Category Archives: Australian Open

Uncontrolled Aggression

Listen to tennis commentary–or a broadcast of any sport, really–and wait for the first mention of “consistency.” You won’t have to wait for long.

“Consistent” is good, and “inconsistent” is bad. Or so we’re told. At first blush, it makes sense. Consistency is a good thing when it comes to following through on your forehand or brushing your teeth every day. But unless you’re the very best player in the world, consistency doesn’t win you Grand Slam titles.

Think of it this way: Every player has an “average” level they are capable of playing. If average Rafael Nadal plays average anybody else on clay, average Nadal wins. If average Richard Gasquet plays average anybody-outside-the-top-fifty, average Gasquet wins. These situations, for the likes of Nadal and Gasquet, are when consistency is actually a good thing. Sure, Rafa might be able to raise him game to previously unheard-of heights, but what’s the point? It’s a matter of winning 6-1 6-0 instead of 6-3 6-2. Nadal’s main concern is avoiding an off day.

Consider the same example from the perspective of Rafa’s opponent. If you’re Tomas Berdych and you play at your usual level against Nadal, you’ll lose. That’s what consistency gets you: thirteen straight losses.

Uncontrolled aggression

Very aggressive players tend to get a bad rap. The guys who always go for their shots–think Lukas Rosol or Nikolay Davydenko–rack up huge winner and unforced error counts. Sometimes it works and often it doesn’t. When it doesn’t, the conventional wisdom always seems to be that these players need to rein in their aggression. They need to be more consistent.

But they don’t. If Rosol stopped unleashing huge shots in every direction, he’d make fewer unforced errors, but he’d hit far fewer winners. He might still hover around #50 in the world, but more likely, he’d still be lurking in the Challenger ranks, looking for the breakthrough that such a passive style might never earn for him. As it is, Rosol’s go-for-broke approach got him that career-defining upset over Nadal, not to mention an ATP title in Bucharest last spring, when he beat three higher-ranked players.

Rather than the pundit’s favored phrase of “controlled aggression,” players score big upsets and major breakthroughs with uncontrolled aggression. (It only looks controlled because it’s working that day.) If you rein in an aggressive player, he may win more of the matches he’s supposed to win, but he’s much less likely to score an upset.

The balance myth

The game of tennis has so much variety–surfaces, climates, playing styles–and so much alternation–deuce/ad, serve/return–that pundits are constantly endorsing balance. Andy Murray needs to get better on clay, they say. Jerzy Janowicz needs to improve his return game. Monica Niculescu needs to learn how to hit a forehand.

It’s a tempting argument to make, because the best players in the game do have that balance. Nadal and Djokovic and Serena and Li have a wide variety of devastating shots and tactics that are effective on every surface. If you want to play like them and reap the same rewards, you need to have that same balance.

Except that, for the vast majority of players–even top-tenners–that just isn’t going to happen. I don’t care if David Ferrer hires a coaching team of Pete Sampras and Mark Philippoussis, he’ll never be much more effective on serve. John Isner could work all offseason with Andre Agassi and remain among the game’s weakest returners.

What’s keeping these players from climbing any higher in the rankings isn’t the fact that they aren’t more balanced. It’s the simple fact that they aren’t better. By definition, most people will never be a once-in-a-generation talent.

Most players are not balanced. And that’s fine. Rather than chasing the impossible dream of out-Novaking Novak, they need to take more risks to outplay their betters in one or two areas. When it doesn’t work, it doesn’t matter–they would’ve lost anyway.

The cluster principle

Tennis rewards the streaky. If you only win four return points in a set, it’s much better to win them consecutively than to spread them out. It’s better to win five matches in one week and go winless for the next four weeks than win one match per week.

Whether it’s points, games, sets, matches, or even titles, it’s better to cluster your triumphs.

If you strive for a balanced game, the best players simply won’t let you go on a streak. Fabio Fognini or Sabine Lisicki might give you a few gifts, but Nadal never will. The only way to cluster your victories over Rafa is to play such aggressive tennis that even he can’t neutralize it. It usually won’t work, but for most players, it’s their only hope. There’s a reason the hyper-aggressive Davydenko is the only active player with a winning record against him.

Stan’s untold narrative

Stanislas Wawrinka probably wouldn’t have beaten a healthy Nadal over five sets on Sunday. But he was winning when Rafa’s back acted up, and he did so by unleashing every weapon in his arsenal.

