ad-court T serve in general, they go wide more often under pressure. This tactic offers an explanation of why some players outperform (at least sometimes) on break points and in tiebreaks. Nick Kyrgios, for instance, is deadly serving in all directions, but in the ad court, he’s even better out wide. Overall, he wins 78.8% of his wide first serves in the ad court, against 75.8% of his T first serves. By “saving” the wide serves for big moments, he is able to defend more break points than his overall ad-court record would suggest. The same theory applies to tiebreaks, where a player could deploy their favored serve more often.

Third question: Could these tactics be improved? I usually start with the assumption that players know what they’re doing. If Kyrgios goes down the middle most of the time and then out wide more often on break points, it probably isn’t a random choice. There’s an easy rule of thumb to check whether servers are making optimal choices, which my co-podcaster Carl Bialik described a few years ago:

If your T serve is better than your wide serve, hit the T serve more. But don’t hit it 100 percent of the time because if you do, your opponent knows you’ll hit it and can stand in the middle of the court waiting for it instead of guarding against the wide serve. So how often should you hit it? Exactly as often as it takes to make it just as successful, but no more, than when you hit a wide serve. If your success rates on different choices are different, you’re not serving optimally.

For instance, facing break point in the ad court, Kyrgios wins 79.7% of his wide first serves and 76.1% of his T first serves. By Carl’s game-theory-derived logic, Kyrgios should be going wide even more often. His win rate on wide serves will go down a bit, as returners find him more predictable, but the average result of all of his break point serves will go up, as he trades a few T serves for more successful wide deliveries.

On average, our 43 players have a 4% gap between their break point win percentages on wide and T serves. Some of that is probably just noise. We’ve logged only 94 break points served by Alexandr Dolgopolov, so his 15% gap isn’t that reliable. Still, some gaps appear even for those players with considerably more data.

The following table shows the ten players with the most break points faced in the dataset. The third column–“BP Wide/T”–shows how much they favor the wide serve on break points. The next two columns show their winning percentages on break point first serves in the two primary directions. Finally, the last column shows the difference between those winning percentages, also in percentage terms. The closer the gap to 0%, the closer to an optimal strategy.

Player             BPs  BP Wide/T  Wide W%   T W%    Gap  
Novak Djokovic     973       1.20    73.1%  72.9%   0.3%  
Rafael Nadal       971       1.87    67.3%  76.7%  12.2%  
Roger Federer      865       1.08    77.1%  77.1%   0.0%  
Andy Murray        730       1.19    71.1%  72.2%   1.6%  
Alexander Zverev   493       1.04    72.4%  76.6%   5.5%  
Stan Wawrinka      379       0.99    72.7%  71.9%   1.2%  
Kei Nishikori      366       1.18    59.5%  69.6%  14.5%  
David Ferrer       347       0.81    59.7%  63.7%   6.2%  
Diego Schwartzman  338       0.69    72.2%  67.8%   6.5%  
Dominic Thiem      294       1.64    71.8%  73.9%   2.8%

Djokovic, Roger Federer, Andy Murray, and Stan Wawrinka are close to the tactical optimum. Nadal is … not. He loves the wide serve on break points, yet he is considerably more successful when he lands his first serve down the T.

But again, we need to work from the assumption that the players know what they’re doing–especially when that player is as accomplished and otherwise strategically sound as Rafa. My focus throughout this post has been on first serves. In general, players make first serves at about the same rate regardless of which direction they choose. In the ad court, down-the-middle attempts are a bit more likely to land in than wide deliveries. But for Rafa, it’s a different story. His wide serve isn’t particularly deadly, but it is the picture of reliability. His ad-court first serve wide hits the mark 77.8% of the time, compared to a mere 59.5% down the middle. The T serve is effective when it lands in, but that in itself is not sufficient reason to make more attempts.

The same reasoning can’t save Kei Nishikori. He has an even bigger gap than Rafa’s, winning about 70% of his break point first serves down the T but only 60% when he goes wide. This is almost definitely not luck: Assuming 180 serves in each direction and the average success rate of about 65%, the chances of either number being at least five percentage points above or below the mean is about 18%. The probability that both are so extreme is roughly 3.5%, so the odds that they are extreme in opposite directions is less than 2%, or one in fifty.

