Podcast Episode 21: Talking About Talking About Tactics

Episode 21 of the Tennis Abstract Podcast, with Carl Bialik of the Thirty Love podcast, is our attempt to reconcile discussions of tennis tactics with those of tennis analytics. We start with our interest in the talented and crafty Alex De Minaur, then cover the oft-ignored tactical skills of Jo Wilfried Tsonga, the usefulness of tactical tips in the amateur game, and the constraints that coaches face when turning their observations into insights that players can use.

As a bonus, we also touch on this year’s new incentive to play doubles at Indian Wells, the crazy new proposal to overhaul Davis Cup, and the recent spate of tennis movies, especially Battle of the Sexes. In keeping with Jeff’s recent return to the U.S., it’s a super-sized episode, clocking in at just under 95 minutes.

Finally, we hope our audio quality is continuing to improve. We’re both now using proper mics, and the difference is, well, audible. Thanks for listening!

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Thank you to FBITennis for outlining this episode, with timestamps:

Alex De Minaur 1:38
Tsonga Decisionmaking 8:10
Pesky/Smart Players 12:30
What are “tactics”? How to analyze? 15:00
Testing effectiveness of shot patterns 20:43
DIY Tactics 27:00
Pros and Coaching Advice 34:40
Which analytics might be useful to pros? 39:58
Indian Wells Singles/Doubles Bonus 1:02:00
Reformatting Davis Cup 1:05:19
Tennis Movies 1:18:00

ATP Streaks of 2017

Italian translation at settesei.it

This is a guest post by Peter Wetz.

With the recent update of Jeff’s ATP and WTA GitHub repositories, we can take a look at notable streaks that happened in 2017. In this post I show matches won/lost and tiebreaks won/lost streaks of the 2017 ATP tour.

Let’s start with matches won:

Name               Start   End     Length
Rafael Nadal       04-17   05-15   17
Rafael Nadal       08-28   10-09   16
Roger Federer      06-19   08-07   16
Roger Federer      10-09   11-13   13
Roger Federer      03-06   03-20   12
Alexander Zverev   07-31   08-07   10
Rafael Nadal       05-29   07-03   10
Stan Wawrinka      05-22   05-29   10
Grigor Dimitrov    01-02   01-16   10

We see that, as far as streaks are concerned, the 2017 season was dominated by Roger Federer and Rafael Nadal. Rafa’s streak of 17 wins, which was halted by Dominic Thiem in the Rome quarterfinal, is the only streak containing three back-to-back tournament wins. Besides Roger and Rafa, only Alexander Zverev won two tournaments back-to-back.

When we talk about the less glamorous category of losing streaks, two names immediately should pop into our minds: Vincent Spadea and Donald Young. The former holds the record of 21 consecutive matches lost* on ATP level, and the latter holds one of the longer losing streaks (17 matches lost in a row) in recent years.

During the 2017 ATP season no player came close to any of these marks, but still there were a few moments where players seemed to have forgotten how to win a match. The following list shows all players with 8 or more consecutive matches lost.

Name                  Start   End     Length
Pablo Cuevas          05-29   10-23   10
Maximilian Marterer   02-06   08-28   10
Paolo Lorenzi         08-28   10-30    8 
Malek Jaziri          03-20   07-03    8 
Daniil Medvedev       07-31   10-09    8 
Stefanos Tsitsipas    02-13   10-02    8

Regarding Maximilian Marterer‘s streak of 10 matches lost, we have to mention that he played a good season at the Challenger level. In between his losses at the ATP level there were deep runs at various Challenger tournaments. Still, it must be frustrating to lose your first round main draw match every time after having successfully gone through qualies. This fact accounts for 7 of his 10 losses at ATP main draws (the other 3 coming from entries as a wild card). Pablo Cuevas, the other player having lost 10 matches in a row last season, on the other hand, achieved a real losing streak with no Challenger level wins hidden among them.

Winning tiebreaks has been discussed on this blog a lot. One of the conclusions was that in the past three players–Roger Federer, Rafael Nadal, and John Isner–consistently outperform their tiebreak expectations. The list of consecutive tiebreaks won in 2017 supports this statement as can be seen in the following table.

Name           Start   End     Length
John Isner     05-15   05-29   11   
Roger Federer  06-19   08-07   8 
Roger Federer  03-06   03-20   8 
(Many tied)                    7

John Isner’s streak went over the course of 8 matches including 2 matches he lost, whereas Roger won all the matches in which he won the tiebreaks contributing to his streaks.

