For a long time I didn’t think much about blocking statistics. The standard measure was blocks per set and that is the measure I used.
I had my first epiphany on the topic when I first noticed that the best blocking team in my league was only ranked fifth according to the current statistical norm. In this case the statistics were clearly not an accurate reflection of the actual game. So I started to dig deeper.
The first two logical steps were opponent’s attack percentage, as a general guide, and block percentage (ie percentage of opponent’s attacks blocked), for more detail. With these two figures I feel I have a much better grasp of how my team actually blocks.
But in the individual sense this doesn’t completely fill the void of understanding, especially when it comes to judging the real effectiveness of middle blockers.
Which leads me to my question…
Assuming access to all raw data, which statistic would most accurately measure the contribution of a middle blocker to team success?
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Meiner Meinung nach kann die Effektivität der Mittelblocker nicht bewertet werden, ohne die Abwehr der gesamten Mannschaft zu untersuchen.
Vollkom richtig, aber was ist der Teil der Mittelblocker in die gesamte abwehr Effektivität?
I am not sure if that could be measured at all. I think something like the effectiveness of a middle blocker is too complex to measure on regular terms. Isn’t for example something like taking out the opponents middle part of the middle blockers job? And if it is and he does, isn’t he effective then? Or do you blame him for not helping out on the outside good enough, creating double block situations? And how do you want to measure all this? That’s lots of regular statistics to put together and also to weight. Which statistic is more important over another?
I don’t know. It’s a tough question and I have no positive answer. I am curious what other coaches have to say 🙂
The middle blocker is responsible for carrying out the total blocking scheme of the team. That answers your first question.
His overall success is partly dependent on the serve, the defence behind him and the success of the transition attack. But what is his direct contribution? Is it opponent’s attack percentage when he is front? Or points won? Or percentage of points won minus service aces? Or…
Start with the assumption that everything can be measured. Now let your imagination run wild 😀
Your comment on success partly dependent on the serve is interesting. Having worked mostly in Men’s Volleyball when I started coaching a women’s team I focused on blocking match ups more then other match ups. But Hugh Nguyen and I realised with the difference in serving in women’s game ment that the serve match up was much more important.
Oliver is probably right. But there are many things in Volleyball that appear to be non-measurable. That’s why statisticians in sports try to find numbers that describe the reality as close as possible. So whether we agree, that certain things are measurable or not, one can discuss numbers that represent a successive approximation to reality.
I think, this approach is valid not only for the effectiveness of middle blockers but for everything.
When discussing numbers, one can start with the question on what is a block – or better let’s first ask about block attempts.
When a blocker is fooled by the setter, jumps on first tempo and the set goes to the outside hitter (which happens very often, as you know 😉 ) – is this a blocking attempt ?
When (in another rally) the blocker jumps with the real attacker and the attack does not even touch the block – is this a blocking attempt ?
… to be discussed …
Great point about measuring. We are just trying to get closer and closer to ‘reality’. The only thing we can be sure about is that ‘reality’ is not what we think we see. 😉
Thanks for your remarks, guys! These really trigger a lot of thoughts.
Actually, I never thought of statistics, or quantitative measures in general, as trying to give an accurate picture of reality. Rather I was, or maybe am, thinking that by using numbers we’re trying to highlight certain aspects of reality, while purposefully neclecting others, i.e. we’re trying to reduce complexity in order to enable ourselves to decide and act.
Whether some measure is oversimplified or overcomplex is then a question of balance in relation to the purpose(s) for which we use it. So I’d definitely like to hear what could be the use of an overall mesure for middles’ contribution to overall team success, Mark.
I presume that it’s gonna be something along the lines of comparing players, either different players (for putting together next seasons roaster or th line-up for a particular match) or the same person over time (for measuring progress in training). However, in neither case do I see a great value in an combined overall measure. For one thing, there are important aspects of middles that hardly can be quantified, as others have been ponting out here already. Second, I think, the weighing factors of the different aspects should vary with the circumstances. E.g. opponents have strong outside hitters, I’d prefer middles that are quick on closing outside blocks and would be wiling to trade this feature against fixture of opponents quick attacker. This easily might be the other way around with different opponents.