Like Nadal, he is one of the few players who makes a lot more first serves in one direction than the other. But unlike Nadal, his first-serve-in discrepancy makes the gap even more pronounced! In the 366 break points we’ve logged, he landed 48.8% of his break point wide first serve attempts and 62.8% of his tries down the T. He lands more first serves down the middle and those serves are more likely to result in points won. Nishikori needs to hit a lot more of his break point serves down the T. His T-specific winning percentage will probably decrease as opponents discover the more pronounced tendency, but his overall results would likely improve.

At the most basic level, players should be aware of their opponents’ serving tendencies, whether by rumor, advance scouting, or data like the Match Charting Project. Beyond that, we’ve seen that there’s even more potential in the data, showing that some men are leaving break points on the table. Most elite tennis players have a good intuitive grasp of game theory, but even elite-level intuition gets it wrong sometimes.

The Impact of Rafael Nadal’s New Serve

Italian translation at settesei.it

A couple of years ago, the story of the Australian Open was a certain veteran Swiss player’s new backhand. Roger Federer won the tournament, raced back up the rankings, and eventually reclaimed the No. 1 spot. This season has kicked off with another superstar, Rafael Nadal, attempting to shore up his own relative weakness by streamlining his serve.

The early results are extremely positive. Through the semi-final, Nadal’s first serves in Melbourne have averaged 115 mph, compared to 110 mph at the US Open last fall. He hasn’t been broken in five straight matches, dating back to the second round, and has faced only 13 break points in his last 15 sets. True, he hasn’t faced a truly tough test, as the draw has handed him only two seeds, neither in the top ten. But his lopsided results thus far could equally be ascribed to his own dominance. After all, he demolished Stefanos Tsitsipas only a few days after the Greek prospect ousted Federer.

Serve speed numbers are encouraging and lopsided wins are great for the body, but our focus should always be on points, and how many of them he’s winning. By that measure, Rafa’s retooled serve has excelled, helping the Spaniard post some of the best-ever serving numbers of his grand slam career.

In six matches, Nadal has won 80.9% of his first-serve points. (Fellow finalist Novak Djokovic has won 77.5% of his. Both numbers are outstanding, as the hard-court tour average is below 75%, a figure that includes the contributions of much more dominant servers.) At hard and grass court grand slams, Rafa has done better only twice: 83.6% at the 2010 US Open and 81.3% and Wimbledon in 2008. Here are his top-ten first-serve performances through the semi-finals at hard court majors:

Tournament            1st W%  2nd W%            
2010 US Open           83.6%   66.9%            
2008 Wimbledon         81.3%   64.3%            
2019 Australian Open   80.9%   58.0%            
2013 US Open           79.5%   64.7%            
2017 Wimbledon         79.4%   58.6%            
2011 Wimbledon         79.4%   59.4%            
2010 Wimbledon         79.3%   61.6%            
2006 Wimbledon         77.9%   62.1%            
2012 Wimbledon         77.3%   61.5%            
2012 Australian Open   76.8%   56.7%

You might notice a pattern at the top of this list: Those are slams that he went on to win. The 2010 US Open was his first hard court major title, sealed with a four-set win over Djokovic, his most dominant non-clay victory over his long-time rival. 2008 Wimbledon was his first title there, in the memorable final against Federer. The 2013 US Open was another relatively tidy triumph over Djokovic. All the Wimbledons that clutter the bottom half of this list are inflated a bit by the surface, and it is revealing that Rafa’s next-best performance at the Australian Open sits so far down the list, with his 76.5% first-serve mark in 2012. That fortnight didn’t end in his favor, but it took nearly six hours for Djokovic to beat him.

This is all encouraging and, at the very least, it will make for an interesting aspect of tomorrow’s final, between the newly dangerous serving of Nadal and the ever-brilliant return game of Djokovic. But with only six matches on record, it’s tough to push the analysis much further. Rafa was dominant against Tsitsipas, but barely better than he was against the Greek when they met in Canada last summer. In Australia, he won 80.3% of service points, including 85% of his firsts; in their previous meeting, he won 78.9% of service points and 93.8% of his firsts. A more positive comparison is between his fourth-round win over Tomas Berdych (75.3% service points won, 80.4% firsts) and his previous hard court meetings with the Czech (66.6%, 72.7%). On the other hand, they hadn’t played since 2015 and Berdych is returning from injury, so we can’t put too much weight on the comparison.