The list of consecutive tiebreaks lost looks as follows.

Name            Start   End     Length
Lucas Pouille   07-03   10-09   12 
Florian Mayer   01-02   07-03   11
Dusan Lajovic   03-06   07-24   8

Lucas Pouille holds the crown for most tiebreaks lost in a row in 2017. In fact he got really close to Robin Haase‘s infamous run of 13 tiebreaks lost.

Finally, I want to present an odd 2017 achievement by Nick Kyrgios: He is the only player ever to lose three matches in a row by retirement.

Date   Tourney   Matchup                           Result
07-31  W'ington  Nick Kyrgios vs Tennys Sandgren   3-6 0-3 RET
07-03  Wimby     Nick Kyrgios vs Pierre H Herbert  3-6 4-6 RET
06-19  London    Nick Kyrgios vs Donald Young      6-7(3) 0-0 RET

The list of 2018 streaks is shaping up nicely already: Doubles partners Oliver Marach and Mate Pavic opened their season with 17 straight wins, including three titles, finally ending with a loss in the Rotterdam final to Pierre-Hugues Herbert and Nicolas Mahut. Marach can even claim an 18-match streak, since he won a Davis Cup match for Austria last month while pairing with Philipp Oswald. Doubles data is tougher to come by, but it’s safe to say that the season-opening run for Marach/Pavic will have a prominent place in any summaries of this year’s ATP streaks.

 

* The list excludes one loss of Vincent Spadea at the 1999 World Team Cup in Düsseldorf, where he lost to Rainer Schüttler 5-7, 6-3, 1-6.

—

Peter Wetz is a computer scientist interested in racket sports and data analytics based in Vienna, Austria.

Trivia: Deja Vu All Over Again

Italian translation at settesei.it

In the last several days, Fernando Verdasco has seen a little too much of Diego Schwartzman. On Sunday in Rio de Janeiro, the two players met in the final of the 500-level clay court event, which Schwartzman won in straight sets. Both players immediately headed for the hard court tournament in Acapulco, where they drew each other in the first round. Verdasco lost again, this time winning six games instead of five.

The odds of this sort of final-to-first-round scenario, with back-to-back matches against the same opponent, is quite rare, and the surface switch makes this one even more unlikely. For one thing, the tour doesn’t move from one court type to another very frequently, and when they do, players don’t always travel through the same sequence of events. Another cause of improbability is that a pair of players who contest a final are usually pretty good, meaning that both of them are often seeded at their next event, making a first-round meeting impossible. In order to see a pair of consecutive matches like Schwartzman’s and Verdasco’s, we require synchronized schedules and a hefty helping of luck.

As Carl Bialik pointed out, this isn’t the first time Verdasco has played back-to-back matches in February against the same opponent, albeit on the same surface: He did so in 2011, dropping the San Jose final and then a Memphis first-rounder to Milos Raonic. Remarkably, when we broaden the search a bit, Verdasco’s name comes up twice more. In 2009, he lost to Radek Stepanek in the Brisbane final, then in his next event, the Australian Open, he beat Stepanek in the third round. (Radek played Sydney in the meantime, for what it’s worth.) And five years later, Verdasco overcame Nicolas Almagro to win the 2014 Houston title, then faced his countryman in his next event two weeks later, losing to Almagro in the round of 16. (Again, while they were back-to-back tourneys for Verdasco, Nico squeezed in a few matches in Monte Carlo in between.)

Back to the matter at hand: In the course of five decades of Open Era men’s tennis, just about everything has happened at least once before. But this exact scenario–two guys facing each other in a final, then a first round match the very next week on a different surface–is a new one. Relax any one of those constraints, and we see a few instances in the past.

Since 1970, there have been about 3,750 tour-level finals. Roughly one-third of the time, the two finalists ended up playing each other at least once more over the course of the season. 197 of those pairs drew each other in their very next event, and in another 62 of the finals, one of the players faced the other in his next tournament (though the other had played an event or two in the meantime, like Almagro and Stepanek). Several of the 197 duos played each other the next week, though it is a bit more common that there was a week off in between.

Of the 197 finalist pairs, 25 of them drew each other in the round of 32 or earlier in their following tournament, though not all of those were first-round matches. (Or, in the case of Andy Murray and Philipp Kohlschreiber in 2015 after contesting the Munich final, they played in Murray’s first Madrid match the following week but not Kohlschreiber’s, since Murray had a bye.) The most common round in which finalists met again was another final, which ensued about one-third of the time.

