Novak Djokovic, Roland Garros 2013// [PC: Yann Caradec]

Tennis Note #32

Neutral Points & Point Enders: The Novak Djokovic Edition

Nikita Taparia
May 1, 2016 · 5 min read
Note: Some major outliers were cut off.

Technically, we do not see this data after the match is over. It only appears during a broadcast. It is not on any websites other than Tennis Abstract — specifically, the Match Charting Project. We typically believe that the winner of the match must have a better winners/unforced error ratio. The dotted line represents if the match winner and loser have the same ratio between winners and unforced errors.

Note: Some major outliers were cut off. The y-axis of the second plot should have been 4 to include a few data points in that regime.

Whether you take the glass half full or half empty approach, the minute you include forced errors, the visuals tell a slightly different story. In some sense, one of these may be like IBM’s take on something called the aggressive ratio — a formula that looks at a player’s ability to hit winners and force their opponents to commit an error.

In this case, it is INDUCED forced errors so really they winners of the match for ATP and WTA cause their opponents to make 13 or 11 errors, respectively.

There is no difference if you consider averages between the ATP and WTA. The only two obvious statements I can make: there are more errors than winners and the match winner makes less mistakes (duh). You can see these numbers for different years with Charles Allen’s tool here.

We can start with the neutral points — the points that represent most of the chess game right before you arrive at check [or checkmate].

Neutral points are as important as point enders. Do not disregard them!

For any color blind readers, I made the dots that represent losses bigger in size so you can distinguish! Anything less than 1 means there were more neutral points lost than won so this initial result makes sense.

After briefly exploring the neutral points, I want to reintroduce something called a dominant shot. You may remember this from Tennis Note #8: Rafa in Paris, in which I illustrated the importance of Rafa’s down the line forehand at Roland Garros. I also used this methodology in Tennis Note #22: A Visual History of Serena Williams as well, to illustrate the shot dominance of Serena Williams. The equation is solely based on the player and does not count forced errors at the hand of their opponent. However, total shots on each side includes not just point enders but neutral points. This way, the dominant shot is normalized and easy to compare between the variety of shot selection. Below is a simplistic analysis for Djokovic, not considering shot selection.

Fascinating! When we think Novak Djokovic, we always think backhand but if you do a side by side comparison over the years, his forehand dominance is higher compared to his backhand dominance. It is a bit tough to interpret this temporal plot other than it appears his forehand is more dominant than his backhand, so let’s consider a side by side comparison.

Remember negative means less dominant or aggressive, or more error prone.

This visual tells us much more information. Many of Novak’s losses appear to correlate with a weaker backhand side. For the few losses where he was a bit aggressive, it may not have been enough. At the same time, despite the behavior of the backhand, if Novak’s forehand is dominant, he won most of those matches. Many opponents try to stay away from the strong side and then get burned by a dominant forehand.

How dominant is this forehand?

Only the positive dominant shots are illustrated. Remember, negative denotes more errors. I depicted inside-in and inside out forehand on the backhand side, going down the line or crosscourt, respectively. Inside-out backhand is on the forehand side going crosscourt.

We can use this same formula to examine each type of shot and determine the average dominance during losses and wins from 2014 to present day of charted matches on Tennis Abstract. The crosscourt shots are the most frequent and in the losses, the crosscourt backhand is slightly dominant but not in the wins. Meanwhile, the wins were highly dependent on not only the forehand dominance but the variety in the forehand shot selection. This result was somewhat expected but I did not think it would overshadow the backhand dominance by a landslide. Then again, if you look at the average number of shots for each shot selection, it is very clear why some shots are more dominant than others. There is more to this story and this is only a first step in our discussion of point enders and in play points. I would love to hear your thoughts. If anything, I leave you with this:

If you liked this analysis, please check out Tennis Note #22!

All data is from Tennis Abstract’s amazing database available on GitHub. I talked about it previously. Special thanks to those who took the time to chart the matches. If you enjoy reading these tennis notes, make sure to follow the publication, ‘Recommend’ and share! Check us out on Facebook! Made a cool observation? Interested in certain topics and writing? Are you a tennis photographer? Comment, add notes, and check out the submission guideline. Let me know which visuals are good and which are not so great. Cheers!

The Tennis Notebook

A ‘romantic’ tale between tennis enthusiasts and an elegant sport. Includes light commentary and analysis of the game.

Nikita Taparia

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Engineer. Scientist. Data Nerd. Cookie/Coffee Addict. Educator. Tennis/WoSo. Photographer. Musician. Artist. Whiteboards. @ByTheMinTennis Commentator. Writer.

The Tennis Notebook

A ‘romantic’ tale between tennis enthusiasts and an elegant sport. Includes light commentary and analysis of the game.