Nadal’s more pessimistic fans will be keeping an eye on his second serve in Sunday’s final, as that delivery has not demonstrated the same jump in effectiveness. In the six Melbourne matches, Rafa has won 58.0% of second-serve points, just barely above his career average of 57.3% at hard court majors. That relative weakness was exploited by Alex De Minaur, the best returner of his Aussie Open opponents, who held Nadal to a measly 36.4% of second serve points won. Djokovic is even better, neutralizing bigger second-serve weapons than Rafa’s, so it remains a concern.

If Nadal wins the title, his new serve will rightfully take much of the credit. Not only has it improved his effectiveness on that side of the ball, it has helped keep his matches short and his body ready for the challenges of hard court tennis. Years ago, I bucked the conventional wisdom and argued that Rafa could reach 17 slams. Since then, Federer has shifted the goalposts, but a bigger-serving Nadal makes 20 or 21 look more realistic than ever before.

The Oddity of Naomi Osaka’s Soft Second Serves

Italian translation at settesei.it

Naomi Osaka has quickly risen to the top of the women’s game on the back of some big hitting, especially a first serve that is one of the fastest in the game. Through Thursday’s semi-final, Osaka’s average first-serve speed in Melbourne was 105 mph, faster than all but two of the other women who reached the third round. Even those two–Aryna Sabalenka and Camila Giorgi–barely edged her out, each with average speeds of 106.

Shift the view to second serves, and Osaka’s place on the list is reversed. While Sabalenka’s typical second offering last week was 90 mph and Giorgi’s was 94, Osaka’s has been a mere 78 mph, the fourth-slowest of the final 32. That mark puts her just ahead of the likes of Angelique Kerber and Sloane Stephens, both whose average first serves are nearly 10 mph slower.

Osaka’s 27 mph gap is the biggest of anyone in this group. The next closest is Caroline Wozniacki’s 23 mph gap, between her 102 mph first serve and 79 mph second serve–both of which are less extreme than the Japanese player’s. Expressed as a ratio, Osaka’s average second serve is only 74% the speed of her typical first. That’s also the widest gap of any third-rounder in Melbourne; Wozniacki is again second-most extreme at 77%.

The following table shows first and second serve speeds, along with the gap and ratio between those two numbers, for a slightly smaller group: women for whom the Australian Open published at least four matches worth of serve-speed data:

Player          Avg 1st  Avg 2nd   Gap  Ratio  
Osaka             105.5     78.5  27.0   0.74  
Keys              105.2     85.4  19.7   0.81  
SWilliams         103.8     88.6  15.2   0.85  
Barty             102.0     88.2  13.7   0.87  
KaPliskova        101.9     80.5  21.4   0.79  
Collins           101.2     82.2  19.1   0.81  
Kvitova            99.6     91.6   8.0   0.92  
Muguruza           98.1     82.5  15.6   0.84  
Pavlyuchenkova     97.9     84.5  13.4   0.86  
Sharapova          97.9     89.6   8.2   0.92  
Svitolina          97.6     78.2  19.4   0.80  
Stephens           96.1     75.1  21.0   0.78  
Halep              95.3     80.9  14.4   0.85  
Kerber             94.0     78.4  15.7   0.83

Oddly enough, having such a slow second serve doesn’t seem to be causing any problems. In today’s semi-final against Karolina Pliskova, Osaka won 81% of first serve points and only 41% of second serve points, but her typical performance behind her second serve is better than that. And in this match, both women feasted on the other’s weaker serves: Pliskova won only 32% of her own second serves. (Though to be fair, Pliskova had the second-largest gap of the players listed above. She tends to rely more on spin than speed when her first serve misses.)

Across her six matches, Osaka has won 73.3% of her first serve points and 49.7% of her second serve points–a bit better than the average quarter-finalist in the former category, a very small amount worse than her peers in the latter. The ratio of those two numbers–68%–is almost identical to those of Danielle Collins, Petra Kvitova, Anastasia Pavlyuchenkova, and Serena Williams, all of whom have smaller gaps between their first and second serve speeds. Of the eight quarter-finalists, Kvitova has the smallest speed gap of all, yet the end result is the same as Osaka’s, she’s just a few percentage points better on both offerings.