Dividing up the 197 pairs a different way, about one-fifth (39) played the follow-up match on a different surface. In only a few of these instances were the two surfaces hard and clay; a disproportionate number of these back-to-back matches happened in the 1970s and early 1980s, when carpet was regular feature on tour, so the hard-to-carpet or carpet-to-hard transition shows up in these results much more frequently than hard-to-clay or clay-to-hard. For any pair of surfaces in these 39 matches, only three occured in the round of 32, and none in the round of 64 or 128.

The three precedents for Schwartzman’s back-to-back wins all have several things in common. First, like Diego’s feat, the same player won both matches. The other two are unlike the Schwartzman double: In each case, there was a one-week break between the tournaments and one of the events was played on carpet.

The first similar achievement was recorded by Tom Gorman, who won consecutive matches against Bob Carmichael in 1976. The first was the Sacramento final (on carpet), followed by the first round in Las Vegas (on hard). Next up was Martin Jaite‘s pair of wins over Javier Sanchez in 1989. After triumphing in the Sao Paulo final (on carpet), Jaite won a hard-court first-rounder against the same opponent two weeks later. Finally, Fernando Gonzalez defeated Jose Acususo twice in a row in 2002, first in the clay-court final in Palermo, then a bit more than a week later on carpet in the first round in Lyon.

Like Schwartzman and his three closest predecessors, most of the finalists managed to defend their victory. Of the different-surface instances, the same player won both matches 26 of 39 times. When the two matches took place on the same surface, the title winner won the next match 101 of 158 times. Most recently, Yuichi Sugita failed to do so: After beating Adrian Mannarino for his first tour-level title in Antalya last summer, he met the Frenchman again in the Wimbledon second round and lost. In a more notable exception, Andre Agassi knocked out Petr Korda for the 1991 Washington title, then lost to Korda in his first match the next week in Montreal. (It wasn’t Korda’s first match, as he didn’t get a bye like Agassi did, but the extra effort paid off. The Czech reached the final.)

We could wait fifty years for an exact parallel of Schwartzman’s feat. Or we could set the bar a little lower and see a rematch almost immediately: Another of last week’s finalist pairs, Lucas Pouille and Karen Khachanov, followed up their Marseille title match with another meeting in the Dubai second round only three days later. Regardless of which standard you choose, there’s one person who would surely prefer to take a break from consecutive matches against the same opponent, and that’s Fernando Verdasco.

Podcast Episode 20: Five Tournaments, Lots of Decisions

Episode 20 of the Tennis Abstract Podcast, with Carl Bialik of the Thirty Love podcast, is a deep dive into the question of surface preferences and tournament choices, as we straddle two weeks of ATP action in which events are played on both hard and clay, and every competitors needs to weigh his or her own skills against issues like jetlag, prize money, and all-important ranking points. We also discuss the potential of future stars Frances Tiafoe, who picked up his first title in Delray Beach, and Daria Kasatkina, who reached the final in Dubai.

If you were turned off by the audio last week … sorry about that. Our latest experiment didn’t work at all. This episode’s audio is much better. Thanks for listening!

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Thanks to FBITennis, here are timestamps and an outline of this episode:

Schwartzman Cracks Top 20 1:10
Scheduling for Surface 17:15
Frantic February Schedule 30:40
Projecting Kasatkina and Ostapenko 38:30
Svitolina Future #1? 43:53
Pressure of Serving for the Match 51:30
Tiafoe Breakthrough 55:53
One-Dimensional Serve Players 1:03:20

Dominic Thiem, Old-School Clay Court Specialist

Italian translation at settesei.it

With a tennis calendar tilted heavily toward hard court events, we don’t see many true clay court specialists these days. The best male players who excel on clay are forced to adapt their games to hard courts, as well: Rafael Nadal has won six majors off of clay, while Pablo Carreno Busta and Diego Schwartzman have both hoisted trophies at tour level hard court events. It’s possible to play a mostly-clay schedule at the Challenger level, but it’s nearly impossible to establish yourself as an ATP regular without winning some matches on hard courts.

Dominic Thiem is capable enough on fast surfaces, but more than any other tour player, he is considerably better on the dirt than off it. In the last 52 weeks, he has won 25 of 31 matches on clay, compared to only 24 of 42 on other surfaces. Against the top ten, he is a respectable 7-9 on clay (more impressive when you consider that 12 of the 16 matches were against the Big Four, seven of them facing Nadal, and two of the others came against Stan Wawrinka), but a dismal 2-15 on hard courts. If you, like me, had settled into thinking of Thiem as a solid but not particuarly threatening member of the top ten, you probably didn’t realize quite how bad he is on hard courts–or just how good he has become on clay.

