Team sport refers to a broad range of sports that require team members to cooperate and interact with one another to achieve an objective. This often involves careful planning, good preparation, and a mental and physical toughness of the players that make up the teams. Examples of this type of activity include tennis, volleyball and basketball.
Athletes are arranged into teams of five or more, and compete against each other to score points. There are many different types of team sports, and each one is unique in its own way.
Some team sports, such as American football and ice hockey, have large playing fields with multiple goals. Other team sports, such as mountaineering, involve a great deal of technical skill and require high levels of physical strength and endurance.
These games also require a lot of cooperation from each player, and the game may take place indoors or outdoors.
The size of the ice or field, the number of teams, and the level of competition will affect the type of tracking technology that is used in a particular team sport. For example, a field for Australian football is relatively large, ranging from 163.6 m by 145 m (University of Tasmania Stadium) to 155 m by 136 m (Sydney Cricket Ground).
Tracking systems can collect data on distances covered at various speeds and occurrences of high-speed movement, accelerations and decelerations. These metrics can be analysed using time series segmentation to detect how athlete physical output changes as a function of time during a match.
However, metric selection for a given sport is complex due to the variety of technologies available and differing contexts of training and competition. Practitioners must therefore be critical in selecting metrics for a specific sport, given the limitations of tracking systems and the specific needs of their users.
For example, in basketball, the size of the court is limited, so determining speed thresholds for sprinting and high- and very-high speed running may be less appropriate than in other team sports.
Similarly, in ice hockey, the rink is a relatively small area for players to operate on, so identifying a set of minimum distances at different intensities may be deemed inappropriate.
This lack of consensus between practitioners could be a key barrier to the successful integration of tracking systems and derived metrics in team sports. As a result, researchers are now developing new methodologies that incorporate supplementary data sources to provide further descriptive analysis of the athlete’s performance and team characteristics.
These methods are particularly useful in the team sport environment, where physical and tactical data are typically mixed and matched . By aligning these contrasting sources, these analytical methods have provided novel insights into the impact of team competition on athlete load and injury risk.
The application of these techniques to athlete tracking data is a relatively new process, which requires a critical thought process to guarantee the optimal use of these monitoring systems and subsequent derived metrics within a specific context.