Winning Return Points When It Matters

In my post last week about players who have performed better than expected in tiebreaks (temporarily, anyway), I speculated that big servers may try harder in tiebreaks than in return games.

If we interpret “try harder” as “win points more frequently,” we can test it. With my point-by-point dataset, we can look at every top player in the men’s game and compare their return-point performance in tiebreaks to their return-point performance earlier in the set.

As it turns out, top players post better return numbers in tiebreaks than they do earlier in the set. I looked at every match in my dataset (most tour-level matches from the last few seasons) for the ATP top 50, and found that these players, on average, won 5.2% more return points than they did earlier in those sets.

That same group of players saw their serve performance decline slightly, by 1.1%. Since the top 50 frequently play each other, it’s no surprise that the serve and return numbers point in different directions. However, the return point increase and the serve point decrease don’t cancel each other out, suggesting that the top 50 is winning a particularly large number of tiebreaks against the rest of the pack, mostly by improving their return game once the tiebreak begins.

(There’s a little bit of confirmation bias here, since some of the players on the edge of the top 50 got there thanks to good luck in recent tiebreaks. However, most of top 50–especially those players who make up the largest part of this dataset–have been part of this sample of players for years, so the bias remains only minor.)

My initial speculation concerned big servers–the players who might reasonably relax during return games, knowing that they probably won’t break anyway. However, big servers aren’t any more likely than others to return better in tiebreaks. (Or, put another way, to return worse before tiebreaks.) John Isner, Ivo Karlovic, Kevin Anderson, and Roger Federer all win slightly more return points in tiebreaks than they do earlier in sets, but don’t improve as much as the 5.2% average. What’s more, Isner and Anderson improve their serve performance for tiebreaks slightly more than they do their return performance.

There are a few players who may be relaxing in return games. Bernard Tomic improves his return points won by a whopping 27% in tiebreaks, Marin Cilic improves by 16%, and Milos Raonic improves by 11%. Tomic and Raonic, in particular, are particularly ineffective in return games when they have a break advantage in the set (more on that in a moment), so it’s plausible they are saving their effort for more important moments.

Despite these examples, this is hardly a clear-cut phenomenon. Kei Nishikori, for example, ups his return game in tiebreaks almost as much as Cilic does, and we would never think of him as a big server, nor do I think he often shows signs of tactically relaxing in return games. We have plenty of data for most of these players, so many of these trends are more than just statistical noise, but the results for individual players don’t coalesce into any simple, overarching narratives about tiebreak tendencies.

There is one nearly universal tendency that turned up in this research. When leading a set by one break or more, almost every player returns worse. (Conversely, when down a break, almost every player serves better.) The typical top 50 player’s return game declines by almost 5%, meaning that a player winning 35% of return points falls to 33.4%.

Almost every player fits this pattern. 48 of the top 50–everyone except for David Ferrer and Aljaz Bedene–win fewer return points when up a break, and 46 of 50 win more service points when down a break.

Pinning down exactly why this is the case is–as usual–more difficult than establishing that the phenomenon exists. It may be that players are relaxing on return. A one-break advantage, especially late, is often enough to win the set, so it may make sense for players to conserve their energy for their own service games. Looking at it from the server’s perspective, that one-break disadvantage might remove some pressure.

What’s clear is this: Players return worse than usual when up a break, and better than usual in tiebreaks. The changes are much more pronounced for some ATPers than others, but there’s no clear relationship with big serving. As ever, tiebreaks remain fascinating and more than a little inscrutable.

The Luck of the Tiebreak, 2015 in Review

Tiebreak outcomes are influenced by luck a lot more than most people think. All else equal, big servers aren’t any more successful than weak servers, and one season’s tiebreak king is often the next season’s tiebreak chump.

I’ve written a lot about this in the past, so I won’t repeat myself too much. (If you want to read more, here’s a good place to start.) In short, the data shows this: Good players win more tiebreaks than bad players do, but only because they’re better in general, not because they have special tiebreak skills. Very few players perform better or worse than they usually do in tiebreaks.

