Category Archives: Official stats

Men, Women, and Unforced Errors

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.


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.


Filed under Gender differences, Official stats