The other day, Roger Federer mentioned in a press conference that he’s “never been a big stat guy.” And why would he be? Television commentators and the reporters asking him post-match questions tend to harp on the same big-picture numbers, like break points converted and 2nd-serve points won.
In other words, statistics that look better when you’re winning points. How’s that for cutting edge insight: You get better results when you win more points. If I were in Fed’s position, I wouldn’t be a “big stat guy” either.
To the extent statistics have the potential to tell us about a particular player’s performance, we need to look at numbers that each player can control as much as possible. Ace counts–though they are affected by returners to a limited extent–are an example of one of the few commonly-tracked stats that directly reflect an aspect of a player’s performance. You can have a big serving day with not too many aces and a mediocre serving day with more, but for the most part, lots of aces means you’re serving well. Lots of double faults means you’re not.
By contrast, think about points won on second serve, a favorite among the commentariat. That statistic may weakly track second serve quality, but it also factors the returner’s second serve returns, as well as both player’s performance in rallies that begin close to an even keel. It provides fodder for discussion, but it certainly doesn’t offer anything actionable for a player, or an explanation of exactly what either player did well in the match.
Aces and double faults are a decent proxy for performance on serve. (It would be nice to have unreturnables as well, since they have more in common with aces than they do with serves that are returned, however poorly.)
But what about every other shot? What about specific strategies?
An obvious example of a base-level stat we should be counting is service return depth. Yes, it’s affected by how well the opponent serves, but it refers to a single shot type, and one upon which the outcome of a match can hinge. It can be clearly defined, and it’s actionable. Fail to get a reasonable percentage of service returns past the service line, and a good player will beat you. Put a majority of service returns in the backmost quarter of the court, and you’re neutralizing much of the server’s advantage.
Here are more atomic statistics with the same type of potential:
- Percentage of service returns chipped or sliced.
- Percentage of backhands chipped or sliced.
- Serves (and other errors) into the net, as opposed to other types of errors.
- Variety of direction on each shot, e.g. backhands down the line compared to backhands crosscourt and down the middle.
- Net approaches
- Drop shot success rate (off of each wing).
Two commonly-counted statistics, unforced errors and winners, have many characteristics in common with these atomic stats, but are insufficiently specific. Sure, knowing a player’s winner/ufe rate for a match is some indication of how well he or she played, but what’s the takeaway? Federer needs to be less sloppy? He needs to hit more winners? Once again, it’s easy to see why players aren’t clamoring to hear these numbers. No baseball pitcher benefits from learning he should give up fewer runs, or a hockey goaltender that he needs to allow fewer goals.
Glimmers of hope
With full access to Hawkeye data, this sort of analysis (and much, much more) is within reach. Even if Hawkeye material remains mostly impenetrable, the recent announcement from SAP and the WTA holds out hope for more granular tennis data.
In the meantime, we’ll have to count this stuff ourselves.