In the past, I’ve found that three players–Roger Federer, Rafael Nadal, and John Isner–consistently increase their level in tiebreaks. In other words, when you calculate how many tiebreaks Federer (or Nadal, or Isner) should win based on his overall rate of serve and return points won, you discover than he wins even more tiebreaks than that.

In any given year, some players score very high or very low–winning or losing far more tiebreaks than their overall level of play would suggest that they should. But the vast majority of those players regress back to the mean in subsequent years.

Here’s a look at which players outperformed the most in 2015 (minimum 20 tiebreaks). TBExp is the number of tiebreaks we would expect them to win, given their usual rate of serve and return points won. TBOE (Tie Breaks Over Expectations) is the difference between the number they won and the number we’d expect them to win, and TBOR is that difference divided by total tiebreaks.

Player              TBs  TBWon  TBExp  TBOE   TBOR  
Stan Wawrinka        46     34   24.9   9.1  19.8%  
Martin Klizan        25     17   12.2   4.8  19.0%  
Marin Cilic          35     26   21.0   5.0  14.2%  
Tomas Berdych        34     24   20.0   4.0  11.7%  
John Isner           64     39   31.7   7.3  11.3%  
Feliciano Lopez      42     27   22.4   4.6  11.0%  
Jiri Vesely          28     16   13.2   2.8  10.1%  
Sam Groth            31     18   14.9   3.1  10.1%  
Gilles Muller        45     27   22.7   4.3   9.5%  
Gael Monfils         28     18   15.4   2.6   9.4%

There are a lot of big servers here (more on that later) and a lot of new faces. Federer and Nadal were roughly neutral in 2015, winning exactly as many tiebreaks as we’d expect. Of the tiebreak masters, only Isner remained among the leaders. He has never posted a season below +5% TBOR, and only twice has he been below +11% TBOR. Just from this leaderboard, you can tell how elite that is.

Along with Isner, we have Marin Cilic, Feliciano Lopez, Sam Groth, and Gilles Muller, all players one would reasonably consider to be big servers. As I mentioned above, big serving doesn’t typically correlate with exceeding tiebreak expectations. It may just be a fluke: Lopez was roughly neutral in 2013 and 2014, and -15% in 2012; Groth doesn’t have much of a tour-level track record, but was -5% in 2014; Muller has been up and down throughout his career; and Cilic almost always underperformed until 2013.

Adding to the “fluke” argument is the case of Ivo Karlovic. His -14% TBOR this year was one of the worst among players who contested 20 or more tiebreaks, and he’s been exactly neutral over the last decade.

Let’s take a closer look at a few players.

Stan Wawrinka: For the second year in a row, he won at least 15% more tiebreaks than expected. Whether it’s clutch, focus, or dumb luck, the shift in his tiebreak fortunes dovetails nicely with his upward career trajectory. From 2006-13, he only posted one season at neutral or better, and his overall TBOR of -9% was one of the worst in the game for that span.

Cilic’s story is similar. Before 2013, he posted only one season above expectations. Since then, he’s won 19%, 16%, and 14% more tiebreaks than expected.

While only anecdotes, these two cases contradict an idea I’ve heard quite a bit, that players weaken in the clutch as they get older. The subject often comes up in the context of Karlovic’s tiebreak futility or Federer’s break point frustrations. It’s tough to prove one way or the other, in part because there’s no generally accepted measure of clutch in tennis. (If indeed there is any persistent clutch skill.) Using a measure like TBOR is dangerous, both because it is so noisy, and because of survivorship bias–players who get worse as they get older are more likely to fall in the rankings and play fewer tour matches as a result.

Another complicating factor is worthy of further study. To estimate how many tiebreaks a player should win, we need to take our expectation from somewhere. I’m using each player’s overall rates of serve and return points won. But if a player is trying harder in tiebreaks (assuming more effort translates into better results), we would expect that he would win more points in tiebreaks.

