Category: Grand Slams

Italian translation at settesei.it

In the middle of 2001, the Grand Slams doubled the number of seeds in the draw from 16 to 32, a change “designed to protect star players and satisfy clay and grass specialists.”

The intended beneficiaries of the change were, of course, all seeded players. Those in the top 16 no longer had to worry about facing a fellow top-32 player until the third round. Those ranked from 17-32, who before the change may have faced a top 16 player in the first round, now received the same protection.

The costs of the 32-seed system are borne by two groups: unseeded players, who are now more likely to face a top-ranked player early; and first-week fans, who would like to see more “compelling” early-round matches. While it’s easy to point to shock upsets like Serena Williams’s exit today as a counterpoint, the first two rounds at Slams often feel like warm-up matches for the biggest stars, with fringe players as their hapless foils.

On the other hand, it’s tough to get an intuitive sense of just how much is at stake here. It may not be as much as you think. From 1989 to 2000, men’s seeds were upset 263 times in the first two rounds of slams. Only 51 of those losses were to players in the top 32. In other words, more than 80% of those upsets would have occurred even with a 32-seed format, and presumably, some of the remaining 51 matches would still have resulted in upsets.

From the perspective of the top 16 seeds, there may not be that much difference between opponents ranked in the next 16 and those ranked lower still. To cherry-pick just one example, there are many seeded players Stanislas Wawrinka would have rather faced this week than Guillermo Garcia Lopez.

For top-four women, it hasn’t made a difference at all. In the twelve years before the switch, they reached the third round in 176 of 190 attempts. In the twelve years after the format change, women seeded 1-4 no longer risked facing a top-32 player in the first two rounds, and reached the third round in 178 of 191 attempts.

In fact, for top-16 women’s seeds in general, the 32-seed format has not helped. From 1989-2000, women’s seeds reached the third round 77.6% of the time, the fourth round 63.5% of the time, and the quarterfinals 40.8% of the time. From 2002-13, with lower-ranked early-round opponents, the corresponding numbers were 78.2%, 60.1%, and 37.1%.

It’s likely that some of the differences have to do with the increasing depth of the women’s game, but it’s hardly the case that the 32-seed format has drastically changed the nature of the majors, at least for the players who have been seeded all along. Men’s top-16 seeds have benefited, reaching the third, fourth, and quarterfinal rounds about 10% more often since the switch to 32 seeds, but even here, we’re not seeing radically different second weeks.

The real change, as you might suspect, appears when we consider the balance of power between the new seeds (17-32) and the rest of the field. From 1989-2000, when there were only 16 seeds and those two groups were treated the same way, men’s players ranked 17-32 reached the third round about twice as often (35% to 17%) as their lower-ranked competitors. Women in the 17-32 range held a wider advantage of 39% to 15%.

Now that there are 32 seeds and the 17-32 group is protected, those gaps have substantially grown. From 2002-13, men seeded outside the top 16 have reached the third round 53% of the time, compared to 12% for unseeded players. Seeded women in the 17-32 range have reached the third round 49% of the time, while unseeded women have equaled their male counterparts at 12%.

These differences, big as they are, aren’t going to affect most fans’ enjoyment of the majors. The format change means that Rafael Nadal faces a player ranked 60th in the world in the second round and a player ranked 30th in the third round. He’ll almost always win both matches, so the end result is the same. A surprise run to the quarterfinals isn’t much different if it’s made by world #25 than by #50.

However, the 32-seed format does amplify the gap between tennis’s haves and have-nots. Yes, he Grand Slams have massively increased prize money in the last few years for all main-draw competitors–first-round losers in Paris earn more than $32,000 for their efforts. But players who reach the third round are able to triple that money.

As we’ve seen, the format change has made it much more likely that #32 reaches the third round (and takes home a nearly six-figure purse) at the expense of everyone ranked lower–despite having little effect on the makeup of the field in the fourth round and beyond.  Plus, the ranking points on offer at Slams mean that third-rounders are that much more likely to earn a seed at the next major, starting the next round of the same cycle.

Seeding 32 players instead of 16 doesn’t have much of an effect on the fates of top players, especially on the women’s side. It can, however, lessen interest in the first several days of play, and it certainly supports an arbitrary middle tier of players at the expense of the rest of the field.

If the 32-seed era were to end here, there’s little reason for tennis fans to miss it.

