The Misuse of a Bell Curve for Determining Your Target Area in Serve-Receive

It is common for many coaches to have their passers target an area 6′-8′ off the net when receiving a serve. The thought is to build in a buffer area to avoid a pass that either goes too close or over the net. Some will use a bell curve to validate this approach (excuse the freehand drawing).


The figure on the left is the target area at the net with an accompanying bell curve. The positive for having this target area is the ability to run a more effective offense, incorporate the middle hitter at a higher rate, use the setter as an attacker, etc. In a traditional bell curve, the average location of the pass is at the peak of the curve. This means that approximately 50% of the passes will be to the left of the peak, and 50% of the passes will be to the right of the peak. So, the thought is that with this target location, a significant percentage of the passes will be over or too tight to the net.
The figure on the right has the target area 6′-8′ off the net. Again, 50% of the passes will be to either the left or right of the peak (average pass). The positive is reduced risk of overpasses from serve-receive while still being able to run an offense. It is important to note that in a traditional distribution pattern of a bell curve, when the target area is 6′ off the net, 50% of the contacts will be a further distance from the net than the target area. So, a significant amount of your offense will have your setter behind the 3-meter line.
Some coaches will also use the traditional bell curve for the setter to target their sets 3′-5′ inside the antenna for a left-side attack. Similar to avoiding overpasses on serve-receive, the rationale for bringing the set inside is to reduce the chance that a set travels outside the antenna. A ball set outside the antenna is a bad mistake by the setter.

I understand the rationale for moving the target off the net. At first glance, using a bell curve to justify these philosophies might make sense. However, I believe that using a traditional bell curve to justify a passing or setting location for all levels of play is inappropriate. It implies that all teams, male and female, and players at every age level possess similar passing and setting skills. It also implies that the level of serving is equal across the various levels of play. These are incorrect assumptions.
There are many types of bell curves. A bell curve plots a distribution of values and the variance from the average (mean). In a normal distribution, the data is symmetrically distributed with no skew. The mean or average value will be located at the peak of the curve. The standard deviation from the mean will either stretch or squeeze the curve. A small standard deviation (in volleyball, this translates to accurate passing or setting) will result in a narrow curve. In contrast, a large deviation (bad passing or inaccurate setting) will result in a broad curve. Using a single bell curve as a rationale for establishing a target area without regard for skill levels is inappropriate.
In the photo below, you’ll see three bell curves.

The red curve might reflect an excellent passing team where the variance of passes is small. Since this team possesses’ good accuracy with only a small deviation, shouldn’t this team pass closer to the net and facilitate a more effective offense? Most attackers are more efficient when the ball travels along the net versus having the set come from off the net or the backcourt.
The blue curve is perhaps a more traditional distribution. A coach whose passers have a larger variance from the target area could justify this team passing 6′ off the net. The variance in passing accuracy is more significant and mandates a larger target area.
The green curve is a team that passes very inaccurately, and their target should be the 3-meter line (or the middle of the court).
If one were to plot variance with your setter, the same concept would hold. If a coach plots the accuracy of the sets, if the variance is significant (green or blue on the bell curve graph), you have setting issues. Either the setter needs lots of work, or you need a new setter. If your setter is accurate, and the variance is small, what would be the reason for the set target to be 5′ inside the antenna? The job of the middle blocker just got more manageable due to having to travel less distance to get to the point of attack.
Most teams at all levels use the Coleman system of monitoring passing statistics, where points are given relative to the location of the pass (3,2,1,0), then an average is generated (points/attempts). I believe that more valuable information is provided for a younger team if we do not use the Coleman system to provide feedback to players. I prefer, especially for younger players, to use a percentage-based system. What percentage of contacts go into the target area? Providing the feedback of “65% of the passes went to target” vs. “you passed a 2.34” will be more meaningful to a 15-year-old player. Using a percentage system might look like the photo below.

Depending on the ages and skill levels of the players, you can adjust the target area. The closer the bunching of passing attempts to the target area indicates the target’s movement to the net. A wide variance of locations mandates a more forgiving target.
The takeaway is that I don’t buy the generic use of a bell curve to justify a certain reception or setting target area. The target areas depend upon the skill level of the players involved. If you have good passers, have them pass somewhat close to the net. If you don’t have good passers, have them target a more forgiving area. One size does not fit all.
If you have a setter with a wide variance in her set location, you must spend more time with that player or identify a different setter. Regardless of the quality of the pass, an inaccurate setter will kill your offensive efficiency.