Isner has admitted to coasting on unimportant points, and for someone with his game style, a whole lot of return points can be classified as unimportant. Very generally speaking, the more one-dimensional the player, the more reason he has to take it easy during return games, and the more he does so, the more we would observe that he outperforms expectations in tiebreaks–simply because he sets expectations artificially low.

That might be an explanation for Isner’s consistent appearance on these leaderboards. And if we assume that players become more strategically sound as they age–or simply better at tactically conserving energy–we might have a reason why older players score higher in this metric.

Two more players worth mentioning are Milos Raonic and Kei Nishikori. They were 5th and 6th on the 2014 leaderboard, outperforming expectations by 15% and 14%, respectively. In 2015, Raonic fell to neutral, and Nishikori (in far fewer tiebreaks) dropped to -14%, nearly the bottom of the rankings. Taken together, it’s a good reminder of the volatility of these numbers. In Raonic’s case, it’s a warning that relying too much on winning tiebreaks (which, by extension, implies relying too little on one’s return game) is a poor recipe for long-term success.

Finally, some notes on the big four. Novak Djokovic and Andy Murray have never figured heavily in these discussions, both because they don’t play a ton of tiebreaks, and because they don’t persistently out- or underperform expectations. Federer and Nadal, however, were long among the best. Both have returned to the middle of the pack: Federer hasn’t posted a TBOR above 5% since 2011, and Nadal underperformed by 8.5% in 2014 before bouncing back to neutral last season.

Whatever tiebreak skill Roger and Rafa once had now eludes them. On the other hand, ten months of good tiebreak luck can happen to anyone, even a legend. If either player can recapture that tiebreak magic–even if it’s mere luck that allows them to do so–it might translate into a few more wins as they try to reclaim the top spot in the rankings.

The Dreaded Deficit at the Tiebreak Change of Ends

Some of tennis’s conventional wisdom manages to be both blindingly self-evident and obviously wrong. Give pundits a basic fact (winning more points is good), add a dash of perceived momentum, and the results can be toxic.

A great example is the tiebreak change of ends. The typical scenario goes something like this: Serving at 2-3 in a tiebreak, a player loses a point on serve, going down a minibreak to 2-4. As the players change sides, a commentator says, “You really don’t want to go into this change of ends without at least keeping the score even.”

While the full rationale is rarely spelled out, the implication is that losing that one point–going from 2-3 to 2-4–is somehow worse than usual because the point precedes the changeover. Like the belief that the seventh game of the set is particularly important, this has passed, untested, into the canon.

Let’s start with the “blindingly self-evident” part. Yes, it’s better to head into the change of ends at 3-3 than it is at 2-4. In a tiebreak, every point is crucial. Based on a theoretical model and using sample players who each win 65% of service points, here are the odds of winning a tiebreak from various scores at the changeover:

Score  p(Win)  
1*-5     5.4%  
2*-4    21.5%  
3*-3    50.0%  
4*-2    78.5%  
5*-1    94.6%

It’s easy to sum that up: You really want to win that sixth point. (Or, at least, several of the points before the sixth.) On the other hand, compare that to the scenarios after eight points:

Score  p(Win)  
2*-6     2.6%  
3*-5    17.6%  
4*-4    50.0%  
5*-3    82.4%  
6*-2    97.4%

At the risk of belaboring the obvious, when the score is close, points become more important later in the tiebreak. The outcome at 4-4 matters more than at 3-3, which matters more than at 2-2, and so on. If players changed ends after eight points, we’d probably bestow some magical power on that score instead.

Real-life outcomes

So far, I’ve only discussed what the model tells us about win probabilities at various tiebreak scores. If the pundits are right, we should see a gap between the theoretical likelihood of winning a tiebreak from 2-4 and the number of times that players really do win tiebreaks from those scores. The model says that players should win 21.5% of tiebreaks from 2*-4; if the conventional wisdom is correct, we would find that players win even fewer tiebreaks when trying to come back from that deficit.

By analyzing the 20,000-plus tiebreaks in this dataset, we find that the opposite is true. Falling to 2-4 is hugely worse than reaching the change of ends at 3-3, but it isn’t worse than the model predicts–it’s a bit better.

