The people of tennis are increasingly talking about “stroke tolerance”. What does it mean?
There is no standard definition. Google Summary settles on this: “The ability to return and refund as a player wants a given ball.” Other definitions are more focusing to prevent more empty errors: How long can a player stay at the rally without mistaking?
I think this is as defense, in a very broad sense. Usually when we talk about defense skills, it is a large service or winner, a network that restores the ends ending the point. In tennis, each time each stroke has an attack component. That is, almost every stroke tests the ability to defend the defense or ability or other player’s tolerance. Can you manage this and save the point live in a wide range of a novak Djokovic backhed, a heavy janny sinner in the legs.
Another way of conceptualizing shooting tolerance is to imagine a winning stat. When the sinner struck this hard siege, the chances of winning the point against an average opponent, say 70%. A player with high strokes tolerance will somehow earn more than 30% of these points. A player with low strokes tolerance, returns (or hits weak answers) and he will earn less than 30% of these points.
We do not have a probability status that knows everything, so we cannot measure the stuck tolerance directly. Because the concept is fuzzy, I do not imagine that we will be fully satisfied to measure multiplication tolerance. But it’s worth trying and this will help Rotterdam Champ Carlos explain how Alcaraz works.
Long rallies
Start on the grounds. Players with high strokes tolerance have to win longer rallies?
I took a line in six innings, including rallies, where the sixth shot was a bug. I don’t want to make everything with stirring the surfaces, so we stick to hard courts today. According to Match Charting project data, men who have won the most “long” rallies of these “long” rallies since the beginning of 2024:
Player 6+ W% Jannik Sinner 56.1% Carlos Alcaraz 55.6% Alex de Minaur 55.1% Grigor Dimitrov 55.1% Joao Fonseca 55.0% Learner Tien 54.5% Andrey Rublev 54.2% Novak Djokovic 53.7% Daniil Medvedev 53.7% Alejandro Tabilo 53.2%
The top of the list is as expected: sinner and alcaraz may be superior to most competitors and has the ability to end the point. Fonseca and Tien will probably not continue these numbers because others did not play the same level of competition as. There is no position of the tabile and many graphic matches. Alexander Zverev is the next place in the list if you want to introduce the tabilet in place.
Complex issues are how these points are end. The goal is not to protect the longest rallies possible. At some point, the tolerant capacity hit and allows you to take calculated risk. Some players are especially strong on this long rallies, especially in the side of the clean-strokes of things to avoid unloaded errors:
Player 6+ Rally UFE% Casper Ruud 15.8% Bu Yunchaokete 17.9% Lorenzo Musetti 18.5% Daniil Medvedev 19.5% Alex Michelsen 19.5% Frances Tiafoe 20.0% Karen Khachanov 20.2% Alejandro Tabilo 20.4% Learner Tien 20.7% Novak Djokovic 21.0%
There are a number of overlaps between the two lists, but not much. The wrong rate of the sinner is better than average, 22.3%, while Alcaraz is worse, 24.1%. In the first round against Botik van de Zandschulp in Rotterdam, Alcaraz did not expanded incidents 40% of points reaching the sixth shot. Still earned half of the long points.
There is a connection between the winning rate and error ratio at long points – there are so many things that mistakes are lost. However, the wrong ratio is less than 30% of the variability in a long rally percentage. Alcaraz breaks a lot of mistakes for one, but still wins the majority of points:
Alcaraz’s mistakes usually expose the weakness of stroke tolerance. Reflects a gambling. (Although the sinner is similar, although its zones can be more harmful at risk. The insulating stroke requires a different approach to tolerance.
To accept mistakes
Bride score for Shots. Since the beginning of the last season, I resumed for hard judicial matches, I collected the initial strokes of each player from the fourth shot of each rally. The shooting is useful for serving tolerance, returns and plus, but these shootings are more than a player’s management. Since most points are short, it will come back and the plus-eleven ones dominate the information. We must cancel them to get an image example that reflects what we think.
(The word “Main” is doing a ton of work here. Talentance is not about the performance of volleyls or smashes at all or the execution of passing shots.
As in long rallies, we can start with strokes tolerants, every stars, the best in preventing errors:
Player UFE/Shot % Learner Tien 7.4% Alexander Shevchenko 7.9% Lorenzo Musetti 8.2% Alejandro Tabilo 8.2% Tommy Paul 8.7% Frances Tiafoe 8.9% Carlos Alcaraz 9.2% Jannik Sinner 9.2% Matteo Arnaldi 9.2% Casper Ruud 9.7%
Musetti, Paul and Ruud are probably the names you expect to see here. Alcaraz and Sinner are more walking. When they look at long rallies, but they do not differ as mistakes when they are tagged.
In general, there is a predictable trade. The players who hit more winners (and forcing more errors) have made more empty mistakes. However, the connection between two numbers is not the same for everyone. Here are the same UFE-on-ten list of winning rates:
Player UFE% W+FE% Learner Tien 7.4% 7.3% Alexander Shevchenko 7.9% 9.1% Lorenzo Musetti 8.2% 9.1% Alejandro Tabilo 8.2% 10.6% Tommy Paul 8.7% 11.1% Frances Tiafoe 8.9% 8.0% Carlos Alcaraz 9.2% 10.1% Jannik Sinner 9.2% 14.1% Matteo Arnaldi 9.2% 8.3% Casper Ruud 9.7% 11.1%
The holy sinner! Typical ATP regularly wins the UFES in these stages of the rally. Tien is on the wrong side of the scale of TieFoe and Arnali. Tabilo is still liked with a limited (and biased) example. And the sinner … well, you need to go more than 15 players from the list before finding anyone who cracks many winners, and Karen Xachanov coughs more than quarter mistakes to perform FEAT.