Whatever the rankings say this week, Wawrinka isn’t one of the best three tennis players in the world. At least “average Stan” isn’t. But that’s the whole point. Tennis doesn’t reward players with ranking points and prize money for consistency. Consistency got Berdych into the top ten and has kept him there for so long … but it has prevented him from spending much time in the top five.

Wawrinka won’t always beat Nadal or Djokovic, and he’ll continue to suffer his share of defeats at the hands of the players ranked below him. The high-risk style of play that earned him a place in the history books won’t always pay off. That’s all part of the package. Stan didn’t get this far by being consistent.

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Filed under Australian Open, Stanislas Wawrinka, Tactics

A Glimmer of Hope for Stan Wawrinka

Stanislas Wawrinka has played 26 sets of tennis against Rafael Nadal, and lost them all. That doesn’t bode well for Stan’s chances in his first Grand Slam final.

As Novak Djokovic can tell you, though, Wawrinka has improved. He has long been a threat to top-ten players, and even before beating Djokovic in the quarterfinals, he had taken the Serb to five sets twice in twelve months.

One of the hidden signs of Stan’s rise comes from his last match with Rafa, at the London Tour Finals last November. Wawrinka lost that match in straight sets–as he has done, of course, every time he’s played Nadal–but it was the tightest match they’d played in four years, going to a pair of tiebreaks.

If we look beyond the scoreline, last fall’s contest was even closer than the pair’s previous two-tiebreak match at the 2009 Miami Masters. This time, Wawrinka won more points than Nadal did–83 to 80, good for 51% of the total. While it isn’t unheard of for the player who wins more points to lose the match, the player who wins more points does end up triumphant in more than 95% of tour-level matches. In their eleven previous meetings, Stan had never won as many as 48% of the total points played.

The quality of Wawrinka’s performance is even more striking when we turn to Dominance Ratio (DR), the ratio of the winner’s rate return points won to the loser’s rate return points won. In 93.5% of matches, the winner of the match is the man who won the higher rate of return points. By expressing this as a ratio, we can get an idea of the winning player’s dominance. 1.0 is a dead heat, and the higher than number, the more dominant the winning player.

In the match last November, Nadal’s DR was 0.86. Rafa won 31.1% of return points while Stan won 36.0%. If you look at 100 straight-sets matches with those stats, you’ll rarely find even one in which the 31.1% RPW player comes out the winner.

In fact, since 1991, there have been fewer than 150 matches in which a player had a DR less than or equal to 0.9 and still won in straight sets. (Matches that go the distance more commonly have this sort of profile, when the winner takes two [or three] tight sets but loses a blowout set, with a score like 7-6 1-6 7-6.)  Only about 50 of these were more extreme than the Nadal-Wawrinka match.

Based on the evidence of this last matchup, we can conclude that Wawrinka has the skills to challenge Nadal. Yet despite coming much closer than in any of their eleven previous meetings–Rafa’s lowest DR in any of them was 1.13–the Swiss didn’t win. Why not?

Let’s recognize the core issue: Stan may have won more points, but he won them at the wrong times. (Or, he didn’t win quite enough of them at the right times.) He held serve more convincingly than his opponent did but didn’t play as well in the tiebreaks. Any explanation has to address this “wrong time” issue. Here are a few:

  1. Nadal raised his game in the important moments. There’s some evidence for this–he outperforms expectations in tiebreaks, and he also wins more break points than non-break points. Some of the break point advantage comes from being left-handed (and taking proper advantage of it), though his break point advantage seems to be even bigger than his lefty advantage.
  2. Wawrinka faltered in the important moments. From the stat sheet of a single match, it would be tough to distinguish this from the first explanation. But perhaps he was overwhelmed by the opportunity he had generated for himself.
  3. Luck. Randomness in tennis isn’t limited to net cords, bad calls, and mishits. If you put two tennis-playing robots out on the court and had them play five consecutive matches, the result wouldn’t be the same every time. Wawrinka misses shots sometimes, and according to the stat sheets (though I’ve never seen it myself), Nadal does too. Just because one of those errors comes at a key moment doesn’t mean the man who committed it is a mental midget.

As much as we like to assign narratives to every possible nook and cranny of a tennis match, I suspect the truth of the matter is a hefty dose of #3 with a bit of #1 thrown in. When the outcome of a match comes down to two seven-point tiebreaks, it’s anybody’s game. It just wasn’t Stan’s that day.