Here are the first- and second-serve points won in Melbourne for the eight quarter-finalists, along with the ratio of those two figures and each player’s serve-speed ratio from the previous table:

QFist           1SPW%  2SPW%  W% Ratio  Speed Ratio  
Kvitova         77.9%  52.8%      0.68         0.92  
Williams        74.7%  50.0%      0.67         0.85  
Osaka           73.3%  49.7%      0.68         0.74  
Collins         72.5%  50.0%      0.69         0.81  
Barty           70.8%  55.7%      0.79         0.87  
Pliskova        70.5%  50.0%      0.71         0.79  
Pavlyuchenkova  67.0%  44.9%      0.67         0.86  
Svitolina       66.5%  48.1%      0.72         0.80

Clearly, there’s more than one way to crack the final eight. With Kvitova, we have a server who racks up cheap points with angles instead of speed, rendering the miles-per-hour comparison a bit irrelevant. Serena’s results are close to Osaka’s, though she gets there with bit more bite on her second serves. And then there’s Svitolina, who doesn’t serve very hard or that effectively but can beat you in other ways.

Knowing all this, should Osaka hit harder second serves? In extreme cases, like today’s 81%/41% performance against Pliskova, the answer is yes–had she simply hit nothing but first serves and succeeded at the same rate, she would’ve piled up a lot of double faults but won more total points. But the margins are usually slimmer, and as we’ve seen, her second-serve performance isn’t bad, it just might offer room for improvement. Every player is different, but faster is usually better.

A thorough analysis of that question may be possible with the available data, but it will have to wait for another day. In the meantime, Saturday’s final will offer us a glimpse of contrasting styles: Osaka’s powerful first offering and soft second ball, against Kvitova’s angles and placement on both serves. Both my forecast and the betting market see the title match as a close one–perhaps Osaka’s second serve will be the shot that makes the difference.

A Closer Look at Tiebreak Tactics

Italian translation at settesei.it

In theory, tiebreaks are a showcase for big serving, the skill that generates enough holds of serve to push a set to 6-6. But no matter how two players get there, the tiebreak itself doesn’t always work out that way.

Two examples suffice from Wednesday’s Australian Open action. Roger Federer’s second-round match against Daniel Evans opened with twelve straight service holds, threatened by only one break point. Yet in the tiebreak, which Federer won 7-5, the returner claimed 9 of 12 points. Across the grounds in front of a much smaller crowd, Thomas Fabbiano and Reilly Opelka forced a fifth-set super-tiebreak. Through 52 games and 319 points, Opelka hit 67 aces and the pair averaged 2.9 shots per “rally.” In the match-deciding tiebreak, Opelka hit no aces, Fabbiano got all but one of his serves back in play, and they averaged 5.5 shots per point.

When I started researching tiebreaks several years ago, I found that the balance of power shifts away from the server: returners win more points in tiebreaks than at other points during the set. It’s not a huge effect, accounting for about a 6% drop in server winning percentage, possibly due to the fact that players almost always give 100% on each point, unlike weak returners facing 40-0 in the middle of the set. Sure, Federer-Evans and Fabbiano-Opelka are outliers: even if servers suffer a bit in the typical tiebreak, the whole sport doesn’t usually turn upside down. Still, the effect is worth a deeper dive.

Isner isn’t the only conservative

Let’s start with some overall trends. Filtering for men’s matches from 2010-19, I found 831 tiebreaks with shot-by-shot data from the Match Charting Project. For each set that ended in a tiebreak, I tallied several stats for both tiebreak points and non-tiebreak points, calculated the single-set ratio for each stat, and then aggregated all 831 breakers to get some tour-wide numbers. Here’s what happens to stats in tiebreaks:

  • Service points won: -6.5%
  • Aces: -6.1%
  • First serve in: +1.3%
  • Returns in play: +8.5%
  • Rally length: +18.9%

(Technical note: When aggregating the ratios from all 831 tiebreaks, I weighted by the number of points in each tiebreak, but only up to a maximum of 11. Longer tiebreaks tend to be the ones if which servers are the strongest, like the 17-15 marathon in the first set of Fabbiano-Opelka. If those were weighted for their true length, we’d bias the results towards the best serving performances.)