When only clay court results are taken into consideration, Thiem rates as the second-best player on the surface. According to clay court Elo, the Austrian outranks everyone on tour except for Rafa and Novak Djokovic, whose rating reflects his skill level when he last regularly played and very likely will overstate his ability when he returns. Thiem trails Nadal by about 180 points, 2410 to 2235, implying that in a head-to-head matchup, we’d except the Austrian to win only 26% of the time. But when we compare Thiem to the rest of the pack and exclude the walking wounded–Djokovic, Wawrinka, Andy Murray, and Kei Nishikori–along with clay-skipper Roger Federer, his position looks much better. The next best clay courter, Alexander Zverev, trails Thiem by about the same margin, nearly 170 points.

A clay court Elo rating over 2200 is a useful marker of elite status. In the professional era, only 29 players have reached that level, 22 of whom can count at least one Grand Slam title to their names. Among active players, only the Big Four, Nishikori, Juan Martin del Potro, David Ferrer, and Thiem belong to the club.

Where Thiem really stands out is the juxtaposition of his clay court success and his hard court mediocrity. After his title last week in Buenos Aires, his Elo rating based only on clay court results was 2234, compared to a hard court rating of 1869. The first number, as we’ve seen, is good for third overall, second if we exclude Djokovic’s increasingly stale results; the second puts him 31st on tour, behind Schwartzman, Damir Dzumhur, and Fabio Fognini.

No one active today is more of a clay specialist–in the sense that his results on clay exceed his results on hard–than Thiem. (There are some even more extreme differences between grass and either hard or clay, but the brevity of the grass season means that many of those contrasts are due only to small samples.) The ratio of Thiem’s clay court Elo rating to his hard court rating–again, 2234 to 1869–is 1.20, far beyond any of the 44 other active players with a clay court Elo rating of 1800 or higher. Simone Bolelli comes in second, at 1.12, and a handful of players, including Nadal, register at 1.10. Here is the entire top 20:

Player                 Clay Elo  Hard Elo  Ratio
Dominic Thiem              2234      1869   1.20
Simone Bolelli             1834      1634   1.12
Rafael Nadal               2410      2182   1.10
Albert Ramos               1873      1696   1.10
Federico Delbonis          1869      1696   1.10
Pablo Carreno Busta        1921      1746   1.10
Pablo Cuevas               1873      1709   1.10
Nicolas Almagro            1903      1755   1.08
Karen Khachanov            1838      1701   1.08
Leonardo Mayer             1878      1741   1.08
Aljaz Bedene               1826      1695   1.08
David Ferrer               2017      1894   1.07
Philipp Kohlschreiber      1951      1845   1.06
Stan Wawrinka              2138      2027   1.06
Martin Klizan              1800      1709   1.05
Guido Pella                1825      1744   1.05
Borna Coric                1830      1760   1.04
Fernando Verdasco          1863      1794   1.04
Alexander Zverev           2067      1997   1.04
Feliciano Lopez            1830      1772   1.03

A few decades ago, when it was possible for top players to spend more than two or three months per year racking up points on clay courts, such lopsided ratings were a bit more common. Of the 29 men who have ever topped 2200 in clay court Elo rating, 11 have at some point recorded a ratio of 1.20 or higher. That includes Nadal, whose clay rating was 20% higher than his hard court number early in 2008, and Sergi Bruguera, whose ratio topped out at 1.29. Four other major titlists–Bjorn Borg, Juan Carlos Ferrero, Thomas Muster, and Guillermo Vilas–also exceeded 1.20 at some point during their career. To put Thiem’s specialization in context, though, consider that Guillermo Coria maxed out at 1.19 and Gustavo Kuerten peaked at 1.16. Even Ferrer–the epitome of the clay court specialist to a generation of fans–never exceeded 1.15 once his clay court Elo rating had passed the 2000-point threshold.

The category into which Thiem fits most neatly–specialists who are decidedly middle-of-the-pack on hard courts–largely belongs to an earlier era. When we lower our clay court Elo standard to a career peak of 2000 points, a mark equal to about 15th on tour right now, we’re left with a group of 145 players in the professional era. Of those, 65 (45%) were at some point as lopsided as Thiem is now, with a clay-to-hard rating ratio of at least 1.20. Yet only five of those belong to active players (Nadal, Thiem, Fognini, Pablo Cuevas, and Nicolas Almagro) and two-thirds of them came before 1995.