If I’m right, there just might be hope for Wawrinka today. In his last two sets against Nadal, he held his own, which is more than just about everybody else on tour can say for themselves.

Unfortunately for Stan, one meeting doesn’t outweigh eleven, and a bit of momentum won’t erase Rafa’s well-earned status as the world #1. Perhaps worst of all, Wawrinka has proven himself Nadal’s almost-equal in two sets. Today, he’ll have to win three.

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Bouchard, Radwanska, and Second Serve Futility

In yesterday’s women’s semifinals, we were treated to some impressive return-of-serve performances. Li Na won almost 65% of points on Eugenie Bouchard‘s serve–a higher percentage than she won on her own.

A less positive view of the situation is that we saw some dreadful serving performances. In particular, both Bouchard and Agnieska Radwanska struggled to win any points at all on their second serves. Genie won just 5 of 27 after missing her first serve, while Aga won only 2 of 16.

You don’t need an IBM Key to the Match to realize that those numbers aren’t going to cut it.

The WTA features a more return-oriented game and more breaks of serve than the ATP does, but these numbers are far out of the ordinary, especially for a solid server such as Bouchard. Here are some circuit-wide averages, derived from about 1,000 tour-level matches played last season:

  • WTA players win 55.5% of service points: 62.3% on first serves and 44.6% on second serves.
  • When the second serve lands in play–in other words, excluding double faults, players win 51.8% of second-serve points.
  • In the average losing performance, players won 57.1% of first-serve points, 40.0% of second-serve points, and 47.2% of second-serve points in play.

Then again, Li and Dominika Cibulkova–especially the Slovakian–aren’t average returners. In 16 Cibulkova wins for which I have serve statistics, she never failed to win at least half of second-serve return points. Only once did she win less than 58% of them, and her median performance was a whopping 63% of second-serve points won. In 7 of the 16 matches, she won second-serve return points at a higher rate than her own first-serve points.

Domi’s dismantling of Radwanska’s second serve still stands out, but in this context, it doesn’t look quite so unusual. When Cibulkova is hitting the ball well, you might as well be throwing batting practice once you miss your first offering.

While Li’s best return performances don’t quite stack up with Cibulkova’s, she has little trouble neutralizing her opponents in Melbourne. In six matches, she has won more than half of second-serve return points in every match, peaking with a 12-of-15 performance in the fourth round against Ekaterina Makarova. Overall, Li has won 86 of 136 second-serve return points in the tournament, good for 63%.

On Saturday, one of these powerful forces will have to give way to the other. The last time Li and Cibulkova met, in Toronto last summer, Domi had one of her worst serving performances of the year, winning only 35.5% of second-serve points, 44.0% of those that landed in play. In that match, Cibulkova failed to display the dominating return game that has been her trademark in Australia, winning barely half of Li’s second offerings, and only 41% when excluding double faults.

But as Cibulkova showed by crushing Radwanska for only the second time in six career meetings, her performances aren’t predictable. Her all-or-nothing style guarantees that we’ll see some fireworks in the final from both servers and returners. And at the rate she’s going, Domi might set some more records in the process.

For even more detailed analysis of yesterday’s semifinals, check out the charting-based analysis of Li-Bouchard and Radwanska-Cibulkova.

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Filed under Australian Open, Serve statistics, WTA

Surprise Semifinalists at the Australian Open

Of the eight singles semifinalists in Melbourne, only two entered the tournament seeded in the top four. Rafael Nadal, the top seed in the men’s draw, has survived, and Li Na, the fourth seed in the women’s draw, is the highest-ranked player still alive on her side.

We haven’t exactly followed the script.

The women’s singles draw, with the top three seeds eliminated, is particularly unusual. It is only the 10th time in the last 35 years that none of the top three seeds have made it through to the final four of a Grand Slam. Such events have been heavily concentrated in the last decade or so–the fourth seed was the highest-ranked surviving player at Wimbledon in 2011 (Victoria Azarenka) and 2013 (Agnieszka Radwanska), and the fifth seed was the apparent favorite at Roland Garros in 2011 (Francesca Schiavone).

