Italian translation at settesei.it
Serving for the set is hard … or so they say. Like other familiar tennis conceits, this one is ripe for confirmation bias. Every time we see a player struggle to serve out a set, we’re tempted to comment on the particular challenge he faces. If he doesn’t struggle, we ignore it or, even worse, remark on how he achieved such an unusual feat.
My findings–based on point-by-point data from tens of thousands of matches from the last few seasons–follow a familiar refrain: If there’s an effect, it’s very minor. For many players, and for some substantial subsets of matches, breaks of serve appear to be less likely at these purportedly high-pressure service games of 5-4, 5-3 and the like.
In ATP tour-level matches, holds are almost exactly as common when serving for the set as at other stages of the match. For each match in the dataset, I found each player’s hold percentage for the match. If serving for the set were more difficult than serving in other situations, we would find that those “average” hold percentages would be higher than players’ success rates when serving for the set.
That isn’t the case. Considering over 20,000 “serving-for-the-set” games, players held serve only 0.7% less often than expected–a difference that shows up only once every 143 attempts. The result is the same when we limit the sample to “close” situations, where the server has a one-break advantage.
Only a few players have demonstrated any notable success or lack thereof. Andy Murray holds about 6% more often when serving for the set than his average rate, making him one of only four players (in my pool of 99 players with 1,000 or more service games) to outperform his own average by more than 5%.
On the WTA tour, serving for the set appears to be a bit more difficult. On average, players successfully serve out a set 3.4% less often than their average success rate, a difference that would show up about once every 30 attempts. Seven of the 85 players with 1,000 service games in the dataset were at least 10% less successful in serving-for-the-set situations than their own standard.
Maria Sharapova stands out at the other end of the spectrum, holding serve 3% more often than her average when serving for the set, and 7% more frequently than average when serving for the set with a single-break advantage. She’s one of 30 players for whom I was able to analyze at least 100 single-break opportunities, and the only one of them to exceed expectations by more than 5%.
Given the size of the sample–nearly 20,000 serving-for-the-set attempts, with almost 12,000 of them single-break opportunities–it seems likely that this is a real effect, however small. Strangely, though, the overall finding is different at the lower levels of the women’s game.
For women’s ITF main draw matches, I was able to look at another 30,000 serving-for-the-set attempts, and in these, players were 2.4% more successful than their own average in the match. In close sets, where the server held a one-break edge, the server’s advantage was even greater: 3.5% better than in other games.
If anything, I would have expected players at lower levels to exhibit greater effects in line with the conventional wisdom. If it’s difficult to serve in high-pressure situations, it would make sense if lower-ranked players (who, presumably, have less experience with and/or are less adept in these situations) were not as effective. Yet the opposite appears to be true.
Lower-level averages from the men’s tour don’t shed much light, either. In main draw matches at Challengers, players hold 1.4% less often when serving for the set, and 1.8% less often with a single-break advantage. In futures main draws, they are exactly as successful when serving for the set as they are the rest of the time, regardless of their lead. In all of the samples, there are only a handful of players whose record is 10% better or worse when serving for the set, and a small percentage who over- or underperform by even 5%.
The more specific situations I analyze, the more the evidence piles up that games and points are, for the most part, independent–that is, players are roughly as effective at one score as they are at any other, and it doesn’t matter a great deal what sequence of points or games got them there. There are still plenty of situations that haven’t yet been analyzed, but if the ones that we talk about the most don’t exhibit the strong effects that we think they do, that casts quite a bit of doubt on the likelihood that we’ll find notable effects elsewhere.
If there is any truth to claims like those about the difficulty of serving for the set, perhaps it is the case that the pressure affects both players equally. After all, if a server needs to hold at 5-4, it is equally important for the returner to seize the final break opportunity. Maybe the level of both players drops, something we might be able to determine by analyzing how these points are played.
For now, though, we can conclude that players–regardless of gender or level–serve out the set about as often as they successfully hold at 1-2, or 3-3, or any other particular score.
Can you tell from the charting project data if the first serve percentage drop on “serving out the set” situations?
you could, though the sample size is almost two orders of magnitude smaller.
Jeff hi,
Big fan here, of you and your work. Thank you for this wonderful blog and data. 🙂
Can you explain how you would find whether the player is serving for the set from the data?
I have been trying to do a similar analysis from your data on github (thank you again!) , but could not figure out a way to identify who serves first on a match. Consequently, one would be able to figure out who serves out to end the set and alike.
Regards,
player who serves first is one of the columns for each match. columns explained:
https://github.com/JeffSackmann/tennis_pointbypoint
I had meant the huge atp/challenger match results data, the ones with year breakdown 🙂
This one: https://github.com/JeffSackmann/tennis_atp
it’s not always possible to tell. there are columns for number of service games for each player, so if one is greater than the other, that’s your first server. otherwise we don’t know.
Could you clarify the methodology? Do you take the hold percentage in all service games in your sample, and compare this to the hold percentage in every game in which a player is serving for a set in the sample? If so, it seems like this isn’t quite the right test of the hypothesis that the probability of winning a service game *against a given opponent* is independent of where that game lands in a set.
Serving for a set means that you’ve broken your opponent’s serve, so in this subset of service games, you’d expect the server on average to be better than their opponent. Whereas a randomly chosen game, you’d expect the server on average to have the same ability (or ranking) as their opponent. So if the probability of winning a service game *against a given opponent* is independent of where that game lands in the set, you’d expect the hold percentage in all games in the sample to be lower than the hold percentage in all games where the server is serving for the set in the sample.
It seems like a better test (and maybe this is what you did) would be to compare the hold percentage in games in which a player serves for the set with the hold percentage in games where players aren’t serving for the set, but do end up serving for the set.
p.s. just discovered this site and the data, and it looks great! Thanks!
each ‘serving for the set’ game is compared to the hold percentage for that player in that particular match.
Wow , this is really interesting, as with all sports we assume “pressure situations” are more challenging, but often times that just isn’t the case.