To quantify the effect, I determined the likelihood that the player serving immediately after the changeover would win the tiebreak, based on each player’s service points won throughout the match and the model I’ve referred to above. By aggregating all of those predictions, together with the observed result of each tiebreak, we can see how real life compares to the model.

In this set of tiebreaks, a player serving at 2-4 would be expected to win 20.9% of the time. In fact, these players go to win the tiebreak 22.0% of the time–a small but meaningful difference. We see an even bigger gap for players returning at 2-4. The model predicts that they would win 19.9% of the time, but they end up winning 22.1% of these tiebreaks.

In other words, after six points, the player with more points is heavily favored, but if there’s any momentum–that is, if either player has more of an advantage than the mere score would suggest–the edge belongs the player trailing in the tiebreak.

Sure enough, we see the same effect after eight points. Serving at 3-5, players in this dataset have a 16.3% (theoretical) probability of winning the tiebreak, but they win 19.0% of the time. Returning at 3-5, their paper chance is 17.2%, and they win 19.5%.

There’s nothing special about the first change of ends, and there probably isn’t any other point in a tiebreak that is more crucial than the model suggests. Instead, we’ve discovered that underdogs have a slightly better chance of coming back than their paper probabilities indicate. I suspect we’re seeing the effect of front-runners getting tight and underdogs swinging more freely–an aspect of tennis’s conventional wisdom that has much more to recommend itself than the idea of a magic score after the first six points of a tiebreak.

Does Serving First in a Tiebreak Give You an Edge?

Tiebreaks are so balanced, with frequently alternating servers and sides of the court, that it seems they must be fair. As far as I know, there is no commonly-cited conventional wisdom to the effect that the first server (or second server) in a tiebreak has any kind of advantage.

Let’s check. In a dataset of over 5,200 tiebreaks at ATP tour events, the first server won 50.8% of the time. Calculating each player’s service points won for the entire match and using those numbers to determine the likelihood that the first server would win a tiebreak, we get an estimate that those first servers should have won only 48.8% of them.

Two percentage points is a small gap, but here, it’s a meaningful one. It’s persistent across each of the three years most heavily represented in the dataset (2013-15), and it holds regardless of the set. While there might be some bias in the results of first-set tiebreaks, since better servers often choose to serve first and lesser servers choose to receive, the effect in each set favors the first server, and the impact of serving first is greater in the third set than in the first.

However, this effect–at least in its magnitude–is limited to ATP results. A survey of 2,500 recent WTA tiebreaks shows that first servers have won 49.7% of tiebreaks, compared to 49.4% that they should have won. Women’s ITF matches and men’s futures matches return similar results. Running the same algorithm on 6,200 men’s Challenger-level tiebreaks confuses the issue even further: Here, first servers won 48.1% of tiebreaks, while they should have won 48.7%.

A byproduct of this research is the discovery that, for both genders and at multiple levels of the game, the first server in a tiebreak is, on average, the weaker player. At first glance, that doesn’t make a lot of sense: We think of tiebreaks as deciding sets when the two players are equal. And since the effect is present for the second and third sets as well as the first, this finding isn’t biased by players choosing who will serve first.

As it turns out, this result can be at least partially explained by another byproduct of my recent research. In my attempt to determine whether it’s particularly difficult to hold when serving for the set, I calculated the odds of holding serve at every score throughout a set, compared to how frequently players should have held. At most holds–including those with the set on the line–there aren’t any major discrepancies between actual hold rates and expected hold rates.

But I did find some small effects that are relevant here. In general, it is a bit harder to hold serve as the second server, at scores such as 3-4, 4-5, and 5-6, than as the first, at scores like 3-3, 4-4, and 5-5. For instance, in the ATP data, players hold serve at 4-4 exactly as often as we would expect them to, based on their rate of service points won throughout the match. But at 4-5, their performance drops to 1.4% below expectations. In the WTA data, while players underperform at 5-5 by 1.4%, they are far worse at 5-6, winning 5.2% less often than they should.

