Data types

1. Categorical/ ordinal

1.1. Data that can be grouped into categories, with or without a set order.

1.1.1. E.g., win-loss, fast-slow, and injured-healthy.

2. Continuous/ Count

2.1. Data that can take any value (continuous) or countable (count)

2.1.1. E.g., lap time, score and player’s height.

3. Time-series/ Longitudinal

3.1. A series of data points indexed (or listed or graphed) in time order

3.1.1. E.g., game tracking data and player statistics over time

4. Spatio-temporal

4.1. Data that includes both spatial andtemporal information, such as the location and time of an event.

4.1.1. E.g., player tracking data (GPS), ball tracking data

5. Complex

5.1. Data involving text, images or videos

5.1.1. E.g.,writings in training journal, or video footage of a swimming competition