Basketball Statistics Blog

eBA Encyclopedia Statistics Terminology: Pie Chart or Circle Graph Statistics

A pie chart (or a circle graph) is a circular chart divided into sectors, illustrating proportion. In a pie chart, the arc length of each sector (and consequently its central angle and area), is proportional to the quantity it represents.

When angles are measured with 1 turn as unit then a number of percent is identified with the same number of centiturns. Together, the sectors create a full disk. It is named for its resemblance to a pie which has been sliced. The earliest known pie chart is generally credited to William Playfair's Statistical Breviary of 1801.

The pie chart is perhaps the most ubiquitous statistical chart in the basketball statistics analysis. However, it has been criticized, and some recommend avoiding it, pointing out in particular that it is difficult to compare different sections of a given pie chart, or to compare data across different pie charts.

Pie charts can be an effective way of displaying information in some cases, in particular if the intent is to compare the size of a slice with the whole pie, rather than comparing the slices among them.

Pie charts work particularly well when the slices represent 25 to 50% of the data, but in general, other plots such as the bar chart or the dot plot, or non-graphical methods such as tables, may be more adapted for representing certain information. It also shows the frequency within certain groups of information.

Graph from Connect.in.com/

A pie chart displays data as a percentage of the whole. Each pie section should have a label and percentage. A total data number should be included.

Advantages
 • Visually appealing
 • Shows percent of total for each category

Disadvantages
 • No exact numerical data
 • Hard to compare 2 data sets
 • "Other" category can be a problem
 • Total unknown unless specified
 • Best for 3 to 7 categories
 • Use only with discrete data
With data from our eBA Encyclopedia

Read More more details about this definition and another statistical terms at our new Statistics Terminology Glossary.

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