You might notice a pattern. In these nine Slams when no top-three seed reached the semifinal stage, the best remaining player didn’t fare so well. Both Vika and Aga fell to lower-ranked opponents when they were the remaining favorites at Wimbledon, and Schiavone lost her shot at the French Open to Li. Only twice in these nine majors did the highest-remaining seed in the semifinals go on to win: Martina Hingis, when she was seed fourth at the 1997 Australian Open, and Anastasia Myskina, when she was the sixth seed at the 2004 French Open.

In a tournament full of surprises, we might not be done yet. It stands to reason that once the favorites are eliminated, the odds of subsequent upsets increase. The lower you go in the rankings, the less difference there usually is between players–there’s a bigger gap between Azarenka and Maria Sharapova than there is between, say, Jelena Jankovic and Angelique Kerber. The smaller the gap, the more likely the upset.

While only one top-four seed remains in the men’s draw, the odds of upsets are moving in the opposite direction. While Nadal can always count on a tough fight from second-seed Novak Djokovic, he typically has little trouble with lower-ranked players. He has won his last 15 matches against the other three players left in the drawRoger Federer, Tomas Berdych, and Stanislas Wawrinka–and lost only 4 of 41 matches against the trio since 2008.

The historical precedent for this sort of semifinal draw also favors Rafa. 14 Grand Slams in the Open Era have featured a semifinal round in which the top seed is the only one remaining of the top four. The top seed has gone on to win 9 of the 14, including 8 of the last 10. The most recent final four that fit this profile was in Melbourne four years ago, when Federer swept the final two rounds without losing a set.

But even this rosy picture for Nadal offers Roger a glimmer of hope.  The last time the top seed was alone in the final four and didn’t go on to win was the 2002 US Open. Lleyton Hewitt was the #1 who failed, paving the way for a 31-year-old Pete Sampras to win one final slam before he retired.

Roger isn’t going to call it quits this week, but he’d sure like to emulate Pete’s success in seizing a wide-open Grand Slam draw.

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A Quarterfinal on Federer’s Racquet

The Roger Federer-Andy Murray head-to-head is a bit of a baffling one. In twenty career meetings–18 of them on hard courts–Murray has won 11, including four of the last five.

Yet for a superficially tight one-on-one record, Fed and Murray haven’t played many tight matches against each other, especially lately. When they went five sets in last year’s Australian Open semifinal, it was the first time they had gone the distance in ten matches. The outcome of a match between them is up for grabs, but whoever wins it tends to do so by a handy margin.

Even that five-set semifinal last year wasn’t as close as it looked. Murray won 54.0% of total points and racked up a Dominance Ratio (DR) of 1.32, meaning that he won far more return points than Roger did. Five setters are usually much closer to 50% and 1.0, respectively. While Murray won far more points, Federer displayed his historically-great tiebreak skill to keep himself in the match.

DR is a convenient measure of the closeness of a match, where 1.0 is a dead heat. Only two Fed-Murray matches–both before 2009–fell in the range between 0.85 and 1.15. By contrast, Novak Djokovic and Rafael Nadal have played seven matches (including two Grand Slam finals) in that range, and Djokovic and Murray have played five.

Tactical nonsense

To traffic in conventional wisdom for a moment, Federer is the most aggressive of the Big Four, while Murray is the most passive. To the extent Andy is likely to hurt Roger, it has more to do with his ability to force Fed into trying to do too much, particularly on the backhand side. If Federer plays patiently and picks his spots, he can crush Murray. If he plays too passively or hits bunches of unforced errors, it can be a rough day at the office.

However, there may not be much Murray can do to determine which Roger shows up.  Simply forcing Fed to hit backhands certainly isn’t enough. The Match Charting Project has amassed shot-by-shot data, including the number of groundstrokes hit from either side, for 23 Federer matches so far. Nadal is particularly good at directing the ball to Federer’s backhand, forcing Roger to hit 56% to 58% of groundstrokes from the backhand side in both a win (last year’s World Tour Finals) and a bad loss (the 2011 Tour Finals).

Taking the average of these 23 matches (most of which are Federer wins, as the Match Charting Project seems to have drawn lots of Fed fans), Roger hits 52.5% of his groundstrokes from the forehand side. This reflects the balance of two factors: Federer wanting to hit his forehand, and opponents trying to keep the ball away from it.

Surprisingly, hitting lots of balls to Fed’s backhand side seems to have few benefits. There is no meaningful correlation between DR and the percentage of groundstrokes Fed hit on the backhand side.