In other words, if two players of equal abilities stay on serve for the first several games of a set, the second server is a little more likely to crack, getting broken and losing the set. Thus, if neither player is broken (or the number of breaks is equal), the second server is likely to be just a little bit better.

That explains, at least in part, why second servers are favored on paper going into tiebreaks. What it doesn’t account for is the discovery that on the ATP tour, first servers overcome that paper advantage and win more than half of tiebreaks. For that, I don’t have a good answer.

Nick Kyrgios, Young Jedi of the Tiebreak

At Wimbledon this year, 19-year-old rising star Nick Kyrgios has shown himself to be impervious to pressure. In his second round upset of Richard Gasquet, he tied a Grand Slam record by surviving nine match points. Against Rafael Nadal, he withstood perhaps the best clutch player in the game. Despite Nadal’s stature as one of the best tiebreak players in the game, the Australian won both of the tiebreaks they contested.

As I’ve shown in other posts, tiebreaks are–for most players–toss-ups. Better players typically win more than 50% of the tiebreaks they play, but that’s because they’re better players, not because they have some tiebreak-specific skill. Only a very few men–Nadal, Roger Federer, and John Isner are virtually alone among active players–win even more tiebreaks than their non-tiebreak performance would indicate.

Kyrgios is making a very strong case that he should be added to the list. In his career at the ATP, ATP qualifying, and Challenger levels, he’s won 23 of 31 tiebreaks, good for an otherworldly 74% winning percentage. Isner has never posted a single-season mark that high, and Federer has only done so twice.

Nick isn’t playing these matches against weaker opponents, and he isn’t cleaning up in non-tiebreak sets. (Too many scores like 7-6 6-1 might suggest that he shouldn’t have gotten himself to 6-6 in the first place.) Based on Kyrgios’s serve and return points won throughout each match, a tennis-playing robot would have had a 52% chance of winning each tiebreak.

Given those numbers, it’s extremely likely that Kyrgios is one of the outliers, a player who wins many more tiebreaks than expected. There’s only a 1% chance that his excellent winning percentage is purely luck. We can be 95% sure that a tiebreak winning percentage of 58% or better is explained by skill, and 90% sure that his tiebreak skill deserves at least a winning percentage of 62%.

Either one of these more modest figures would still be excellent. Milos Raonic, his quarterfinal opponent and a player who represents an optimistic career path for Kyrgios’s next few years, has posted a 58% tiebreak winning percentage at tour level. Tomorrow’s match won’t be enough to prove which player is better in these high-pressure moments, but given each man’s playing style, it’s almost certain that we’ll see Kyrgios tested in another batch of tiebreaks.

The Luck of the Tiebreak, 2013 Edition

Another year, another new set of tiebreak masters.

Despite the conventional wisdom, very few players demonstrate any kind of consistent tiebreak skill over and above their regular, non-tiebreak tennis playing ability.  In other words, while someone like Novak Djokovic is bound to win well over half of the tiebreaks he plays–after all, he’s better than almost everyone he faces–there’s no secret sauce that allows him to win any more than his usual skill level would suggest.

Nowhere is this more evident than in this year’s top tiebreak performers.  I calculated the likelihood of each player winning every tiebreak they played this year, given their typical rates of serve and return points won, giving us a ranked list of those players who most exceeded and most underperformed expectations.  At the top of the list, names like Roberto Bautista Agut, Dmitry Tursunov, Marin Cilic, and Leonardo Mayer.

Maybe Bautista Agut is a clutch monster just waiting for recognition, but it’s more likely he just had a few bounces go his way.  Cilic is an excellent example: While he won 54% more tiebreaks than expected this year, 2013 was only the second season of the last six in which the Croat exceeded expectations in tiebreaks.  Whether tiebreak performance is clutch skill or simply luck, the numbers show that it isn’t persistent.

However, as I’ve noted before, a very few players do consistently outperform tiebreak expectations.  They tend to be players who find themselves in tiebreaks often, and their success may be because they manage to maintain their serve at its usual level.

