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Discussion Starter · #1 · (Edited)
Though this isn't an exact formula for measuring court speed, it gives you a good idea on how hard it is to break. Here are the percentages to many of the big tournaments in order from hardest to easiest.
Lyon (Indoor Carpet) 2007 13.57%
Halle 2008 14.35%
Artois Championships (Queens) 2007 15.76% 2008 16.75%
Wimbledon Breaking Percentage 1998 19.78% 2001 19.01% 19.21% 2003 19.55% 2006 (3rd-Final) 17.9% 2007 (Total) 17.34% 2008 16.77%
Cincinnati 2007 19.22% 2008 16.45%
Basel 2007 (Carpet) 17.21%
Madrid 2007 (Total) 18.02%
St. Petersberg 2007 19.87%
Paris 2006 19.89% 2007 (Indoors) 20.08%
Dubai 2007-2008 21.10%
Montreal 2005 20.76% 2007 21.12%
Miami Breaking Percentage 2007 22.32% 2008 21.70%
US Open Breaking Percentage 1998 21.53% 2002 (3rd round-Final) 2006 (3rd round-Final) 20.74% 2007 21.87%
Indian Wells Breaking Percentage 2007 21.93% 2008 22.97%
Aussie Open Breaking Percentage 2008 (Total) 23.18%
Rome Breaking Percentage (Total) 2007 23.34% 2008 23.25%
Toronto Breaking Percentage 2004 18.33% 2006 23.53% 2008 21.03%
Roland Garros Breaking Percentage 2007 24.13% 2008 23.68%
Chile Breaking Percentage 2008 24.85%
Hamburg Breaking Percentage (Total) 2006-2008 27.78% 2008 27.23%
Brazil Breaking Percentage 2008 28.12%
Monte Carlo Breaking Percentage 2005 30.55% 2007-2008 29.20%
Estoril Breaking Percentage 2008 30.84%

More Stats here to add to back up my breaking percentage idea. All slams are 3rd Round-Final only.

First Serve Points Won Cincinnati 2008 75.78%
Aces per First Serve Cincinnati 2008 18.94%
First Serve Points Won Wimbledon 2006 73.85% 2007 73.94% 2008 74.64%
Aces Per First Serve Wimbledon 2006 14.61% 2007 13.4% 2008 15.34%
Aces Per First Serve Basel 2007 16.83%
First Serve Points Won Basel 2007 73.36%
First Serve Points Won 72.63%
Aces Per First Serve St. Petersberg 2007 10.67%
First Serve Points Won US Open 2002 71.75% 2006 71.78% 2007 70.42%
Aces Per First Serve US Open 2002 14.66% 2006 12.63% 2007 11.94%
First Serve Points Won French Open 2008 68.71%
Aces Per First Serve French Open 2008 9.78%
First Serve Points Won Rome 2008 67.8%
Aces Per First Serve Rome 2008 8.18%
First Serve Points Won Hamburg 2008 66.76%
Aces Per First Serve Hamburg 2008 8.22%
 

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Discussion Starter · #4 ·
Re: Court Speed Theory

I know this probably took a long time, but you'd have to look at a few more years to see if these numbers don't just differ by chance.
Don't know if that will help. They tend to mess with the speed sometimes. The slams are more accurate than the Master Series since 127 matches of 3-5 sets is more data than 55 matches of 2-3 sets. Also the Aussie Open started really slow the first week and speeded up at the end just like predicted with a new surface needing time to speed up.
 

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Re: Court Speed Theory

Don't know if that will help. They tend to mess with the speed sometimes. The slams are more accurate than the Master Series since 127 matches of 3-5 sets is more data than 55 matches of 2-3 sets. Also the Aussie Open started really slow the first week and speeded up at the end just like predicted with a new surface needing time to speed up.
Tnq for the notion and the statistics. Interesting...

But, you are talking about a theory (court speed theory), so you can't count one year observation only. It must be longitudinal if applied for every surfaces, and longitudinally-cohort if only for one surface alone. Otherwise, it is not sufficient for theory. Just call it court speed hypothesis... :D

Of course no need to take this into terminological discussion or academic one. But obvious enough to judge that in your "theory", the breaking percentages might be just differ by chance as RagingLamb said...