Italian translation at settesei.it

The best-of-five-sets format used in Grand Slam men’s singles favors the mentally and physically strong. It also gives better players the edge, as it reduces the number of fluky results.

However, simple best-of-five records aren’t always our most useful guide. A player who consistently goes deep in slams faces difficult opponents far more frequently than he would at ATP 250 or 500 events.  We would expect that many players would have worse records in best-of-five matches not because of any tendency, but because of consistently tough draws.

If we accounted for all that–opponent quality and the structural bias toward favorites in best-of-fives–who would come out strongest? Which players outperform expectations the most in Grand Slams?

Let’s start with a few names you might not expect, before we narrow the search down to players with the longest resumes:

• Of players with 100 career tour-level matches, the man who has outperformed the most at Slams is Bernard Tomic. In 35 matches at majors, he has won 20 despite his rankings suggesting he would win only 11–82% better than expected. Outside of slams, he has precisely played to his ranking.  Modest as Bernie’s track record is, no other active player comes close to this gap.
• Bump the threshold to 200 career matches, and your man is … Denis Istomin? His 21-21 record at Slams doesn’t seem so impressive until you consider that he has never been seeded. His rankings would imply he should have won only 16 matches.
• The parade of underdogs continues when we up the standard to 300 career matches. Victor Hanescu has outperformed best-of-five expectations by a solid 20%, going 28-32 while his lowly rankings would suggest he should have won only 23 matches.

Let’s move on to the big dogs. I meant to limit this study to active players, but when you go far enough back to cover the careers of guys like Radek Stepanek and Tommy Haas, you end up getting a lot of notable former stars. And here, Marat Safin stands out.

Safin’s career mark in slams was 95-41, excellent by any standard. His winning percentage of about 70% was about 14% higher than the combination of his rankings and his opponents would have predicted. While he exceeded expectations in Slams, he underwhelmed in other events.  He won almost 10% fewer best-of-three matches than would have been expected over the course of his career.

No current top-ten player displays as big a gap between best-of-five and best-of-three performance than Safin did, but Jo Wilfried Tsonga comes the closest. In this table, I’ve shown each player’s career record at majors, how that compares to the number of wins they should have expected, then the same pair of numbers for non-slams. (I’ve excluded all Davis Cup matches.) Finally, the “ExpRat” column shows how much better each guy played at majors than at non-majors–the ratio of how much more the player exceeded expectations at Slams than elsewhere.

Player                 Bo5 W%  Bo5 Exp  Bo3 W%  Bo3 Exp  ExpRat  
Jo Wilfried Tsonga      76.6%     1.17   66.6%     0.98    1.19  
Tomas Berdych           69.3%     1.06   63.1%     0.95    1.12  
Stanislas Wawrinka      67.0%     1.17   58.6%     1.08    1.08  
Novak Djokovic          85.3%     1.06   79.2%     0.99    1.07  
Rafael Nadal            88.3%     1.07   82.1%     1.01    1.06  
Andy Murray             79.6%     1.05   73.7%     1.03    1.02  
Roger Federer           84.4%     1.01   79.2%     1.00    1.01  
David Ferrer            70.6%     0.95   65.6%     0.96    0.99  
Richard Gasquet         64.0%     1.04   63.5%     1.09    0.95  
Juan Martin Del Potro   72.9%     1.13   72.5%     1.24    0.91

It’s inevitable that the Big Four make up the middle of the pack. When you are as good as they have been for as long as they have been, you can only exceed expectations so much. Most impressive of the group is Rafael Nadal, who has been better at majors than non-majors despite vastly preferring clay courts. Many of the journeyman players who do the worst by this metric are clay specialists–guys like Filippo Volandri and Potito Starace who are virtually guaranteed first-round exits at three slams each year.

While Juan Martin del Potro‘s appearance at the bottom of this list seems particularly timely after last night’s upset, it may be no more than a statistical fluke stemming from his long absence and long comeback in 2010 and 2011.  His ranking lagged behind his skill level for a long time, which explains why he has managed to exceed expectations both at Slams (+13%) and at non-majors (+24%). The loss to Roberto Bautista Agut won’t help his numbers, but it may take several more slams before we can be more confident about Delpo’s best-of-five tendencies.

When Tsonga and Roger Federer clashed in last year’s Melbourne quarterfinals, Federer escaped in five sets. If, as expected, they face off this year as well, these numbers represent one reason why Fed might not be so lucky again.

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For further reading, check out Colin Davy’s similar study.