Judging by the increase in successful first offerings, it looks like servers are a bit more conservative in tiebreaks. The large drop in aces and even bigger increase in returns in play provide additional evidence. Focused returners may be able to erase a small number of aces, but not that many, and they wouldn’t be able to convert so many into successful returns. The nearly 20% increase in rally length can be explained in part by the drop in aces (those one-shot rallies are replaced with more-shot exchanges), but the magnitude of the rally length effect suggests that players are more conservative on both sides of the ball.

More than one way

Not every player handles breakers the same way. Several men, including Federer, serve about as well as usual in these high-pressure situations. Certain others, like Rafael Nadal, appear to be more conservative, but make up for it by feasting on the toned-down offerings of opposing servers. Still others, like the impossible-to-write-about-tiebreaks-without-bringing-up Ivo Karlovic, underperform on both sides of the ball.

Here are the 20 players with the most tiebreaks recorded by the Match Charting Project since 2010. For each one, you can see how their rates of service points and return points won in tiebreaks compare to non-tiebreak situations. For instance, Jo Wilfried Tsonga wins 5.4% more service points in tiebreaks than otherwise, compared to the usual shift of 6.5% in the opposite direction. But Tsonga’s rate of return points won falls 3.4%, while the typical player increases his haul on return by 6.5%.

Player                    SPW    RPW  
Jo Wilfried Tsonga       5.4%  -3.4%  
Roger Federer            0.4%   3.2%  
Stan Wawrinka           -0.1%   4.2%  
John Isner              -0.6%   6.4%  
Novak Djokovic          -0.8%  11.8%  
Andy Murray             -2.2%   8.7%  
Alexander Zverev        -2.7%  18.7%  
Juan Martin del Potro   -3.3%   5.3%  
Nick Kyrgios            -4.1%  10.5%  
Dominic Thiem           -4.6%  12.1%  
----ATP AVERAGE----     -6.5%   6.5%  
Kevin Anderson          -7.1%   8.9%  
Gilles Simon            -8.0%  16.3%  
Tomas Berdych           -8.4%   6.8%  
Milos Raonic            -9.2%   9.1%  
Rafael Nadal            -9.4%  13.6%  
Marin Cilic            -10.2%   5.8%  
Bernard Tomic          -11.3%   4.5%  
Ivo Karlovic           -12.6%  -0.9%  
Grigor Dimitrov        -13.8%   5.1%  
Karen Khachanov        -25.1%  -5.4%

For most players, the goal appears to be to win enough extra return points to counteract the drop in service success. Nadal is the most extreme example, winning almost 10% fewer service points than usual, but doing even more damage to his opponents. Alexander Zverev is the most impressive of the bunch, dropping his serve level only a bit, while converting himself into a Rafa-like returner. As you might expect, his tiebreak record is outstanding, winning far more than expected last season. We’ll see whether his eye-popping numbers persist.

A winning strategy

Ideally, I would wrap up a post like this with a recommendation. You know, analyzing the various approaches, based on these numbers, we can confidently say that players should….

It’s not that easy. It’s hard enough to identify which players are good at tiebreaks, let alone why. As I’ve written many times before, tiebreak results are closely related to overall tennis-playing skill, but not to serving prowess or excellence in the clutch. In any given season, some players amass outstanding tiebreak records, but their success one year rarely translates to the next. At various times in the past, I’ve highlighted Federer, Isner, Nadal, and Andy Murray as players who defy the odds and consistently outperform expectations in tiebreaks, but even they don’t always manage it. Isner, the poster boy for triumph via tiebreak, won slightly fewer breakers than expected in both 2016 and 2018.

Still, let’s look at these four guys in the light of the shot-by-shot data I’ve shared so far. Federer, Isner, and Murray are in the minority of players who hit more aces in tiebreaks than otherwise. However, it it doesn’t necessarily mean they are much more aggressive; of the the three, only Federer makes fewer first serves than usual. Isner manages to reduce the number of returns in play by 10%, compared to non-tiebreak situations, while the other two do not. Nadal breaks the mold entirely, making 6% more first serves than usual and hitting barely half as many aces.