Based on the limited data available, it appears that Murray has tried a variety of tactics.

In the two Fed-Murray matches for which we have shot-by-shot data–the 2010 Australian Open final and the 2012 Dubai final–Murray took opposite approaches to the problem. In the Melbourne final, he managed to direct 57% of balls to Fed’s backhand, which is as good as anyone but Nadal has managed. In the Dubai match, Roger hit 64% of his groundstrokes from the forehand side, the second-highest rate of any of the 23 Federer matches in the database.

In both cases, Murray lost. To take another example, Juan Martin del Potro has beaten Fed while letting him hit 57% forehands and lost to him while forcing him to hit 57% backhands.

The database–limited in matches and biased as it is toward Fed’s victories–probably can’t take us any farther. But from here, we can speculate that Federer has it in his power to win or lose regardless of the tactics thrown his way. Murray, like Nadal, has always forced him to hit one extra ball. The sort of aggression that takes a player far out of position to hit, for instance, an inside-out forehand can backfire against such a talented defensive player.

In four matches at the Australian Open so far, Federer has offered us plenty of glimpses of his glory days. Murray will likely prove to be his biggest test of the tournament, but Fed’s fate still hangs on his own racquet.

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Filed under Andy Murray, Australian Open, Match charting, Roger Federer

The Geriatric Australian Open

You’ve probably heard about the steady aging of professional tennis.  In both the men’s and women’s games, fewer teenagers than ever are winning important matches, and more and more thirty-somethings are remaining at the top of the game.

My favorite illustration: 25 years ago, the oldest man in the Australian Open draw was Johan Kriek, about two months short of his 31st birthday when the tournament began.  This year, 24 men in the main draw are older.

A total of 33 men in the singles draw have reached their fourth decade, only the third time in tournament history that the number has exceeded 20.  If lucky loser Stephane Robert replaces the injured Gilles Simon, we’ll have 34 thirty-somethings, tied with the all-time record, set in 2012.

Even without Simon’s withdrawal, we already have a record for average age in the men’s draw.  That figure this year is 27 years and 126 days, 80 days more than the previous record, set last year.  (Replacing Simon with Robert would add another 11 days to the average.) The new record also marks the seventh consecutive year that the average age of the men’s singles draw has increased.

While the age of the women’s draw isn’t quite record-setting, the rise of thirty-somethings in the women’s game has been even more rapid.  Only 13 years ago, in 2001, Els Callens was the only woman over the age of 30 in the draw (she was a mere 156 days past her 30th birthday).  This year, there are a record-high 15 players over the age of 30 in the women’s singles draw.

The 2012 Aussie Open field remains the oldest on record, at 24 years and 321 days.  This year’s draw–at 24 years and 292 days–is close enough that, had 16-year-old Ana Konjuh lost her third-round qualifying match to Olga Savchuk, ten years her senior, we would be looking at a new record.

Long term trends and the folly of forecasting

By just about any metric you might devise, the game has gotten steadily older for about 25 years.  As with any trend in the news, this one has led too many commentators–both casual and more academic–to claim that this is a permanent trend, or that “you’ll never see another teenage tennis champ.”

Protip: Never put your money on “never.”

What these arguments often fail to account for is that, for about twenty years after the inception of the pro game in the late 1960s, the sport–both men’s and women’s–consistently got younger.  When the 2012 Wimbledon men’s draw broke that event’s record for average age, the record it was breaking was from 1968.

Sure, there are plenty of possible explanations for the steady age decline of the 1970s and 1980s, just as there are many for the current increase.  And there are probably hard limits at either extreme that prevent the age of the game from swinging too far in either direction.

In any case, we’re not in the middle of an infinite rise in ages any more than we were amid an endless decline in 1985.  Twenty years from now, the 2014 Aussie Open data points could be an meaningless step on this upward path or an important inflection point in another shift in the game.  We’re unlikely to see a teenage Slam champ next year, or the year after that, but is it really possible to make a sensible case that, in six years, today’s 12-year-olds will be helpless against today’s 24-year-olds?

What we can be confident about is what has happened, and even without accounting for the return of Pat Rafter, this year’s Melbourne field represents yet another data point in the aging of elite-level tennis.

