Data Types

Qualitative data

This refers to refers to subjective data, meaning that the information is generally based on the thoughts and opinions of the person delivering the information. Depending on the method used to collect the data, such opinions can be those of the performer or an observer of the performance. Qualitative data gathering methods can include:

• coach feedback

• video analysis

Quantitative data

This relates to objective data, meaning the information is generally factual and gathered through the data method. Quantitative data is usually presented in numerical form and gathering methods can include:

• multi stage fitness test

• Illinois agility test

• disciplinary record

Some data gathering methods produce both qualitative and quantitative data. These are methods that combine opinions alongside numerical data. For example, data gathering methods that produce both qualitative and quantitative data include:

• POMS test

• SCAT

• Social facilitation questionnaire

Interpreting Data 

As qualitative data is created from the opinion of an observer/performer, it is important to highlight the most important elements in order to correctly identify strengths and development needs.

Subjective opinions may be based on a general overview of a performance so it can be easy for a performer to miss important pieces of data. For example, when receiving coach feedback, a performer may not understand some of the information given, causing them misinterpret the information and focus on the wrong strengths or development needs. When interpreting qualitative data, it is important to seek clarification on the information provided.

Quantitative data may be easier to interpret as data is presented in numerical form. Quantitative methods to collect data on performance are usually very specific to a factor therefore, with comparisons to previous tests or others, it can be easy to identify strengths and development needs. Many tests also have normative data, allowing a performer to place their score within a category (for example, excellent, good, average, below average, poor), helping them identify their priorities for performance development.

When seeking areas to improve within a performance, it is important to use both qualitative and quantitative data. For example, seeking out the opinion of a coach/peer can help guide a performer to a general overview of what they need to improve on. Using this qualitative data, they can focus on a quantitative methods that they can use much more effectively to measure the effectiveness of a PDP.