I know this probably took a long time, but you'd have to look at a few more years to see if these numbers don't just differ by chance.
No need to wait years to come. Just add past years' statistics or let somebody else provide the data and see what we can find next...
 

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Re: Court Speed Theory

interesting...
 

· Forum Umpire:, Gaston Gaudio,
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Re: Court Speed Theory

Good idea, but too many flaws with it.
 

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Re: Court Speed Theory

all in all I like the way you approach this, but it somehow irritates me that, according to it, Wimbledon is considerably faster than US Open and Australian Open:confused:
That's why we need percentage in longitudinal or period of time. Define it first, then make a statistics. The result will be more reliable, whether it irritates you or not.:wavey:
 

· Forum Umpire:, Gaston Gaudio,
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Re: Court Speed Theory

So give some help, plz
Weather conditions can't be measured accurately, then types of match ups, played during that period, if there are Sampras vs Ivanisevic on ice rinks, then the stats will be skewed.

It's actually quite useless to measure it, though nothing wrong with idea itself.

In other words you can make stats say anything you want, but it still will only give a limited perspective.

The court surfaces have changed significantly from 1997 to now.
 

· Forum Umpire:, Gaston Gaudio,
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Re: Court Speed Theory

For one Monte Carlo is not quicker than Hamburg, only unless it has rained every day for 5 weeks.
 

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Re: Court Speed Theory

Weather conditions can't be measured accurately, then types of match ups, played during that period, if there are Sampras vs Ivanisevic on ice rinks, then the stats will be skewed.

It's actually quite useless to measure it, though nothing wrong with idea itself.

In other words you can make stats say anything you want, but it still will only give a limited perspective.

The court surfaces have changed significantly from 1997 to now.
If there is a unique condition in a particular year, it doesn't mean we can't make generalization. And you just helped us by narrowing the problem. Now we can start with a certain period, 1997-now and a period before it if you want (also after someone can define this period.)

We could also crosscheck the stats with type of player who won the tournament during a period in order to make the generalization stronger and more informative ...
 

· Forum Umpire:, Gaston Gaudio,
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Re: Court Speed Theory

If there is a unique condition in a particular year, it doesn't mean we can't make generalization. And you just helped us by narrowing the problem. Now we can start with a certain period, 1997-now and a period before it if you want (also after someone can define this period.)

We could also crosscheck the stats with type of player who won the tournament during a period in order to make the generalization stronger and more informative ...
It doesn't work, the perfect example is in the first post. If the slower the surface means more breaks of serve, then Hamburg would have a higher percentage than Monte Carlo.

With the match ups, is it 2 big servers playing on a very fast surface. I have highlighted the problem. Rome is the fastest, but if they get wet days, then it changes the dynamics, humidity and wind as well, can't be measured accurately, as it changes the match up, which will effect the numbers, therefore leaving the speed theory flawed.

So, there are too many flaws for it to be accurate, and stats can be manipulated.
 

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Re: Court Speed Theory

Well my theory of court speed is the higher the breaking percentage, the slower the surface is. I decided to do a bunch of tedious work to get the breaking percentage of all 4 slams and some of the Master Series. Anyways here are the numbers.
Wimbledon Breaking Percentage (Total) 17.337%
US Open Breaking Percentage (Total) 21.87%
Aussie Open Breaking Percentage (Total) 23.179%
Roland Garros Breaking Percentage (Total) 24.132%
Monte Carlo Breaking Percentage (Total) 29.22%
Hamburg Breaking Percentage (Total) 26.8%
Rome Breaking Percentage (Total) 23.34%
Indian Wells Soon available
Miami Soon Available

Sorry to disappoint you but that has been used to determine the speed index for all surfaces. I've post that 5-6 months ago and will try to find links to it.:wavey:
 

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Discussion Starter · #18 ·
Re: Court Speed Theory

It doesn't work, the perfect example is in the first post. If the slower the surface means more breaks of serve, then Hamburg would have a higher percentage than Monte Carlo.

With the match ups, is it 2 big servers playing on a very fast surface. I have highlighted the problem. Rome is the fastest, but if they get wet days, then it changes the dynamics, humidity and wind as well, can't be measured accurately, as it changes the match up, which will effect the numbers, therefore leaving the speed theory flawed.