John Isner and Roger Federer are the usual suspects.  Isner won 20% more tiebreaks this year than expected, in line with his numbers in 2011 and 2012.  (In 2009 and 2010, he was even better.)  Federer beat expectations by 10%, avoiding his first neutral-or-worse season since 2003 by winning a pair of breakers against tough opponents at the Tour Finals in London.

With another year’s worth of data in the books, we can safely add one more active player to this elite group.  Rafael Nadal was fifth overall this year, winning 23% more tiebreaks than expected.  Nadal hovered around the neutral level until 2008, winning almost exactly as many breakers as his overall skill level would suggest.  But since then, he has had only good tiebreak seasons.  No other player besides Isner and Federer has posted more than four better-than-expected tiebreak seasons in the last six.

For the rest of the ATP, it’s best to look at these numbers as indexes of luck.  The men at the top will probably have to win more non-tiebreak sets next year to maintain their ranking, while the guys at the bottom can expect a modest boost with just a little less bad luck.  That is, unless they play too many tiebreaks against John Isner.

The complete list of 2013 tiebreak performance is below.  ‘TBOE’ is “Tiebreaks Over Expectations,” the difference between the number of tiebreaks my algorithm expects a player to win and the number he actually won.  ‘TBOR’ is a rate version of the same stat, calculated by dividing TBOE by the total number of tiebreaks played.  TBOE rewards players like Isner who play lots of tiebreaks and play them well, while TBOR identifies those who have been particularly lucky in whatever number of tiebreaks they contested.

Player                  TB  TBWon  TBExp  TBOE    TBOR  
Roberto Bautista Agut   21     16   10.3   5.7   27.0%  
Dmitry Tursunov         21     16   10.4   5.6   26.8%  
Marin Cilic             15     11    8.2   2.8   18.7%  
Leonardo Mayer          15      9    6.8   2.2   14.9%  
Rafael Nadal            25     18   14.6   3.4   13.6%  
Gilles Simon            25     16   12.7   3.3   13.0%  
Ivo Karlovic            29     18   14.8   3.2   11.1%  
John Isner              53     36   30.1   5.9   11.1%  
Andy Murray             23     16   13.5   2.5   11.0%  
Fabio Fognini           23     14   11.7   2.3   10.0%  
Juan Martin Del Potro   33     21   17.7   3.3   10.0%  
Benoit Paire            29     17   14.3   2.7    9.3%  
Philipp Kohlschreiber   33     19   15.9   3.1    9.3%  
Jerzy Janowicz          26     15   12.9   2.1    8.2%  
Jarkko Nieminen         27     14   11.9   2.1    7.9%  
Bernard Tomic           30     16   13.7   2.3    7.6%  
Julien Benneteau        24     14   12.4   1.6    6.9%  
Alexandr Dolgopolov     21     11    9.6   1.4    6.8%  
Ernests Gulbis          23     13   11.5   1.5    6.4%  
Tommy Haas              26     16   14.4   1.6    6.3%  
Jeremy Chardy           21     12   10.7   1.3    6.0%  
Roger Federer           25     15   13.6   1.4    5.4%  
Grega Zemlja            19     10    9.0   1.0    5.3%  
Feliciano Lopez         24     14   12.9   1.1    4.4%  
Jo Wilfried Tsonga      30     17   15.8   1.2    4.2%  
Ryan Harrison           15      7    6.4   0.6    4.1%  
Tommy Robredo           24     14   13.1   0.9    3.8%  
Novak Djokovic          28     19   17.9   1.1    3.8%  
Lleyton Hewitt          16      9    8.4   0.6    3.5%  
Daniel Brands           19     10    9.4   0.6    3.4%  
Fernando Verdasco       24     14   13.5   0.5    1.9%  
David Ferrer            21     12   11.8   0.2    1.0%  
Kei Nishikori           16      9    8.9   0.1    0.9%  
Martin Klizan           15      7    6.9   0.1    0.9%  
Kevin Anderson          35     19   19.1  -0.1   -0.2%  
Marinko Matosevic       16      9    9.1  -0.1   -0.4%  
Mikhail Youzhny         23     11   11.4  -0.4   -1.8%  
Milos Raonic            36     19   19.7  -0.7   -1.9%  
Sam Querrey             31     15   15.6  -0.6   -2.1%  
Stanislas Wawrinka      32     17   17.7  -0.7   -2.3%  
Florian Mayer           18      8    8.4  -0.4   -2.4%  
Gael Monfils            27     13   13.7  -0.7   -2.5%  
Igor Sijsling           19      9    9.5  -0.5   -2.6%  
Andreas Seppi           19      9    9.5  -0.5   -2.8%  
Denis Istomin           24     11   11.8  -0.8   -3.2%  
Richard Gasquet         29     15   16.0  -1.0   -3.4%  
Daniel Gimeno Traver    18      7    7.6  -0.6   -3.5%  
Vasek Pospisil          24     11   11.9  -0.9   -3.6%  
Tomas Berdych           34     17   18.6  -1.6   -4.7%  
Victor Hanescu          24     10   11.2  -1.2   -5.2%  
Ivan Dodig              27     12   13.5  -1.5   -5.7%  
Robin Haase             24     10   11.4  -1.4   -5.9%  
Albert Ramos            16      7    7.9  -0.9   -5.9%  
Benjamin Becker         18      7    8.1  -1.1   -5.9%  
Horacio Zeballos        20      7    8.2  -1.2   -6.2%  
Jurgen Melzer           19      8    9.4  -1.4   -7.4%  
Nicolas Almagro         34     17   19.5  -2.5   -7.5%  
Lukas Rosol             15      6    7.3  -1.3   -8.9%  
Evgeny Donskoy          17      6    7.7  -1.7  -10.2%  
Alejandro Falla         15      6    7.6  -1.6  -10.9%  
Grigor Dimitrov         22      9   11.5  -2.5  -11.4%  
Marcos Baghdatis        20      6    9.5  -3.5  -17.4%  
Carlos Berlocq          18      7   10.2  -3.2  -17.5%  
Juan Monaco             15      5    7.7  -2.7  -18.3%  
Janko Tipsarevic        19      5    8.7  -3.7  -19.5%  
Edouard Roger Vasselin  19      4    8.2  -4.2  -22.3%

