Sabr Metrics: The Case For the Hyper-Aggressive Return

Italian translation at settesei.it

Roger Federer has made waves the last few weeks by occasionally moving way up the court to return second serves. While the old-school tactic was nearly extinct in today’s game of baseline attrition, it seems to be working for Fed.

At least in one sense, it’s too early to say whether the kamikaze return is an effective tactic. Federer has used it sparingly for only a handful of matches, and in that tiny sample, he’s missed plenty of returns. But in the view of many pundits, the hyper-aggressive return gets in his opponents’ heads, making the tactic more valuable than simply changing the result of a few points. Presumably Roger agrees, since he keeps using it.

I agree that the tactic is a good one, though for a different reason. By taking greater risks, Fed is generating more unpredictability, or streakiness, on his opponents’ service games, which is valuable even if he doesn’t win any more return points.

Watching and waiting

To win a match, a player usually needs to break serve, and in the contemporary men’s game, that’s not an easy thing to do. On average, servers win about 64% of points and hold about 80% of service games. On hard courts, the equivalent numbers are even higher. Against a good server–let alone John Isner, Fed’s opponent tonight–they are higher still.

Returners who stand well behind the baseline and try only to put the ball back in play are basically crossing their fingers and hoping for the best. Maybe their opponent will miss several first serves, or the server will make a couple of errors against those weak returns. It can work, and for a brilliant returner such as Novak Djokovic, hitting moderately aggressive returns and winning some of the ensuing rallies is usually good enough for several breaks per match.

For most players, however, breaks of serve rely more on the server’s occasional lapses. To put it in numerical terms: A passive returner is playing the lottery in every return game–a lottery with only a 10% to 20% chance of winning.

Generating the coin flip

The best way to earn more breaks of serve, of course, is to win more return points. But unless you’re spending the offseason at Djokovic’s training camp, that’s unlikely.

The alternative is to change the rules of the lottery. Instead of accepting a steady rate of 35% of return points, a hyper-aggressive strategy is more likely to make the point-by-point results more streaky, even if the overall rate doesn’t change.

To see why this is effective, we need to oversimplify a bit. A player who wins 35% of return points will, on average, break in 17% of his return games. If we introduce a slight variation in the rate of return points won, we see a slight improvement in break rate, as well. If that same player wins 30% of return points in half of his games and 40% of return points in the other half, he’ll break serve 18% of the time.

That one percent improvement is barely noticeable. It probably represents what’s already going on in most matches, often because servers are a bit streaky already. The more volatility we introduce, though, the more the odds tilt toward the returner.

Double the variation and say that the returner wins 25% of return points half the time and 45% the other half. Now he’ll break serve in 21% of games, or one extra break per 25 return games. Still not overwhelming, but that’s one extra break in a five-setter.

The real magic happens when we expand the variation to an even split between 20% of return points and 50% of return points. In that scenario–when, remember, our returner is still winning 35% of points–the break rate improves to 26%, almost one more break per ten return games. On average, that’s an extra break per best-of-three match, and closer to two extra breaks in a typical best-of-five match.

Back to reality

A hyper-aggressive return game is going to result in more return errors as well as more return winners. That’s true regardless of return position: Mikhail Kukushkin managed to break Marin Cilic four times on Friday by going for return winners, even if he stayed in the general area of the baseline.

So a new return tactic is unlikely to make a player much better in general. And of course, it’s unlikely to generate anything like the neat, theoretical examples shown above, when one game is better and one game is worse.

However, I suspect that higher-risk shots are more likely to be streaky, which would result in something like those neat examples. And if the pundits are right, that Fed’s kamikaze return unnerves his opponents, that ought to make his return games even streakier still, as his opponents deal with a new challenge mid-match.

Whenever there’s an opportunity to change the nature of the game and make it less predictable, the underdog should take it. Odd as it is to think of Federer as the underdog, he–like everyone else on the men’s tour–is in fact fighting an uphill battle in every return game. Hyper-aggressive tactics are a small step toward leveling the field.

2 thoughts on “Sabr Metrics: The Case For the Hyper-Aggressive Return”

  1. Excellent blog, Jeff. It is quite a trenchant analysis, and from a tennis obsessed (and number obsessed and pattern obsessed) person’s perspective, I would complete concur with you. From a pragmatic empirical point of view, it is also quite obvious that this tactic adds great unpredictability, forcing server to think differently, introducing double faults in some cases.
    I have exams these days, but I would like to contribute with the algorithmic aspect of your work on this blog as soon as I have some more free time. Would that be possible?

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