In some cases, players with substantially better clay court results learn to compete at a higher level on faster surfaces. Thiem is 24, and Nadal had a similar specialist’s ratio at age 22. Other former greats enjoyed early success on clay and quickly figured out hard courts as well. The Austrian may prove to be a late bloomer in that regard. That’s unlikely, but when Nadal retires or (improbable as it seems) fades, Thiem is poised to rack up titles and emerge as the greatest clay court player of his generation, regardless of whether his hard court game improves.

Podcast Episode 19: Comeback Stories

Episode 19 of the Tennis Abstract Podcast, with Carl Bialik, covers a slew of comeback stories, from Federer’s return to No. 1 to Kei Nishikori and the inaugural New York Open, with more than a glancing mention of Maria Sharapova’s progress and the impending appearances on tour of Serena Williams and Marion Bartoli.

Thanks for listening!

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Thanks to FBITennis, here are timestamps and an outline of this episode:

Theme: Comebacks 0:38
Federer Comeback 1:15
Fed’s Ability to Retain #1 5:37
Long Island ATP 250 (NY Return) 19:33
Nishikori Comeback 25:23
Bartoli Unretirement 35:15
Sharapova Comeback Progress 41:45
Serena’s Anticipated Comeback 48:04
Crazy Aussie Open Results 55:00
Mining the Challengers 1:03:48
WTA Consistency in Top 10 1:06:28

Roger Federer’s 20th, Easiest Grand Slam Title

Italian translation at settesei.it

After Rafael Nadal’s US Open title last fall, I wrote a piece for the Economist that attempted to measure each Grand Slam title by difficulty. If you’re interested in the methodology, you can review it there. The conclusion was intriguing: Nadal’s opponents en route to his 16 major titles were considerably more difficult than the routes Roger Federer took to his first 19. By “difficulty-adjusted” Slam titles, Rafa led by a whisker, 18.8 to 18.7.

Since then, Federer won the 2018 Australian Open, incrementing his major tally by one. Even though he faced rather weak competition, surely the additional title nudged his difficulty-adjusted total above Rafa’s, right?

It did, but not by much. Adjusted for difficulty, Roger’s seven wins in Melbourne were worth only 0.42 majors. By comparison, his previous low was the 2006 Australian, worth 0.61, and Rafa’s lowest was last year’s US Open, at 0.62. Federer’s previous average was 0.98, Nadal’s was 1.18, and Rafa’s route to the 2013 French Open was worth a whopping 1.65.

Fed’s draw was historically weak. Only a handful of majors in the professional era were easier for their champion, and they all came before 1985–most of them in Melbourne, which didn’t yet attract the best talent in the world. This year’s Australian Open path to the title was even weaker when put in the context of the current decade: The average major title from 2010-17 was worth 1.23, largely because the Big Four usually needed to overcome each other.

According to surface-specific Elo, the toughest challenge Federer faced last month was Tomas Berdych, closely followed by Marin Cilic. Even after deep runs in Australia, neither player even ranks in the current Elo top ten. The algorithm that adjusts slam titles considers how the average major champion would fare against a particular set of competition; against Berdych and Cilic, that hypothetical average champ is expected to win 88% and 89% of the time, respectively. Even Nadal had to get past Juan Martin del Potro in New York last year.

Still, Federer can claim the top spot on yet another list, as his 19.1 difficulty-adjusted Grand Slam titles exceed Rafa’s 18.8 as well as the 15.3 of Novak Djokovic. It doesn’t have quite the same ring that “20 majors” does, and it’s in considerably more immediate danger. If Nadal stays healthy and wins the French Open, he is virtually guaranteed to reclaim the difficulty-adjusted crown, and by a wider margin than Roger currently holds. Roland Garros has traditionally been tough: With the exception of 2010, all of Rafa’s trophies in Paris have been tougher than average. Unlike the traditional Grand Slam tally, the difficulty-adjusted ranking could yo-yo between the two rivals for as long as they remain competitive.

Podcast Episode 18: A New Season Attacks

Episode 18 of the Tennis Abstract Podcast, with Carl Bialik, is our attempt to cover four months of tennis in 75 minutes. We fail, of course, but en route, we have plenty to say about Nick Kyrgios, some other rising men, and the fate of the WTA’s counterpunchers. We also discuss the Match Charting Project, to which you should contribute.

Unfortunately, there’s some mechanical buzz on my side of this recording, for reasons I haven’t yet identified. We’ll be back in early February with another episode–and, we hope, no extraneous noise. As always, thanks for listening!