Here’s the full scatterplot:
This is a tough attitude than previously shown. The player-player change in Winner explains the half of the difference in the error rate. Again, some players prevent ordinary trade. The graph is closer to the upper left corner, the aggression is more risky.
Aggression managed (for
Thinking makes the strange feeling to measure hitting tolerance winnerBut that’s exactly what we will do.
Simplify, think we put each stroke into one of two categories: aggressive or defensive. The aggressive shots are not really about hitting tolerance. Aggression is a stroke that only has the player knows more or less that the player can do, unless just last a ditch. He strikes hard, targeting the line and finishes the point in one way or another.
Shooting tolerance is not about this risk of melons. We are interested in how durable in each of a player.
We will carry some assumptions together to reach. You probably don’t agree with some and almost do not agree with some results. But in any case a minute together with me.
Say that the winners (and compulsory errors) are “value” half many of the discharge errors. The usual ratio is about 1: 1 but does not count forced errors, and It counts the “bad” mistakes from low-hitting tolerance. Thus, the ratio of 2: 1 means that if a player will hit two winners, the value of the work is an error in an interval. For Alcaraz, the 10.1% wins rate, playing flawlessly in non-aggressive situations, will still have a 5% error rate.
From there, we get acquainted with the “non aggressive” error ratio. The total error rate of Alcaraz is 9.2% and we write 5% as the value of the aggression that leaves us with 4.2%. We will share it in the number of non-aggressive shots, ie 100% of its strokes, minus the winners of minus, aged 5% of aggressive mistakes. Thus: 4.2% (100% – 10.1% – 5% =) are divided into 84.9%. Touch the calculator and get an error ratio of non-aggressive error 4.9%.
From a more positive point of view, it is “stuck tolerance” 95.1%. That is, when a stroke has a reasonable chance (his opponent did not win or created a compulsory mistake), and he does not go big, he is 95.1% of time. The tour is 93.7% between Nizami. The best ten, which excludes names like Tien and Tabilo, said I mentioned the above:
Player ShotTol Jannik Sinner 97.3% Tommy Paul 96.2% Lorenzo Musetti 95.7% Andrey Rublev 95.4% Carlos Alcaraz 95.1% Grigor Dimitrov 95.0% Casper Ruud 95.0% Daniil Medvedev 94.9% Frances Tiafoe 94.5% Alex de Minaur 94.4%
Thus, do you agree that Alex de Minavan did not have Rublev, Dimitrov or Tiaphoe’s shot tolerance? Can you get Djokovic out of the top ten? (In the last 13 months, its indicator is an average of 93%.) Of course you are not. That’s what I’m here.
Djokovic is easy enough to explain. His last 13 months became a rocky. If we expand the time frame by 2020, its number is hit by 97.1%.
Dimitrov is higher than expected because of trust in slices. Dan Evans was also better than this metric. Although slices don’t create too many abusive opportunities, it is a good way to continue the balls in the game. I hesitate to rule out slices from metric, but some kind of adjustment is likely to be in order.
De minaur can open another limit to this approach. One of the assumptions I hit together is the winners of everyone to the same price. But Aussie is relatively small: only a magic wand can not create winners as they can wave and guilty. Should take more risk to finish points. For this set of shots, its winner / error ratio is 10.7% to 10.0%. My model assumes that some of the mistakes are the aggressive images that miss the sign of the sign. What if it’s more? In the world of Bizarro, where players really celebrate their intentions before each stroke, we can see more of the number of minic errors in this category.
Or, perhaps not heel As firm as we think. In both cases, the next time it is something to watch the time you adapt to a match.
Back to Alcaraz
Why is the name of Carlitos in the title? The sinner (or tien or ruud) are better than most of these sizes.
This is what I am fascinated about the shooting tolerance clever to explain. If the shooting tolerance identifies something, it should tell us who will win long rallies. And to some extent: the sinner overlaps the list of tolerance and he wins more rallies than anyone. (Although it proves a lot of things: sinner is better than anything else or not.)
Again, Alcaraz is not behind long rallies. Spain is in second place with room for reserve. Tommy Paul, the stuck tolerance makes it better in metric, but only wins only 51% of long rallies.
X-Factor, I think it’s the tolerance instrumental. You can win some dots by hitting your opponent by hitting the opponent, because yes, they will eventually miss. But almost often you will keep the rally live, even a little in your favor and they will take a risk that pays. If that opponent is guilty, it is probably the result. Just ask the de minavr who lost all of their career meetings with Italian.
Alcaraz’s long rally spells do not appear in the metric of the tolerance, which is not limited to the start. The signature carlitos point is a ten-stroke rally where it puts or polished on the network with a drop of damage. Its initial prowo is not a match not enough for the sinner and his net skills are behind the feder or Nadal. Is there a player who can successfully go to acrobatics as a successful rally?
Spain is often approaching the net halves as the sinner. He earns about three-thirds while he does. In today’s game, the average rally should be a net approach earnedAnd many powerful discounted players do not have basic skills to create this chance.
The tolerance injected, then it is not necessary, but not enough. (And this is also ignoring short points. The unbreakable rally is not considered a lot when the service does not occur. Alcaraz is close to keeping the point alive and has more choices than anyone when it comes to finishing.
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