Men, Women, and Unforced Errors

Italian translation at settesei.it

If you’ve ever suffered through a debate about the relative merits of men’s and women’s tennis, you’ve probably heard the assertion that women’s tennis is sloppier–“riddled with unforced errors,” perhaps.  Maybe you’ve even made that claim yourself, which is understandable, given how often some version of it crops up, unchallenged, in tennis commentary.

But is it really true?  Do WTA matches feature so many more unforced errors than ATP matches? Unforced errors were counted at most slam matches last year, so we can find out.

Let’s start with the most recent results.  In men’s matches at the 2013 US Open, 33.2% of points ended in an unforced error.  Play may have tightened up just a bit in the final week: In the round of 16 and later, 32.9% of points ended in UFEs.

Women’s matches did, in fact, feature a higher rate of unforced errors. Considering the entire tournament, 39.7% of points ended that way, while in the fourth round and later, the rate dropped to 36.7%.

So yes, there are more unforced errors in the women’s game.  There are similar gaps between ATP and WTA error rates at Wimbledon and the Australian Open, and while the difference on the French Open clay is smaller, it is still present.

Eyeballing errors

However, these aren’t massive differences.  Using the US Open numbers, we can calculate that WTA points ended in UFEs about 20% more often than ATP points.  In the last four rounds of the tournament, when more people are watching closely and drawing conclusions, that difference drops to 11.7%.

Without a scorebook in hand, that gap may well be too small to spot.  In a typical set of, say, 60 points, the average ATP pairing averaged 20 UFEs, against a typical WTA matchup’s  24.  That’s one extra unforced error every other game–if that.  Looking at the four final rounds, the difference drops to 20 UFEs in a men’s match against 22 in a women’s match.  Two extra errors a set.

The divide is real, but it hardly seems substantial enough to represent a major difference in the quality of play or in the viewing experience.

Here are the numbers for the entire field at all four 2013 slams, followed by the rates in the final 16:

Slam             ATP UFE%  WTA UFE%  WTA/ATP  
Australian Open  36.2%        44.4%     1.22  
French Open      33.6%        37.0%     1.10  
Wimbledon        19.1%        24.6%     1.29  
US Open          33.2%        39.7%     1.20

R16 and later:                                           
Slam             ATP UFE%  WTA UFE%  WTA/ATP  
Australian Open  36.4%        41.1%     1.13  
French Open      33.9%        34.9%     1.03  
Wimbledon        20.5%        24.4%     1.19  
US Open          32.9%        36.8%     1.12

Don’t read too much into the contrasts between one slam and another–what’s important here is how the same set of scorers, in the same conditions, are judging men’s and women’s matches.  Wimbledon, especially, is known for its, shall we say, unique approach to counting unforced errors.

Instead, a power gap

The French Open rates are by far the closest of those at the four slams.  This shouldn’t come as a surprise.  On a slower surface, ATPers earn fewer free points than usual on serve, finding themselves more frequently in rallies.  Take away those one- or two-shot rallies that the men’s game is known for, and the UFE disparity starts to shrink.

While we can’t account for all service winners and forced error returns, we can take aces out of the equation.  So far, we’ve only see unforced errors as a percentage of all points.  Take UFEs as a percentage of all non-ace points, and the difference between men’s and women’s error rates decreases.

In other words, now we’re starting to look at what happens when the serve is returnable:

Slam             ATP UFE%  WTA UFE%  WTA/ATP  
Australian Open  39.6%        46.2%     1.17  
French Open      35.6%        38.3%     1.08  
Wimbledon        21.2%        25.9%     1.22  
US Open          36.1%        41.3%     1.14  

R16 and later:                                
Slam             ATP UFE%  WTA UFE%  WTA/ATP  
Australian Open  39.6%        42.8%     1.08  
French Open      35.3%        36.0%     1.02  
Wimbledon        22.7%        25.6%     1.13  
US Open          34.9%        38.3%     1.10

In most of these cases, we’re down to a couple of points per set.  If we were able to sort out service winners and perhaps forced error returns, we would almost surely see even more minor differences.

There’s no doubt that men hit harder serves and are, on average, more likely to win a point without having to hit a second ball.  But if we’re comparing the characteristics of women’s tennis, it doesn’t seem right to give the men credit for not hitting as many unforced errors when some of the already modest difference is due to the dominance of the serve.

Quibbles

This entire analysis depends on the unforced error stat, which I don’t much care for.  It is hugely dependent on the scorer, and there’s no widespread agreement in the sport on what exactly it means.

However, if we want to challenge a widely-held belief about unforced errors, there’s not really any way around using unforced errors, is there?

The best we can do to eliminate scorer’s biases is to compare only within single events.  The same person isn’t counting unforced errors at every US Open match, but each scorer probably works both men’s and women’s matches.  At a given venue, every scorer might even go through the same training program.

Even with that consideration, there is the strong possibility that scorers make adjustments–consciously or unconsciously–depending on the gender of players on court.  If unforced errors are shots that a player should have made but didn’t, a lot hinges on your interpretation of the word “should.”  It may be that some shots would be called unforced errors in a men’s match, but forced errors in a women’s match.  To the extent that’s the case, it’s awfully difficult to compare the genders using a stat that itself differs depending on gender.

On the other hand, scorers are presumably tennis fans, and they’ve heard the same conventional wisdom everyone else has.  If you believe that women hit more unforced errors than men do, perhaps you call borderline women’s shots unforced and borderline men’s shots forced.  In that case, scorers might be unwittingly amplifying the gender difference, not reducing it.

