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Which Attack is the Most Effective in Volleyball: Hard Attacks, Roll Shots or Tips?

Tipping in Volleyball

I previously wrote a post on how tipping in volleyball, compared to hard attacks, is effective but undervalued in the women’s game and at lower levels (see link).  Due to this finding, I decided to coach tipping to the two teams I coached this season.  I found tipping was highly effective for Flaming Six Coyotes Women (and for our opponents too) so I continued coaching the team to tip more to keep the points rolling.  I found the opposite to be true for UCL Men as they were terrible tippers so I stopped coaching it.  

The effectiveness of tipping with my teams was actually in line with the original analysis.  Despite this, I wanted to revisit this topic.  Firstly, I have statted much more matches since that post in 2019, especially seeing that I statted nearly every match in the 2019-20 season of the Women’s Super League.  Secondly, I have data at different competition levels to analyse, such as the Women’s London Division 1, BUCS Men Division 1, Women’s All Nations Tournament and Boys Under 18s Summer League.  Thirdly, I did not include attacks blocked killed as an attack error in the original blog post so this was something I wanted to correct.   All of this means I can really look at how effective hard attacks, roll shots and tips are in relation to the competition level.  


The chart below shows the Attack Point Scored % and Attack Efficiency % of the attack separated by shot type (hard, roll and tip) at the various levels of the women’s game.  Attack Point Scored % is calculated as =Attack Points Scored/ Total Attack Attempts and Attack Efficiency % is calculated as =(Attack Points Scored – Attack Errors)/ Total Attack Attempts.  The Attack Point Scored % and Attack Efficiency % are also commonly known as the Kill % and Hitting %, respectively.  

You can see that tipping is the most effective attack at BUCS Tier 1 level and London Division 1 level.  Hard attacks are the most effective attack in the NEVZA Club Championship, Super League and Women’s All Nations.  However, tipping is only 1% less effective compared to hard attacks in the NEVZA Club Championship and Super League.  Roll shots are the least effective type of attack at all levels except for BUCS Tier 1 level.  

It looks like the higher the playing level, the higher the effectiveness of hard attacks.  NEVZA and Super League players should be bigger physically and better technically compared to BUCS Tier 1 and London Division 1 players.  This is pronounced in the All Nations Tournament where I basically had Super League players (in Team USA) playing against mostly London Division 1/2 level teams (of course we played some very good teams but this only makes up a small percentage of the data).  

It is surprising to see that tipping is effective at all levels, with a consistent hitting % of around 20±3%.  Only tipping effectiveness in the All Nations is markedly lower at 12%.  The reason why tipping is generally effective statistically is that it is a very safe type of attack to execute (a low 10% error rate) while you will still consistently get kills (consistently around a 30% kill rate).  


The chart below shows the Attack Point Scored % and Attack Efficiency % of the attack separated by shot type (hard, roll and tip) at the various levels of the men’s game. 

It looks like hard attacks are the most effective form of attack at all levels.  I suspect this is because even at Men’s BUCS Tier 1 level, the players are big enough and good enough to make hard attacks work.  The exception is Boys Under 18s where tipping is the most effective form of attack.  The reason for this is probably because Under 18 Boys are still developing so their hard attacks are highly inconsistent (or wild) whereas tipping is still a safe shot to make.  

Hard attacks generally become more effective the higher the competition level.  It does appear that tipping is ineffective at mid competition level but is increasing effective at the higher and lower levels.  However, the data I have at the higher and lower competition levels are based on limited data of 4 to 7 matches only.  More match data can drastically change that.    


The original question is which attack out of hard attacks, roll shots or tips is the most effective in volleyball.  The answer is it depends on the competition level.  Hard attacks are the most effective form of attack at higher competition levels.  It is definitely the clear route to scoring points in the men’s game whereas tipping is a great option too in the women’s game as tipping is nearly as effective as hard attacks.  

However, the effectiveness of hard attacks does decrease the lower the level.  It means at some competition level, tipping becomes the most effective attack compared to hard attacks.  This is the case at Women’s BUCS Tier 1, Women’s London Division 1 and Boys Under 18s level.  

Roll shots are generally the worst type of attack in both men’s and women’s games.  

An interesting find is that tipping is consistently effective at all levels in the women’s game.  It looks to have a consistent hitting % of around 20±3% and a kill rate of around 30%.  In the men’s game, there’s some evidence that tipping is not effective in the mid-level (BUCS Men’s Tier 1 and Men’s Super League) but it becomes more effective at the higher level (International, Champions League) and lower level (Boys Under 18s).  However, there’s limited data of 4 to 7 matches at those levels so it is volatile to change with more match data.  