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Thanks to FBITennis, here are timestamps and an outline of this episode:

Nick Kyrgios (Brisbane/Aus Open) 1:01
Match Charting Project 13:34
Kyrgios vs. A. Zverev 21:54
Going for Broke on 2nd Serve 22:58
World Tour Finals “Big Four” (Goffin, Thiem, Zverev, Dimitrov) 25:00
Del Potro Masters/Majors Potential 36:27
WTA – Who Wins the Slams? 40:29
WTA – Dark Horses (Konta, Goerges, Garcia, Barty) 49:15
Shenzhen Finals – WTA Chaos 52:14
Tennis TV /WTA TV 57:48
Hopman Cup/Experimental Formats 59:44

The Power of One Point Per Thousand

Italian translation at settesei.it

Last week, I offered a method to rank smash-hitting skill. I measured the results in “points per 100”–the number of points a player could expect to gain or lose, relative to tour average, thanks to their ability hitting that one shot. The resulting figures were quite small: My calculations showed that Jo-Wilfried Tsonga has the game’s best smash, a shot worth 0.17 points per 100 above average, and 0.27 points per 100 above the weakest smash-hitting player I found, Pablo Cuevas.

That gap between best and worst of 0.27 per 100 gives us a rough maximum of how much difference a good or bad smash can make in a player’s game. The rate is roughly equivalent to one point out of 370. It sounds tiny, and since most players are closer to the average than they are to either of those extremes, the typical smash effect is even smaller still.

However, it’s difficult to have any intuitive sense of how much one point is worth. In any given match, a single point, or even five points, isn’t going to make the difference. On the other hand, plenty of matches are so close that one or two points would flip the result. If an average player could train really hard in the offseason and develop a smash just as good as Tsonga’s, what would that extra 0.17 points per 100 mean for him in the win column? What about in the rankings?

This is a relatively straightforward question to answer once we’ve posed it. Over the course of a season, the best players win more points than their peers–obviously. Yet the margin isn’t that great. In 2017, no man won points at a higher clip than Rafael Nadal, who came out on top 55.7% of the time. That’s less than seven percentage points higher than the worst player in the top 50, Paolo Lorenzi, who won 49.1% of points. Nearly half of top 50 players–22 of them–won between 49.0% and 51.0% of total points, and another 15% fell between 51.0% and 52.0%.

Fixing total points won

These numbers are slightly misleading, though only slightly. The total points won stat (TPW) tends to cluster very close to the 50% mark because competitors face what, in other sports, we would call unbalanced schedules. If you win, you usually have to play someone better in the next round; win again, and an even more superior opponent awaits. This means that the 6.6% gap between Nadal and Lorenzi is a bit wider than it sounds: Had the Italian faced the same set of opponents that Rafa did, he wouldn’t have managed to win 49.1% of points.

That problem, however, is possible to resolve. Earlier this year I shared an algorithm that analyzed return points won by controlling for opponent, by comparing how each pair of players fared in equivalent matchups. (That analysis hinted at the second-half breakthrough of return wizard Diego Schwartzman.) While we don’t know exactly what would happen if Lorenzi played Nadal’s exact schedule, we can use this common-opponent approach to approximate it. When we do so, we find that the 1st-to-50th, Nadal-to-Lorenzi spread is almost 10 percentage points; setting Rafa’s rate at a constant 55.7%, Lorenzi’s works out a less neutral-sounding 46.2%. Many players remain packed in the 49%-to-51% range, but the overall spread is wider, because we control for tennis’s natural tendency to cancel out player’s wins with subsequent losses.

Even when we widen the pool of players to 71–everyone who played at least 35 tour-level matches this season–the ten-percentage-point spread remains. Lorenzi remains close to the bottom, a few places above Mikhail Youzhny, whose competition-adjusted rate of points won is 45.7% ranks last, exactly ten points below Rafa.

Think about what that means: In a typical ATP match, for every hundred points played, only ten are really up for grabs. That isn’t literally true, of course: There are plenty of matches in which one player wins 60% or more of total points. But on average, you can expect even the weakest tour regular to win 45 out of 100 points. In team sports analytics, this is what we might call “replacement level”–the skill level of a freely available minor leaguer or bench player. I don’t like importing the concept of replacement level for tennis, because in an individual sport you’re never really replacing one player with another. But at the most general level, it’s a useful way of thinking about this subject–just as even a minor league batter could hit .230 in the major leagues (as opposed to .000), so a fringey ATP player will win 45% of points, not 0%.