Detailed stats: Lots of great things are happening with the Match Charting Project. Several people have stepped forward and started contributing to the project already this year, and we’re up to 144 matches in the database.  From Day One in Australia: Bencic vs Date-Krumm, Venus vs Makarova, and Errani vs Goerges.  I hope you’ll join in the fun.

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Filed under Aging trends, Australian Open

Winners and Losers in the 2014 Australian Open Men’s Draw

Every draw carries with it plenty of luck, but even by Grand Slam standards, this year’s Australian Open men’s singles draw seems a bit lopsided.  The top half makes possible a Rafael Nadal-Roger Federer semifinal, at least if Federer gets past Andy Murray and Nadal beats the likes of Bernard Tomic.

While Novak Djokovic is seeded below Nadal, he gets the benefit of a projected semifinal matchup with David Ferrer.  A more substantial challenge may arise one round earlier, as a possible quarterfinal opponent is Stanislas Wwrinka, who took Djokovic to a fifth set twice in the last four Grand Slams.

As I’ve done in the past, let’s quantify each player’s draw luck.  Using my forecast, combined with a forecast generated by randomizing the bracket, we can see who were the biggest winners and losers in yesterday’s draw ceremony.

The algorithmic approach is most useful in confirming our suspicions about the draw luck of the top players.  Djokovic and Ferrer, the top seeds in the bottom half, definitely came out ahead.  While Djokovic had a respectable 28.0% chance of winning the tournament in the randomized projection, he has a 33.7% chance given the way the draw turned out.  In turns of expected ranking points, the draw gave him a 10.7% boost, from an expectation of 747 points to one of 827 points.  In percentage terms, Ferrer’s expectation jumped even more, from 312 to 368 (18.0%).

Nadal, however, had the worst draw luck of the top ten seeds.  Before the bracket was arranged, he had a 30.7% chance of winning the title, with an expectation of 763 ranking points.  Once the draw was set, his title chances fell to 24.9% and his point expectation dropped to 662.  No one else in the top ten lost more than 7% of their expected ranking points on draw day; Nadal lost 13%.

It doesn’t take an algorithm, though, to identify the draw’s worst losers.  They’re placed where you’ll always find them: right next to the top two seeds.  In the randomized projection, Tomic had a 58% chance of winning his first-round match and a 27% chance of reaching the third round.  In reality, though, he’ll play Nadal first.  His slight chance of earning a place in the second round gives him an expectation of 29 ranking points (10 of which he earns simply by showing up).  In the random projection, his ranking point expectation was 75.

Lukas Lacko, the unlucky man who will play Djokovic in the first round, didn’t suffer quite so much, if only because he didn’t have as high of expectations in the first place.  Before the draw, he could expect 48 ranking points and a 15% chance of reaching the third round.  Now, his projection is a mere 24 ranking points, one of the worst in the entire draw.

The luckiest players are always those who had little chance of progressing far in the draw, but managed to draw someone equally inept.  At the Australian Open, the four luckiest guys have yet to be identified: all are qualifiers.  The luckiest man of all will be the one who is placed in the topmost qualifying spot, opposite Lucas Pouille.  At this stage, my rating system doesn’t think much of the Frenchman, so it is likely that the qualifier will be the heavy favorite entering that match.

In the randomized projection, each qualifier has a 29% chance of winning his first match and a 6% chance of winning his second, for a weighted average of 32 ranking points.  The man who plays Pouille, however, will enter the field with an expectation of 55 ranking points.  Other qualifiers with nearly the same happy outcome will be those who draw Federico Delbonis, Julian Reister, and Jan Hajek in the opening round.

Here are the pre-draw and post-draw expected ranking points of the men’s seeds, along with the percentage of pre-draw points they gained or lost:

Player                 Seed  Pre  Post  Change  
Rafael Nadal           1     763   662  -13.2%  
Novak Djokovic         2     747   827   10.7%  
David Ferrer           3     312   368   18.0%  
Andy Murray            4     473   488    3.1%  
Juan Martin Del Potro  5     421   393   -6.6%  
Roger Federer          6     411   397   -3.4%  
Tomas Berdych          7     264   317   20.2%  
Stanislas Wawrinka     8     290   279   -3.9%  

Player                 Seed  Pre  Post  Change
Richard Gasquet        9     186   186    0.1%  
Jo Wilfried Tsonga     10    151   187   23.8%  
Milos Raonic           11    223   234    5.0%  
Tommy Haas             12    207   222    7.5%  
John Isner             13    176   196   11.2%  
Mikhail Youzhny        14    190   193    1.5%  
Fabio Fognini          15    101    81  -19.3%  
Kei Nishikori          16    172   135  -21.6%  