In Practice

The findings do make it quite clear in regards to how I should coach my teams next season.  For Flaming Six Coyotes, I suspect tipping will still be effective in the Women’s London Premier (since we got promoted from Division 1) so I will definitely still be coaching that.  For UCL Men, there’s nothing in the analysis to suggest tipping will work in the BUCS Premier South league (since we got promoted from BUCS Division 1), so I’ll just let the guys hit hard.  For Polonia SideOut London, I will have to inform Coach Kontopoulos of this finding so he can encourage the team to tip more.  A new team I will be coaching next season is the American School of London Varsity Boys team.  The data indicates tipping is highly effective at that level so this is something I will definitely coach.  You can probably find out how that worked out in my coaching reflection next year.  

*** Update 12 July 2022 ***

It was great to see John Forman at Coaching VB wrote a blog post (To tip, or not to tip) about this blog post.  I like reading his blog posts because there’s always interesting snippets of information to think about.  Anyway, he wrote some concerns about what I wrote that I wanted to address.

“Consideration #1: Interaction of attack types
First, it is important to understand how the success of tipping/rolling relates to hard swing performance. Generally speaking, the idea of a tip or roll shot is to catch the defense expecting a full swing. That is, of course, not counting the times when it’s just about trying to get the ball in the court.”

This was one thing I addressed in my previous blog post.  The attack stats do not differentiate whether it came after a good or poor set.  I imagine most of the tips come after a tight set near the net as an emergency shot so it should be easier to read.  If a tip comes after a good set, I suspect tipping is more effective because the defence is expecting a hard attack.  Unfortunately, I can’t collate this data because I don’t (as of yet) collect setting stats.  Once I do (probably using this system), I can calculate the effectiveness of the attack by attack type (hard, roll, tip) and set quality (good, too far off, too far in, too tight, too wide).  

“What happens as you increase the frequency of off-speed shots? Or if your effectiveness when spiking is low? The defense starts to expect the tips and rolls, right? Maybe they move a defender in to a position dedicated to tip coverage. That means tips score less often. It’s a case of diminishing returns, so you need to find the balance point.”

If you increase the frequency of tip attacks by 10% for example, I don’t think players and teams will notice the difference.  I did it with Flaming Six Coyotes and I didn’t see the team adapting.  Of course, I say this without data to back it up.  It would be an interesting exercise to chart the percentage of attack attempts that are tips and the hitting percentage for tips on a set-by-set or match-by-match basis.  This could be a future blog post.  

In any case, even if the opposing teams do adapt, your team can adapt too.  If the outside hitter tips to 2 and the player at 1 anticipate this, the outside hitter can also power tip deep to 1.  Similarly, if the outside hitter tips to 3 and the opposing outside hitter at 4 anticipates this, the outside hitter can always tip sharp to 4.  I recently had a training session focused on tipping practice.  Even when the defenders knew the attackers were going to mostly tip, there were still plenty of kills.  Also, remember that the hard attack option is not taken away.  The attackers in the training session were mostly tipping but I did allow the odd hard attack to keep the defence honest.  I did feel that the hard attacks looked more effective because the defending team kept cheating by defending more inside the court to anticipate the tips.  

“Consideration #2: What happens on non-kills?
We also have to keep in mind that we can’t just consider offensive effectiveness in terms of kills and errors (hitting efficiency). It’s also worth looking at what happens on those non-terminal plays. There’s a big difference between an attack the has the opponent scrambling and one which results in an in-system offensive opportunity.

As a result, a somewhat better metric to use here is rally win% after the off-speed shot. That will better capture what happens when there isn’t a kill or error.”

I have previously thought about using another performance indicator other than the classic hitting % [=(Kills – Errors)/ Total Attack Attempts] to measure the attack (see link).  It was on the idea that around 55% of attack attempts end the rally with a kill or error so the hitting % ignores 45% of the other attack attempts.  I did float the idea of basing the attack performance indicator on the +1 attack (it includes the probability of winning or losing the next attack) or the Rally Win %.  I noted back then that I would still stick to the Hitting Percentage because it is already highly correlated with success in volleyball (see link) and players understand what it is.  However, it would be an interesting idea to go through that process and see what the results are like.  



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