So, there are too many flaws for it to be accurate, and stats can be manipulated.
Monte Carlo was considerably slower by 2.4% or something like that. That is a big enough gap imo to say the stats won't vary enough for it to be easier to break in Hamburg. Monte Carlo had its share of dry days this year as well. Also the big factor of why I think it is so hard to break at Wimbledon is the unpredictable bounce. Hard courts give you a true bounce so yeah that variable between hard courts and grass can mess up the speed there. Still advantage server even though the proof of the actual speed is hard to figure out.
 

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Re: Court Speed Theory

Don't know if that will help. They tend to mess with the speed sometimes. The slams are more accurate than the Master Series since 127 matches of 3-5 sets is more data than 55 matches of 2-3 sets. Also the Aussie Open started really slow the first week and speeded up at the end just like predicted with a new surface needing time to speed up.
if you do not include more data, you have no way of determining if this is just chance or an actual trend

kafemotor said:
No need to wait years to come. Just add past years' statistics or let somebody else provide the data and see what we can find next...
Yes, that's exactly what I meant. It'd be a good idea to look at data from previous years.
 

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Discussion Starter · #20 · (Edited)
Re: Court Speed Theory

if you do not include more data, you have no way of determining if this is just chance or an actual trend
Someone else will have to do previous years for trend setting. Here's an idea on how much it varies from round to round.
Monte Carlo 2008
Round 1 Breaking Percentage (24 matches) 27.97%
Round 2 Breaking Percentage (16 matches) 26.37%
Round 3 Breaking Percentage (8 matches) 31.95%
Rounds 4-6 Breaking Percentage (7 matches) 36.92%
Hamburg 2007
Round 1 Breaking Percentage (24 matches) 27.61%
Round 2 Breaking Percentage (16 matches) 25.39%
Round 3 Breaking Percentage (8 matches) 27.47%
Rounds 4-6 Breaking Percenatage (7 matches) 26.48%
Rome 2008
Day 1 Breaking Percentage (14 matches) 23.51%
Day 2 Breaking Percentage (12 matches) 24.45%
Day 3 Breaking Percentage (14 matches) 23.1%
Days 4-5 Breaking Percentage (11 matches) 22.22%
Roland Garros 2007
Round 1 Breaking Percentage (64 matches) 23.33%
Round 2 Breaking Percentage (32 matches) 24.86%
Round 3 Breaking Percentage (16 matches) 24.20%
Round 4 Breaking Percentage (8 matches) 28.11%
Rounds 5-7 Breaking Percentage (7 matches) 23.43%
Wimbledon 2007
Round 1 Breaking Percentage (64 matches) 17.41%
Round 2 Breaking Percentage (32 matches) 17.07%
Round 3 Breaking Percentage (16 matches) 17.744%
Round 4 Breaking Percentage (8 matches) 19.28%
Rounds 5-7 Breaking Percentage (7 matches) 14.737%
US Open 2007
Round 1 Breaking Percentage (64 matches) 21.49%
Round 2 Breaking Percentage (32 matches) 21.59%
Round 3 Breaking Percentage (16 matches) 21.908%
Round 4 Breaking Percentage (8 matches) 23.23%
Rounds 5-7 Breaking Percentage (7 matches) 24.995%
Aussie Open 2008
Round 1 Breaking Percentage (64 matches) 23.84%
Round 2 Breaking Percentage (32 matches) 23.60%
Round 3 Breaking Percentage (16 matches) 20.69%
Round 4 Breaking Percentage (8 matches) 24.21%
Rounds 5-7 Breaking Percentage (7 matches) 19.72%
Miami 2008
Round 1 Breaking Percentage (32 matches) 24.699%
Round 2 Breaking Percentage (32 matches) 20.954%
Round 3 Breaking Percentage (16 matches) 17.85%
Round 4 Breaking Percentage (8 matches) 22.91%
Rounds 5-7 Breaking Percentage (7 matches) 18.792%
Indian Wells 2008
Round 1 Breaking Percentage (32 matches) 23.49%
Round 2 Breaking Percentage (32 matches) 22.35%
Round 3 Breaking Percentage (16 matches) 23.14%
Round 4 Breaking Percentage (8 matches) 21.83%
Rounds 5-7 Breaking Percentage (7 matches) 24.64%
 
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