Player                 Seed  Pre  Post  Change
Tommy Robredo          17     71    61  -13.4%  
Gilles Simon           18    116    95  -18.3%  
Kevin Anderson         19     80   107   33.9%  
Jerzy Janowicz         20     99   154   55.3%  
Philipp Kohlschreiber  21    125   132    6.2%  
Grigor Dimitrov        22    136   122  -10.1%  
Ernests Gulbis         23    125   107  -14.1%  
Andreas Seppi          24     94    49  -47.8%  

Player                 Seed  Pre  Post  Change
Gael Monfils           25    147   101  -31.4%  
Feliciano Lopez        26    100    80  -20.7%  
Benoit Paire           27     94    89   -5.5%  
Vasek Pospisil         28     82    81   -0.9%  
Jeremy Chardy          29    111   126   13.7%  
Dmitry Tursunov        30    101    80  -21.0%  
Fernando Verdasco      31    106   105   -0.8%  
Ivan Dodig             32    104   106    1.8%

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Australian Open Men’s Quarterfinal Projections

The field is down to eight. It still includes the top five seeds and seven of the top ten players in the game, so there’s still plenty of uncertainty. Novak Djokovic showed some chinks in the armor during yesterday’s match against Lleyton Hewitt; Rafael Nadal is never a lock on a hard court; Roger Federer has what may be the toughest quarterfinal draw of the top four; and despite a drubbing last time he played Andy Murray, Kei Nishikori is playing as well as ever.

Oddly enough for such a steady player, this is only David Ferrer‘s second grand slam quarterfinal since 2008 and just his sixth quarterfinal in 36 career slams. In his last slam quarter–Melbourne last year–he beat world number one Nadal. The odds will be even steeper against him this week.

Player                        SF      F      W  
(1)Novak Djokovic          75.4%  49.2%  31.0%  
(5)David Ferrer            24.6%   9.6%   3.4%  
(4)Andy Murray             66.5%  30.9%  16.2%  
(24)Kei Nishikori          33.5%  10.4%   3.8%  

(11)Juan Martin Del Potro  36.0%  14.0%   4.9%  
(3)Roger Federer           64.0%  34.0%  16.4%  
(7)Tomas Berdych           36.6%  15.9%   6.0%  
(2)Rafael Nadal            63.4%  36.1%  18.3%

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The Non-Threatening Dr. Ivo

The perception in tennis is that some players are always dark horses, guys who on any given day might play well above their ranking. Often, these players have “top ten talent” coupled with mental lapses–think Gael Monfils, Marcos Baghdatis, Thomaz Bellucci, Philipp Kohlschreiber. Their rankings sag because of brainless losses (Monfils to Lukasz Kubot at Wimbledon, Baghdatis to somebody every third week), but they occasionally flash their brilliance with a surprising result.

Put it together, and you have a dark horse. There’s a special sort of dark horse upon whom everyone seems to agree: the freakishly tall ace machine. Rob Koenig sounds sensible tweeting about Roger Federer‘s third round match against Ivo Karlovic: “Karlovic v Fed?? Even though Fed has a good record against him, he’s not a guy you wanna see on your side of the draw.” That’s the official line before just about every match Ivo or John Isner plays. The unstoppable serves make them capable of anything.

Or do they? A barrage of bombs starting almost ten feet in the air and bouncing over your head doesn’t sound like a fun day on the court, but does it translate into more losses for top players?

The short answer is no. If anything, Karlovic has shown himself far less likely than the average player to perform above or below his ranking. Last August, I created a metric called ‘Upset Score’ designed to measure how often a player wins against a superior opponent or loses to an inferior one. (Player ability is measured by my ranking system, which predicts match outcomes better than ATP rankings and considers surface.) The metric counts extreme upsets more heavily, so Ivo beating David Ferrer is scored as much more meaningful than defeating, say, Stanislas Wawrinka. Of the 87 players who had 40 or more ATP-level matches in the 20-month span I analyzed, Karlovic had the tenth lowest Upset Score.