Roger Federer and the Missing Tiebreaks (+Updated WTForecast)

For most of his career, Roger Federer has been one of the very few players to play better in tiebreaks than in standard deuce games.  His career record, winning breakers at a 65% clip, illustrates his success at the business end of tight sets.  But there’s more to the story.  Even a player a good as Federer has been should not have won that many tiebreaks.

As I wrote in a pair of posts a year ago, there is very little evidence for any kind of tiebreak-specific skill.  Some players do well in tiebreaks, of course, but their success is almost always due to being good in general–better players win more points, and that translates into tiebreaks.  Plenty of big servers, such as Ivo Karlovic and Milos Raonic, don’t win any more tiebreaks that you would expect simply by looking at the rate at which they win points.

However, a tiny fraction of players defy this regression to the tiebreak mean. Playing a ton of tiebreaks seems to help a bit–John Isner always wins more than expected–and a few other cases might be explained by extreme confidence or intimidations.  These include Pete Sampras and–you guessed it–King Roger.

In the eight seasons from 2004 to 2011, Federer won almost 10% more tiebreaks than his stats say he should have.  In 2006, his outrageous 37-14 tiebreak record was a big part of his equally outrageous overall success.  But even a player as good as Roger was that year “should” have only gone 31-20.  That would still have been an impressive win rate, and let’s not forget, many of his tiebreaks were against excellent players who had already pushed him that far.

As with so much else, that tiebreak magic has eluded Fed in the past two seasons.  Last year was the first season since 2003 when he failed to win more tiebreaks than expected.  He has been neutral this year and last.