Given the difficulties of collecting data from hundreds of matches on different continents spread across many months, I doubt any non-automated method of counting unforced errors would address all of these issues.  For now, we have to take the official unforced error counts as the best available representation of reality and draw conclusions accordingly.

Whatever the limitations of the data, and whatever the other differences between the genders on a tennis court, unforced error counts are not nearly the distinguishing factor that they’ve been made out to be.

7 thoughts on “Men, Women, and Unforced Errors”

  1. Terrific reporting & analysis. I also like the Perrotta/Bialik article you link to at the WSJ. I’m getting the feeling that you & Perrotta and Bialik are a sort of community in that you share information? At any rate terrific job. I wish we could see some of this informing commentary more – even match commentary.

    Meanwhile if I can go on somewhat of a tangent – my own thought on why the WTA seems to get so much criticism is purely subjective (i.e. I take my own gut response & generalize wildly). I hate it that the WTA permits on-court coaching – it creates the impression that women are weak and need older men to “inspire” or scold them as it may be. I also wish the league would grow the gonads to actually put a lid on the screeching rather than merely talk about it – although frankly there are so many men who now grunt to excess that this is no longer an ATP vs WTA issue.

    Like I say, I have only a gut reaction – but my gut reaction is still that there aren’t that many WTA players I will go out of my way to watch, outside of Serena and some of the promising youngsters (loved Duvall’s match against Stosur). I should like Age for her creativity; but I don’t. I can’t stand Sharapova for her lack of imagination and baseline rut and her screeching. I like Azarenka’s game but having to turn down the sound is growing old. On and on . . .

    1. Thanks. Yep, I have the pleasure of knowing both Carl and Tom.

      The more I watch WTA matches (which still isn’t much, but more than it used to be), the more I think that it’s easy to find stuff to complain about with any player of either gender. If you prefer men’s tennis–maybe b/c you’ve always watched it–there’s plenty with Vika or Maria or anybody else to annoy you. If you prefer women’s tennis, a Djokovic-Nadal match can be just as objectionable (only longer).

      A few worth watching, IMO: Kerber, Lisicki, Bouchard, Mattek-Sands, Jankovic, Woz (though I know she bores many), Halep, Kirilenko, and Keys.

  2. I look forward to a stat you’ll be able to generate as soon as you get IBM to supply you with the kind of shot-by-shot analysis you’re getting with your spreadsheet – pattern changes per game, set, and match. How many plays did the winning and losing players repeat? At what point did the patterns change? What effect did the changes have?

    I’m wondering if I bore of women’s tennis because their power seems to exceed their mobility. A man seems to need to open the court wider than a woman to score a clean winner. WTA matches seem a lot like the old serving duels. As long as a woman can hit two corners hard, she wins the point. Wozniaki plays for time by softballing and Aga plays against rhythm, but someone like Lisicki looks a lot like Goran Ivanisevic at the service notch. When she’s hitting those corners, even Serena can’t catch up with her shots, but she can’t keep it up long enough.

    Taken together, I think the women’s game, especially among the seeds, ends up conforming strongly to patterns – even when the patterns are failing. The men seem more able to cover the entire 27×39 feet, so you see more pattern creativity. Again, just like in the old serve dueling days, if the serve brought you this far you had very few plan B’s once the other guy dialed in his return. You served smarter and hoped the other guy’s nerve would crack. As long as Azarenka can hit hard enough to keep Serena from tagging corners at will, she’s in the match, but if Serena’s nerve holds she’s going to start hitting parts of the court too far away for Azarenka to reach. So the pattern doesn’t change. Azarenka wins by hitting hard enough to move Serena too far to hit dangerously and Serena wins by hitting hard enough Azarenka can’t get to the ball. On a smaller court they’d need to be more creative, but with 27 feet to play with this lone pattern works too well to change.

    Some day your numbers will prove me wrong. 🙂

    1. Yeah, I do hope to have enough data to test the pattern-predictability stuff. We may get there.

      There are definitely some WTA players who are very predictable (you can impress your friends by predicting the direction of Petkovic’s groundstrokes with 95% accuracy), but I think the creativity/unpredictability of ATP players is overstated. The top men may have more flexible weapons with which they can end points, but I think your typical rally in the Djokovic/Murray/Nadal axis falls into a few patterns. And when one of those guys plays a baseliner with less skill, the patterns get even more repetitious.

      I like your comparison of 2010s WTA to 1990s-ish ATP. Not sure that’s a bad thing, especially for the many fans who want to see the men play on faster surfaces.

      1. I’m wondering if an analysis such as this, comparing errors, accounts for fatigue; i.e. taking into account either a duration of a match, or number of points, or number of strokes. You’d expect there to be many more UFEs in the Isner vs Mahut match than in the Graf vs Zvereva (1988 French Open finals). So, you’d expect, by extension, a game that is longer (hence more fatigue), that has lower number of UFEs to be of a higher caliber.

  3. of more interest is the shape of the distribution across the genders. It would not surprise me if the higher mean in the women’s game was down to a longer tail to the right of the mean, i.e. there are more horrific performances each slam in the women’s game: such extreme instances would certainly contribute towards a cognitive bias when forming a general opinion.

    the truth is that aggressive players in the women’s game play to a much lower percentage than the men: they have to. the difference in movement ability between the sexes is much smaller than the difference in shot power, so hitting through someone requires a woman to take far more risk, particularly those who have to hit flat.

    it’s no big deal, but it’s unacceptably rarely mentioned by the commentators.

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