In other words, there’s no single path to success. Federer and Isner maintain their superlative serving while taking advantage of their opponents’ nerves or conservative tactics. (I’ve previously suggested that the difference in serve points won comes from players like Isner upping their return game in pressure situations. He does, but not any more than the average player.) Nadal plays to his own strengths, forcing players into rallies from both sides of the ball. There may be some quality that ties these four men together (like focus), but we’re not going to find it here.

Ivo Karlovic and the Odds-On Tiebreak

Italian translation at settesei.it

Ivo Karlovic is on track to accomplish something that no player has ever done before. Over the course of his career, Karlovic, along with John Isner, has set a new standard for one-dimensional tennis playing. The big men win so many service points that they are almost impossible to break, making their own service-return limitations manageable. With a player on court who maximizes the likelihood of service holds, tiebreaks seem inevitable.

This season, Karlovic has taken tiebreak-playing to a new level. Through last night’s semi-final at the Calgary Challenger (final score: 7-6, 7-6), the 6-11 Croatian has played 42 matches, including 115 sets and 61 tiebreaks. In percentage terms, that’s a tiebreak in 53% of all sets. Among player-seasons with at least 30 matches across the ATP, ATP qualifying, and ATP Challenger levels since 1990, no one has ever before topped 50%.

Even approaching the 50% threshold marks someone as very unusual. Less than 20% of tour-level sets reach 6-6, and it’s rare for any single player to top 30%. This year, only Isner and Nick Kyrgios have joined Karlovic in the 30%-plus club. Even Reilly Opelka, the seven-foot American prospect, has tallied only 31 tiebreaks in 109 sets this season, good for a more modest rate of 28.4%.

Karlovic is in truly uncharted territory. Isner came very close in his breakthrough 2007 season on the Challenger tour, playing 51 tiebreaks in 102 sets. The rest of the all-time top ten list starts to get a little repetitive:

Rank  Year  Player        Sets  TBs    TB%  
1     2018  Ivo Karlovic   115   61  53.0%  
2     2007  John Isner     102   51  50.0%  
3     2005  Ivo Karlovic   118   56  47.5%  
4     2016  Ivo Karlovic   146   68  46.6%  
5     2017  Ivo Karlovic    91   42  46.2%  
6     2006  Ivo Karlovic   106   48  45.3%  
7     2015  Ivo Karlovic   168   76  45.2%  
8     2018  John Isner     149   65  43.6%  
9     2001  Ivo Karlovic    78   34  43.6%  
10    2004  Ivo Karlovic   140   61  43.6%

* Karlovic’s and Isner’s 2018 totals are through matches of October 20th. 

For more variety, here are the 15 different players with the highest single-season tiebreak rates:

Rank  Year  Player           Sets  TBs    TB%  
1     2018  Ivo Karlovic      115   61  53.0%  
2     2007  John Isner        102   51  50.0%  
3     2004  Amer Delic         95   37  38.9%  
4     2008  Michael Llodra    117   45  38.5%  
5     2008  Chris Guccione    173   65  37.6%  
6     2002  Alexander Waske   109   40  36.7%  
7     1993  Greg Rusedski      99   35  35.4%  
8     2017  Reilly Opelka     115   40  34.8%  
9     2005  Wayne Arthurs      95   33  34.7%  
10    2004  Dick Norman        97   33  34.0%  
11    2001  Ivan Ljubicic     148   50  33.8%  
12    2004  Max Mirnyi        137   46  33.6%  
13    2014  Samuel Groth      172   57  33.1%  
14    2005  Gregory Carraz     98   32  32.7%  
15    2007  Fritz Wolmarans    80   26  32.5%

Karlovic is truly in a class by himself. He’ll turn 40 next February, but age has had little impact on the effectiveness of his serve. While he reached his career peak ranking of No. 14 back in 2008, it was more recently that his serve was at its best. In 2015, he won more than three-quarters of his service points and held 95.5% of his serve games. Both of those marks were career highs. His recent serve stats have remained among his career bests, winning 73.5% of service points in 2018, though as his ranking has tumbled, these feats have come against weaker competition, in ATP qualifying and Challenger matches.