Neither of this is meant to say that statistics cannot be helpful, of course. Rather the contrary is the case, I think. There is great value in collecting data, e.g.on how many effective blocks a certain players has against high balls to opposites, if that is what I as a coach consider to be one middles weak point and want to plan and evaluate training accordingly. And of course these numbers have to be correct and in that very sense a description as close to reality as possible.I think, many of the contributions here give an excellent overview on what aspects of the game are important to be mastered by middles and can be measured quantitatively one by one, though.
As I commented to Oliver, the middle blocker is responsible for the entire blocking scheme. Therefore an attack attempt when he is front row must be considered a block attempt. If he blocks in the wrong part of the net, we have to include that.
So now we can define at attempt, step two…
If I could have all the data I want, I would be looking at the percentage of outside sets that have a double block and a triple block, block touches per attack attempt, and points per block touch. I would look at that as well the statistics you mentioned to measure the defensive half of the game.
I am actually a volleyball coach in UAE
and I was middle blocker few years ago and I played with the Tunisian National team in two youth world championship EGYPT 2001 and Iran 2003
middle blocker have many task to do in blocking and so in offense
blocking part:-stopping the 1st tempo hitter (fast)
-(if high ball)reaching the side blocker to create a double bloc on the side hitter
-(if fast side ball) reach the side blocker and cover even a small area in the field
-(if too fast) cover down the side blocker for any tips or touch bloc balls
offense part: -fix the opponent middle blocker so the side hitter can hit with single bloc
-hit very fast balls in first tempo so you fix bloc and the defense to be near the 3 meter line
in my opinion to measure how a middle blocker contribute to the success of the team we have to do a very specific statistics and we need to count
-effective blocs (points)
-balls touched in blocs with no points
-how many times he reach the side blocker and how many times he doesnt
-how many points in hit
-how many times he fixes the opponent middle blocker
and the best thing to know who is the best middle blocker in your team is by asking the setter and the side hitters because they know exactly who is helping them in all these parameters I just wrote
thank you very much
many good ideas from wael chamakhi!
covers most of the things I would have included…
the only thing is you need to include the percentages of the opponent attackes somehow. there are attackers that will kill you if they find only a single block, and there are some you might still defend. so so need to account for that, when judging the ability of a middleblocker to build a doubleblock.
and what’s more is, that you have to take into account the opponents reception as well. so all of tha data but also in categories after perfect pass, good pass, bad pass…. that would also give you an idea in which are the MB has to work…
Really interesting question – here are some thoughts:
– anything you look at has to be in relation to opponent spike attempts, not points or rallies.
– you could look at the percentage of opponent attacks that do not end in a kill. This should indicate the block/defence effectiveness
– you need to factor in the number of block points that the middle was involved in. Or maybe just the number of block points. If there is a one on one stuff on the outside, then you could argue that this was an effective implementation of a strategy.
– do you count block touches and/or tools? If so you should factor this in.
– if you count block touches/tools then you could relate this back to the end location of the hit. If the ball goes at right angles this would not be good, but if it stays in the ‘channel’ of the court, then this could still be a good block.
I’d suggest looking at these things, putting them together, then comparing some great/good/medicore middles and see if the numbers resonate.
I am still not convinced that you can measure the effectiveness of a middle blocker. Some of the ideas mentioned here include things the middle can not effect directly or indirectly (like his own teams service) that should be excluded from any measurement. If you count those in don’t you measure the teams effectiveness? So if it’s only the middle blocker the ideas Alexis brought in look good to me. But do all these factors really weigh the same? Don’t you have to value some of them more then others? And if it’s yes, how do you do this?
The idea is to isolate the influence of the middle blocker, so you have to take the serving factor out. Absolutely.
You are right the weights for different situations can’t be the same. My first idea is to weight blocking against positive and perfect reception 1.5 times other reception. And perhaps in transition 0.5 times bad reception.
What are your suggestions?