This flies directly in the face of conventional wisdom. Looking at the current rankings, we find Ivo just below the likes of Santiago Giraldo and Olivier Rochus–neither one of whom would be viewed as a “tricky” third round opponent. Yet both have Upset Scores in the top half of active players. While there’s no doubt Karlovic was once a very dangerous opponent (as his peak ranking of 14 suggests), he has only one top ten scalp in his last twelve tries, dating back to 2009 Wimbledon. We have to go back to the first half of 2007 to find a stretch in which he was a consistent threat to top players.

Isner isn’t as predictable, but delivers fewer upsets than 60% of the guys on tour. Same story as with Ivo: more often than not, he wins and loses according to past performance. Big John has won two of his last fourteen matches against the top ten, and one of those was an ‘upset’ of Nikolay Davydenko, who by this metric is the least predictable man on the tour.

Massive servers may make for more interesting matches–against any opponent, it’s safe to say that Isner and Karlovic are more likely to deliver a tiebreak or four. But if you’re a top player deciding who you’d like to see coming up in your bracket, you probably don’t care whether you win 6-1 or 7-6(8). Whatever the score, Karlovic is best seen as a steady player on the fringes of the top 50, not some loose cannon who will knock out a top seed one day and lose to a qualifier the next.

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Australian Open Men’s R32 Projections

The top seven seeds are still alive, so in the big picture, not much has changed since I posted pre-tournament odds.   The big names have all seen their chances of winning creep up a little bit,  largely because they’ve gotten past the dangers of the first two rounds.  Some upsets elsewhere in the draw have helped, as well.

The biggest winner on that score is Juan Martin del Potro, whose chances have jumped from 2.6% to 4.2%, as he’s been granted what should be two easy matches before a quarterfinal showdown with Roger Federer.

Player                       R16     QF     SF        W
(1)Novak Djokovic          91.9%  76.3%  59.2%    26.7%
Nicolas Mahut               8.1%   2.6%   0.7%     0.0%
(23)Milos Raonic           79.8%  19.3%   9.0%     1.1%
(WC)Lleyton Hewitt         20.2%   1.8%   0.3%     0.0%
(9)Janko Tipsarevic        54.6%  28.4%   8.9%     1.3%
(17)Richard Gasquet        45.4%  21.7%   5.9%     0.7%
(27)Juan Ignacio Chela     13.9%   2.3%   0.2%     0.0%
(5)David Ferrer            86.1%  47.7%  15.8%     2.7%  

Player                       R16     QF     SF        W
(4)Andy Murray             81.4%  55.6%  34.5%    10.4%
Michael Llodra             18.6%   6.6%   2.0%     0.1%
Mikhail Kukushkin          23.8%   4.8%   1.2%     0.0%
(14)Gael Monfils           76.2%  33.0%  16.3%     2.9%
Julien Benneteau           31.6%   8.8%   2.3%     0.1%
(24)Kei Nishikori          68.4%  29.6%  12.4%     1.8%
Frederico Gil               8.8%   1.5%   0.1%     0.0%
(6)Jo-Wilfried Tsonga      91.2%  60.1%  31.3%     7.3%  

Player                       R16     QF     SF        W
Alejandro Falla            35.9%   9.6%   1.9%     0.1%
Philipp Kohlschreiber      64.1%  24.7%   7.3%     0.5%
Yen-Hsun Lu                21.6%   9.1%   1.8%     0.1%
(11)Juan Martin Del Potro  78.4%  56.5%  26.4%     4.6%
(13)Alexandr Dolgopolov    49.2%  16.3%   8.3%     0.9%
Bernard Tomic              50.8%  17.2%   8.7%     1.0%
Ivo Karlovic               18.4%   7.0%   2.8%     0.2%
(3)Roger Federer           81.6%  59.5%  42.8%    13.2%  

Player                       R16     QF     SF        W
(7)Tomas Berdych           71.3%  44.9%  20.9%     4.4%
(30)Kevin Anderson         28.7%  12.0%   3.3%     0.2%
(21)Stanislas Wawrinka     64.6%  31.0%  12.3%     1.8%
(10)Nicolas Almagro        35.4%  12.2%   3.3%     0.2%
(16)John Isner             55.1%  17.1%   7.7%     0.9%
(18)Feliciano Lopez        44.9%  12.4%   5.0%     0.5%
(q)Lukas Lacko             13.2%   4.4%   1.2%     0.0%
(2)Rafael Nadal            86.8%  66.1%  46.4%    16.1%

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