Points to wins

In team sports analytics, it’s common to say that some number of runs, or goals, or points is equal to one win. Thinking in terms of wins is a good way to value players: If you can say that upgrading your goalkeeper is worth two wins over your current option, it makes very clear what he brings to the table. Again, the metaphor is a bit strained when we apply it to tennis, but we can start thinking about things in the same way.

Another oddity in tennis is that players not only face very unequal competition, they also play widely different numbers of matches. The year-end top 50 contested anywhere from 35 matches up to more than 80; part of the variation is due to injury, but much is structural: The more matches you win, the more you play. Rafa managed his schedule by entering only a handful of optional events, yet only David Goffin played more matches. So we have another quirk to handle: In this case, let’s adopt the fiction that a tennis season is exactly 50 matches long. Rafa’s actual record was 67-11; scaled to a 50-match season, that’s roughly 43-7.

Finally, we can look at the relationship between points and wins. Points, here, means the rate of total points won adjusted for competition. And wins is the number of victories in our hypothetical 50-match season. The relationship between points and wins is quite strong (r^2 = 0.75), though of course not exact. Roger Federer won matches at a higher rate than Nadal did, but by competition-adjusted total points won, Rafa trounced him, 55.7% to 53.5%. And as we’ve seen, Lorenzi is close to the bottom of our 71-player sample, despite hanging on to a ranking in the mid-40s. Luck, clutch play, and a host of other factors make the points-to-wins relationship imperfect, but it is nonetheless a healthy one.

It doesn’t take many points to boost one’s win total. An increase of only 0.367 points per 100 translates into one more win in a 50-match season. The average player contests 8,000 points per season, so we’re talking about only 29 more points per year. This puts my smash-skill conclusions in a new light: The spread between the best and the worst of 0.27 points per 100 seemed tiny, but now we see it’s worth almost a full win over the course of a 50-match season.

Wins to ranking places

Unless you’re nearing a round number and have a hankering for cake, even wins aren’t the currency that really matters in tennis. What counts is position on the ranking table. The relationship between wins and ranking position is another strong but imperfect one (r^2 = 0.63).

As we’ve seen, the middle of the ATP pack is tightly grouped together in total points won, with so many players hovering around the 50% mark, even when adjusted for competition. There’s not much to distinguish between these men in the win column, either: On average, an increase of 0.26 wins per 50 matches translates into a one-spot jump on the ranking computer. Put another way: If you win one more match, your ranking will improve by four places. Again, these are not iron laws–in reality, it depends when and where that extra win occurs, and the corresponding ranking improvement could be anywhere from zero spots to 30. Still, knowing the typical result allows us to understand better the impact of each marginal win and, by extention, the value of winning a few more points.

One point per thousand

Combine these two relationships, and we get a new, conveniently round-numbered rule of thumb. If an increase in one ranking place requires 0.26 additional wins per 50 matches, and one additional win requires 0.367 extra points per 100, a little tapping at the calculator demonstrates that one ranking place is equal to about 0.095 points per 100. Round up a bit to 0.1 per 100, and we’re looking at one point per thousand.

One extra point per thousand is a miniscule amount, the sort of difference we could never dream of spotting with the naked eye. Players regularly win entire tournaments without contesting so many points; even for Goffin, who served or returned more than 12,000 times this year, we’re talking about a dozen points. Yet think back to all of those players clustered between 49% and 52% of total points won; even when adjusted for competition, three men ended the 2017 season tied at exactly 50.4%, with less than one point per thousand separating the three of them.

The one part of the ranking table where one point per thousand is no more than a rounding error is the very top. Usually one player separates himself from the pack, and the top few distance themselves from the rest. This year is no different: The competition-adjusted gap between Nadal and Federer is a whopping 2.2% (22 points per thousand), while the next 2.2% takes us all the way from Fed through the entire top 10. The 2.2% after that, extending from 51.1% to 48.9%, covers another 20 players: spaced, on average, one point per thousand apart. For a player seeking to improve from 30th to 20th, the path is largely linear; from 5th to 3rd it is much less predictable–and probably steeper.

If this all sounds unnecessarily abstruse, I can only mention once again the example of my smash-skill findings. Now we know that the range of overhead-hitting ability among the game’s regulars is worth close to three places in the rankings. Imagine a similar type of conclusion for forehands, backhands, net approaches… it’s exciting stuff. While plenty of work lies ahead, this framework allows us to measure the impact of individual shots–perhaps even tactics–and translate that impact into ranking places, the ultimate currency of tennis.