I haven’t thought about weighing this yet and agree completely with you. What I was thinking about was more how to weight the concrete block. How for example to give the middle blocker credit for closing the double block and forcing the outside to attack another direction? If that leads to an error on the attackers side or enables the team of the middle blocker to be successful in transition you could rate it 0,75 times compared to a successful block by the middle.
But here comes a question: Don’t you have to weight the same situation with the exception that the opponent’s outside scores against the other blocker at least 0,5 times? The middle blocker did his job…
Hey Mark, I just stumbled across the blog and have really enjoyed reading.
I would argue that success (measured by traditional metrics) for a MB depends mostly on serve, which is something completely out of his control. The players who precede a MB in the service order can have a massive effect on his blocking statistics. Situations where there is only one (or even two, to a certain extent) hitter available increases the odds for the blocking team but may not reflect the actual ability of a MB. So in order to measure the independent ability of a MB, we need to limit any effect that a serve has. Any measure that includes points won or opponent attacker percentage have included in them the effect of the serve, which can skew results.
I like the idea of weighting, though assigning percentages to different situations can be tricky, and in the end we may subconsciously assign more weight to things that we already traditionally value, and miss some big ideas. That being said, I don’t think it’s impossible.
If we borrow a page from baseball and sabermetrics, we could calculate the expected percentage of success for all MBs in a league in certain situations, and compare our MB to the average. (This is a modified version of WAR, or Wins Above Replacement, which measures the net wins in a season that a player contributes versus an average player on the bench). With a percentage success rate assigned to different situations (eg a perfect pass and a pipe set, or a positive pass and a fast set outside), we could see what percentage of plays our MB is successful in. With such specific parameters it would take some time to build a complete data set on a MB, but in the end, an independently good MB will have a success percentage in a each category that is higher than the league average, and does not depend on service.
What should count:
-Solo and double blocks involving the MB (when it is a success or failure)
-Solo blocks on the wings (only when it is a failure)
What should not count:
-Triple blocks (at all times, since MB contribution is only 1/3)
-Solo kill blocks on the wings (it may be the implementation of a strategy, as Alexis said, but would weigh too heavily in favor of the MB for a negligible contribution, so easier to exclude it)
-Hitting errors (straight out, into the antenna, etc)
-Kill block (MB solo or MB double)
-A ball that is touched by a defender (this hopefully incorporates the positive effect of channeling a ball with the block, while minimizing the effect of bad defending)
-A ball that is played off the block and is covered by the attacking team
-A ball that is tooled out
It’s not perfect, but I don’t think you can have a truly independent measure that doesn’t lose some of the contributions a MB makes, just as you also can’t have a complete measure that is totally independent. This example is on the extreme side of being independent, but seems necessary when you look at how dependent most of the traditional statistics in volleyball are.
I’m late to the party (and to your blog) on this one but I thought I’d throw in my two cents to back up what Matt Reynolds has said above. I’m a statistician in the AFL industry and a major part of my job is defining measure for clubs and media to use for analysis. I have been involved in volleyball for quite a while but only a very amateur level so I don’t have any idea what measures are available at an elite level. I remember seeing Alexis present a paper at the AIS a few years ago on rating setters using traditional statistics but that’s as much exposure as I’ve had.
I like your idea of weighting based on the quality of the pass but I think it’s dangerous to do it arbitrarily.
A few years ago we developed a measure in the AFL to grade the ability of a player’s kicking. The existing traditional measure was kicking efficiency – the percentage of a player’s kicks that were effective, but this gave highly skewed results across different playing positions, particularly in favour of defenders who have more space to kick to and are generally under less pressure than other players. We invested heavily to expand the detail of our recorded stats so we now have a measure (six distinct categories) of how much pressure a kick is under from opposition players, the length of the kick, the intended target (shot at goal, kick to a stationary teammate, kick to a leading teammate, etc) and even whether it was left/right foot. These extra variables are then combined to categories each kick to get a measure of difficulty and eventually, a relative efficiency called a Kick Rating. A player deep in defence might hit targets 85% of the time, but others in the same situations as him might do so 90% of the time, so that player would be rated a worse kick than one who hits targets 50% of the time, but is attempting kicks that are normally only effective 30% of the time. This new rating has been adopted by AFL clubs as a definitive and trusted measure.