Age has taken its toll, however, and Ivo’s return game is the victim. From 2008-12, he broke serve in more than one out of ten chances, while in 2016-18, it has fallen below 8%. Neither mark is particularly impressive–Isner and Kyrgios are the only tour regulars to break in less than 17% of games this season–but the difference, from a peak of 12.0% in 2011 to a low of 7.1% this year, helps explain why the Croatian is playing more tiebreaks than ever.

Karlovic has long been one of the most unique players on tour, thanks to his height, his extreme statistical profile, and his willingness (or maybe his need) to approach the net. As he gets older and his game becomes even more one-dimensional, it’s only fitting that he breaks some of his own records, continuing past the age when most of his peers retire in order to hit even more aces and play even more tiebreaks.

How Fast Was the Laver Cup Court?

Embed from Getty Images

Italian translation at settesei.it

Laver Cup has redefined what a tennis event can be, and so far, the new definition seems to involve fast courts. Last year, we saw nine tiebreaks out of eighteen traditional sets, plus a pair of match tiebreaks that went to 11-9. This year’s edition wasn’t quite so extreme, with five tiebreaks out of sixteen traditional sets, but it still featured more tight sets than the typical tour event, in which tiebreaks occur less than once every five frames.

As usual, teasing out surface speed comes with its share of obstacles. Yes, there were lots of tiebreaks and yes, there were plenty of aces, but the player field featured more than its share of big servers. John Isner, Nick Kyrgios, and Roger Federer each contested two matches each year, and in Chicago, Kevin Anderson represented one-quarter of Team World’s singles contribution. No matter what the surface, we’d expect these guys to give us more serve-dominated matches than the tour-wide average.

Let’s turn to the results of my surface speed metric, which compares tournaments by using ace rate, adjusted for the serve and returning tendencies of the players at each event. The table below shows raw ace rate (“Ace%”) and the speed rating (“Speed”) for ten events from the last 52 weeks: The four 2018 grand slams, the fastest and slowest tour stops (Metz and Estoril, respectively), the two Laver Cups, and the two events that rate closest to the Laver Cups (Antalya and New York).

Year  Event            Surface   Ace%  Speed  
2018  Metz             Hard     10.6%   1.57  
2018  Antalya          Grass     9.9%   1.28  
2017  Laver Cup        Hard     17.0%   1.26  
2018  Australian Open  Hard     11.7%   1.17  
2018  Wimbledon        Grass    12.9%   1.16  
2018  Laver Cup        Hard     13.3%   1.09  
2018  New York         Hard     15.7%   1.09  
2018  US Open          Hard     10.8%   1.02  
2018  Roland Garros    Clay      7.7%   0.74  
2018  Estoril          Clay      5.2%   0.55

The speed rating metric ranges from about 0.5 for the slowest surfaces to 1.5 for the fastest, meaning that the stickiest clay results in about half as many aces as the same players would tally on a neutral surface, while the quickest grass or plexipave would give the same guys about half again as many aces as a neutral court would.

Last year’s Laver Cup, despite a whopping 17% ace rate, was barely among the top ten fastest courts out of the 67 tour stops I was able to rate. The surface in Chicago was on the edge of the top third, behind the speedy clay of Quito and considerably slower than the Australian Open.

These conclusions come with the usual share of caveats. First, surface speed is about more than ace rate. I’ve stuck with my ace-based metric because it’s one of the few stats we have for every tour-level event, and because despite its simplicity, it tracks closely with intuition, other forms of measurement, and player comments. Second, we’re not exactly overloaded with observations from either edition of the Laver Cup. Last year’s event featured nine singles matches, and this year there were eight. It’s even worse than that, because third sets are swapped out for match tiebreaks, leaving us even less data. That said, while we don’t have many matches to work with, we know a lot about the players involved, which isn’t as true of, say, Newport or Shenzhen, where a larger number of matches are contested by players who don’t make many appearances on tour.

The two Laver Cup surfaces rate as speedy, but not out of line with other indoor hard courts on the ATP tour. There will be tiebreaks and plenty of aces wherever Isner and Anderson go, no matter what the conditions.