Overperforming in Davis Cup

This is a guest post by Peter Wetz.

With the help of weighted surface specific Elo ratings we have a powerful new tool to measure player performance. The traditional conclusion of the tennis season, the Davis Cup final, provides us with an opportunity once again to examine which players thrive when competing for their nation and which players seem to suffer from the pressure. While we are at it, I don’t like the sound of the word offseason. After all, there are still ITF tournaments, not to mention the Australian Open Asia-Pacific Wildcard Play-offs.

As already hinted, Elo ratings have proven to represent a better picture of player quality than traditional ATP rankings. Hence, comparing expected wins based on Elo with actual wins provides us with a clearer picture of who outperforms expectations and who does not.

In this evaluation, I consider completed World Group and Group 1 Davis Cup live rubbers played since 1980. The data set contains around 5000 matches through this year’s World Group Quarterfinals, and I’ve limited my focus to players having played 15 or more matches.

Let’s first take a glance at the obvious stat, win-loss percentage. The following table shows the top ten win-loss records of all players under consideration. (The Active column denotes if the player is still an active player).

Name	        W	L	Perc	Active
Rafael Nadal	20	1	95%	1
Boris Becker	31	2	94%	0
Andy Murray	25	3	90%	1
Balazs Taroczy	23	3	89%	0
David Ferrer	20	3	87%	1
Andre Agassi	23	4	85%	0
Roger Federer	40	7	85%	1
Novak Djokovic	27	5	84%	1
Guillermo Vilas	16	3	84%	0
Andrei Medvedev	16	3	84%	0

As one would expect, the big four and other all time greats are included. However, this obviously does not tell the whole story. Rafael Nadal is expected to win most of the time and that is what he does. For such a player, it is hard to outperform expectations.

If we compute how much a player outperforms his expectations, we get a clearer picture, given we want to know who does especially well in Davis Cup. Expected wins are calculated based on a half-and-half mix of surface specific Elo and overall Elo as this, in general, provides close to the best results, as pointed out in a previous article.

The tables below show the top and bottom five among all (first table) and active (second table) players in terms of over and underperforming expected wins. It shows actual wins (W), expected wins (eW), the percentage of over or underperformance (+/-), and if a player is still active.

Name	         W	eW	+/-	active
Francisco Maciel 11	6	72%	0
Slobodan Zi'vic  20	11	72%	0
Vasek Pospisil	 9	5	71%	1
Adrian Ungur	 6	3	56%	1
Mahesh Bhupathi	 5	3	55%	0
...
Wally Masur	 7	10     -31%	0
Sebastien Lareau 7	10     -31%	0
James Blake	 7	10     -36%	0
Nicolas Kiefer	 6	10     -40%	0
Aqeel Khan	 2	4      -57%	0

Name	        W	eW	+/-	Active
Vasek Pospisil	9	5	71%	1
Adrian Ungur	6	3	56%	1
Andrey Golubev	13	8	46%	1
Di Wu	        14	9	45%	1
Steve Darcis	15	11	35%	1
...
Florian Mayer	7	8      -14%	1
Gilles Muller	9	10     -15%	1
Alejandro Falla	8	9      -17%	1
John Isner	9	11     -19%	1
Jurgen Melzer	20	25     -22%	1

The tables seem to overlap with some conventional wisdom floating through the tennis sphere. Namely, that Steve Darcis, despite his recent losses at the Davis Cup final, plays above expectations. Also, Jurgen Melzer is known for regularly disappointing Austrian Davis Cup fans. (In his defense, he created several moments of joy, too).

If we were to pick a Davis Cup hero for the active and inactive group of players, Slobodan Zivojinovic and Andrey Golubev seem to be good choices. Golubev has a record of 13-6 (68%) and outperforms expected wins by 46%. He provides a good combination of consistently beating players he should beat and scoring more than his share of exceptional upsets (Wawrinka 2014, Goffin 2014, Melzer 2013 and Berdych 2011).

Zivojinovic provides a similar pattern with a record of 20-8 (71%), 72% better than expected. He tallied six wins out of ten matches in which Elo assigned him a win probability of less than 25%. Further, he only lost one match in when his pre-match odds of winning were greater than 35%.

This post provides insight into how Elo ratings help in quantifying a player’s performance. We identified players who have (not) shown great improvement on what the algorithm expected based on results from the regular tour. For future research it would be interesting to delve into Davis Cup doubles heroes: Where there are no dead rubbers, stakes are always high.

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Peter Wetz is a computer scientist interested in racket sports and data analytics based in Vienna, Austria.