To steer it back to volleyball… You would have to first define the success/failure measure for the MB, which you’ve started to do in previous comments. I’ll leave that to those with a more intimate knowledge of the elite level of the sport. From there you would need to classify the possible situations a MB can find themselves in – taking into account serve/pass quality, setting option and potentially even the attack patterns of the available hitters, not just the one given the ball. Taking success/failure measures across the populating within each of the possible blocking situations would then give you a better understanding of what is expected of a MB and hopefully give a more accurate measure of their contribution based on opportunity.
Hopefully this has been a positive contribution and not just a really long ramble…
Thanks, Karl. Your comment is by no means a ramble.
Thanks for the insight into your sport. (Another time I’ll ask you why the AFL doesn’t call itself a sport anymore 😉 )
For the moment, I don’t have the resources to develop this into a single number. I am working with a range of figures from different situations and trying to increase my understanding based on those, rather than necessarily trying to rank MB’s absolutely. That would be a goal for a later time.
One question though. One commentator on the facebook page suggested that kill blocks should have an extra weight because of their psychological impact. In your example, would kicking a goal give extra weight to a kick?
Kicking a goal doesn’t carry extra weight. My thoughts are that trying to measure psychological impacts of on-court actions is dangerous. I’m sure that there is a significant effect, but I can’t think of any way that it could possibly be measured with any confidence. You could look at giving extra weight to a kill block but the danger is that whatever weight you choose will be almost certainly be arbitrary.
We have noticed that especially when kicking at goal, teams playing against good teams have significantly worse accuracy than teams playing against poor teams, even when controlling for the difficulty of shots taken. We’ve all but decided that it must be a psychological factor of players knowing they need to make the most of opportunities against good teams. Acknowledging or discovering this and actually building it into a measure are two very different things.
Now that the German league started its season, I stumbled over some Data Volley scouting files and was astonished on how differently blocks were scouted and by that means valued/weighted.
Re-reading the above comments I think that we are like discussing the third step when not knowing how to do the first one.
Even in elements where we have settled statistical numbers (like i.e. kill percentage for attacks), I bet there are many different opinions on how this kill percentage contributes to team success.
For middle blockers we don’t even have those well-known numbers.
We have some attack numbers – which we should not discuss here, because the focus obviously is on the defensive part of the position – and the blocks per set, mentioned by Mark in his first paragraph.
“Assuming acces to all raw data …” is hypothetical IMO.
For me as a scoutman the story starts if I can key in correct codes.
As stated above, every attack attempt should be blocked … OK, agreed.
Now there is another point coming in:
Data Volley coding of element “quality” should very often be seen more like a “game progression”. Like A- means that after your attack the opponent is in control of the ball and can launch a counter attack , A+ means that your team gets control again. This does not really absolutely measure the quality of attack.
The DV manual states:
= Error (hands out, net ball, ball in own side or opposite side )
/ Invasion (point goes to the other team)
– Poor (the opponent can play the ball again)
+ Positive (the ball is touched and can be played again by the home team)
# Winning (direct point)
This a very good starting point for me though there are only codes entered if the blocker actually touches the ball.
To conclude my opinion: only if we have settled numbers (2nd step), which can be calculated out correct statistical recordings (1st step), then we can start to create a formula (or probably every coach will have his own) to measure the contribution (3rd step) of an element (or player role) to success.
Dear Coach Mark,
I am working on my Master Thesis to develop a rating scale like the 4-point reception scale on blocking, considering stuffing block, rebound block, blocking error and etc. We are using mathematical model to see the probability of the team score the rally under each blocking scenario. Hope to see your insight and would be happy to discuss with you further.
I would be happy to discuss it with you, and to see your results. Send me a message on my facebook page (www.facebook.com/AtHomeOnTheCourt) with your email address and we can make contact.