It’s tempting to wonder, then, how big a part the disappearance of Roger’s tiebreak magic has played in his overall decline.  If he had won tiebreaks at the “extra” rate he did throughout his peak, he would have claimed two, or possibly three more than he actually did, flipping his pedestrian 13-10 tiebreak record to a more Fed-like 15-8 or even 16-7.  (This post was written before Fed’s tiebreak win over Djokovic in London on Tuesday.  In any event, improving his record to 14-10 doesn’t drastically change anything.)

How much of an impact would those bonus tiebreaks have had?  With a bit of guesswork and a handful of counterfactuals, we can put a number on it.  We’re looking at “flipping” two or three of Roger’s ten lost tiebreaks.  Of those ten, three didn’t end up mattering, as he won the match anyway.   The remaining seven occurred in five matches:

The final match in this list provides the simplest illustration of the math involved here.  Flip the lost tiebreak in the Delpo match, and Federer wins the title, earning 200 additional ranking points.  Since we’re only switching the outcome in two or three tiebreaks, that’s either a 20% or 30% chance of that particular tiebreak counting among those switched, for either 40 or 60 additional points.

It gets much more involved with something like the Stakhovsky loss.  Not only do we need to consider the different outcomes of flipping both tiebreaks (and Roger winning) and flipping just one (and Roger maybe winning), we also need to estimate Fed’s chances of progressing through the draw.  Despite the very early loss, Wimbledon was almost double the lost opportunity of any of the other matches, as his path to the semifinal would’ve gone through Jurgen Melzer, Jerzy Janowicz, and Lukasz Kubot.  To quantify the effect of flipping the Wimbledon outcome, we must consider the probability of his reaching those later rounds and the number of points he would have collected had he gotten that far.

Crunch all the numbers, and if you flip two tiebreaks, Federer gains about 380 ranking points.  Flip three, and it’s about 560.  Either of those numbers would move him in front of Berdych in this week’s rankings and given him a lot more breathing room on the road to London.  These bonus points would still have left a huge gap between him and the top five.

Perhaps more important than a few hundred ranking points, how different would the 2013 Federer storyline look if you flipped just a small number of those results?  Give him the 4th set against Stakhovsky and the 2nd with Delbonis, watch him win the deciders, and there’s a different Fed narrative for the summer.  Whether it’s bad luck, decreased confidence, less intimidation, or something else entirely, it’s crucial that we remember that tiebreaks are often decided by a single bad service point or great return point.  If a narrative can’t hold up against a couple of points going the other way, it probably isn’t telling us very much about a player’s actual performance level.

Yet, if Federer has turned a corner this fall, it would be a mistake to expect improved results to come from a resurgence of his tiebreak mojo.  Whatever mysterious factors cause a tiny minority of players to exceed tiebreak expectations, it seems less likely that fading 30-something Fed has them.  He certainly hasn’t benefited from them for the last two years.  But most of all, unless he gets back into more very high-profile matches–as he may this week–the few hundred points he could gain from tiebreak magic just won’t make much of a difference.

London forecast: Today, the results went as expected, with Nadal beating Ferrer and Novak defeating Federer.  Nadal was such a heavy favorite that his win doesn’t affect his chances much, but Djokovic enjoys a bigger bump. The top two seeds are now almost equal, while Federer faces increasingly long odds.

Player     3-0  2-1  1-2  0-3     SF      F      W  
Nadal      50%  42%   9%   0%  91.2%  52.5%  31.5%  
Djokovic   43%  46%  11%   0%  88.5%  54.4%  31.0%  
Ferrer      0%  29%  50%  21%  31.9%  12.2%   4.5%  
Del Potro  22%  50%  28%   0%  71.3%  36.6%  16.7%  
Federer     0%  30%  51%  20%  30.2%  14.1%   6.3%  
Berdych     0%  14%  48%  38%  16.4%   5.7%   2.0%  
Wawrinka   13%  48%  38%   0%  60.5%  21.2%   6.9%  
Gasquet     0%  10%  44%  45%  10.0%   3.3%   1.1%

Click here for the pre-tournament forecast.