The longevity debate we’ve been having touches on the issue of peak level of play, but only indirectly. The reasons we give for Federer’s decline do imply something about his peak level of play: if even a GOAT level player has genuinely good reasons, in today’s game, why he would fall behind his main rivals at around the age of 30, then that supports the argument that his peak level was genuinely GOAT level. If, on the other hand, there is no good reason why a 30-year-old should be falling behind his rivals in today’s game, then that lends weight to the argument that Federer is losing now because he is encountering tough rivals for the first time and his peak level was never GOAT level to begin with.
But all that was an indirect way to talk about peak level. Match stats can directly illustrate peak level of play, and I want to list those that I have gathered for Federer, Nadal and Djokovic.
The stats still have to be interpreted, but this, at least, is a direct measurement of level of play.
The most common stats used today to illustrate level of play are winners and unforced errors. Subtracting the errors from the winners, we get winner/error differentials, which can be useful. But that method has one large drawback, in that it only counts the unforced errors. The forced errors – which are almost never reported – are nowhere to be seen, and often they tell a different story.
One method that does measure forced errors is the Aggressive Margin. You can read about it here: http://www.itftennis.com/shared/medialibrary/pdf/original/IO_24691_original.PDF.
Basically, in tennis you want to be as aggressive as possible while making as few errors as possible. That's what the Aggressive Margin measures. It counts the points that you win aggressively -- either by striking clean winners or by forcing your opponent into errors -- and compares that with how many points you lost by making unforced errors.
To put it most simply, if you win 25% of the all the points played in a match through aggressive plays – either by striking clean winners or by forcing your opponent into errors – and you lose 10% of all the points played in the match through unforced errors of your own, then your Aggressive Margin is 15%.
To have a high Aggressive Margin does not mean that you have to be what we normally think of as "an aggressive player." A guy who makes relatively few winners and few errors, like Nadal, can have just as high an Aggressive Margin as a guy who makes a ton of winners and errors. What matters is whether you can win points but not pay too high a cost in errors. Whoever does better at that balancing act has the higher Aggressive Margin and is almost always the winner of the match.
Over the years I’ve collected official stats for many matches, from which I’ve calculated Aggressive Margins. I have stats for all of the GS finals played by Federer, Nadal, Djokovic and Murray, against each other or against any player. I have stats for dozens more of their matches, and stats for many other players as well.
NOTE: the highest Aggressive Margins tend to occur on grass. The slower the surface, the more difficult it is to hit winners or to force errors from your opponents.
The highest Aggressive Margin I’ve ever calculated belongs to John McEnroe in the 1984 Wimbledon final: 52.8%. That does not automatically mean that his performance was the best of all time. Stats can’t be used that literally; and it’s a matter of judgment whether 52.8% against an aging Jimmy Connors is as impressive as some other performances we could name.
Any additional stats, comments, questions, arguments and corrections are most welcome.
Lists for Federer and Nadal
Lists for Djokovic, Murray, Roddick, Hewitt, Safin, Del Potro, Tsonga
But all that was an indirect way to talk about peak level. Match stats can directly illustrate peak level of play, and I want to list those that I have gathered for Federer, Nadal and Djokovic.
The stats still have to be interpreted, but this, at least, is a direct measurement of level of play.
The most common stats used today to illustrate level of play are winners and unforced errors. Subtracting the errors from the winners, we get winner/error differentials, which can be useful. But that method has one large drawback, in that it only counts the unforced errors. The forced errors – which are almost never reported – are nowhere to be seen, and often they tell a different story.
One method that does measure forced errors is the Aggressive Margin. You can read about it here: http://www.itftennis.com/shared/medialibrary/pdf/original/IO_24691_original.PDF.
Basically, in tennis you want to be as aggressive as possible while making as few errors as possible. That's what the Aggressive Margin measures. It counts the points that you win aggressively -- either by striking clean winners or by forcing your opponent into errors -- and compares that with how many points you lost by making unforced errors.
To put it most simply, if you win 25% of the all the points played in a match through aggressive plays – either by striking clean winners or by forcing your opponent into errors – and you lose 10% of all the points played in the match through unforced errors of your own, then your Aggressive Margin is 15%.
To have a high Aggressive Margin does not mean that you have to be what we normally think of as "an aggressive player." A guy who makes relatively few winners and few errors, like Nadal, can have just as high an Aggressive Margin as a guy who makes a ton of winners and errors. What matters is whether you can win points but not pay too high a cost in errors. Whoever does better at that balancing act has the higher Aggressive Margin and is almost always the winner of the match.
Over the years I’ve collected official stats for many matches, from which I’ve calculated Aggressive Margins. I have stats for all of the GS finals played by Federer, Nadal, Djokovic and Murray, against each other or against any player. I have stats for dozens more of their matches, and stats for many other players as well.
NOTE: the highest Aggressive Margins tend to occur on grass. The slower the surface, the more difficult it is to hit winners or to force errors from your opponents.
The highest Aggressive Margin I’ve ever calculated belongs to John McEnroe in the 1984 Wimbledon final: 52.8%. That does not automatically mean that his performance was the best of all time. Stats can’t be used that literally; and it’s a matter of judgment whether 52.8% against an aging Jimmy Connors is as impressive as some other performances we could name.
Any additional stats, comments, questions, arguments and corrections are most welcome.
Lists for Federer and Nadal
Lists for Djokovic, Murray, Roddick, Hewitt, Safin, Del Potro, Tsonga
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