Team sport can be a highly social and rewarding form of physical activity for youth. Unlike individual sports, team sports involve a group of players playing together, thereby promoting cooperation, mental toughness, and the satisfaction of reaching personal goals (Fresno Pacific University).

Norms of effort and performance define the collective identity of members of a team and provide one of the key features that distinguish a sport team from a conventional group [6, 7]. These norms, which are largely formed in practice sessions, inform athletes’ expectations regarding what behaviors are appropriate across various contexts relevant to sport participation, such as practice and competitions.

Tracking data provides practitioners with a variety of metrics to monitor athlete performance during training and matches. However, there are a variety of considerations that need to be considered when choosing the most suitable tracking system and corresponding metrics for use in team sport.

Physiological output is a key indicator of athlete effectiveness during competitive play and is often overlooked during tracing. Athletes execute periods of high-intensity running and cyclic movement that are significantly more intense than a game average [8, 9].

The volume and complexity of the trace from athlete tracking systems makes it difficult to detect such changes in physical output via aggregate parameters alone. Hence, time series analysis has been utilised to analyse how athletes’ physical output changes during a match as a function of time.

Similarly, the frequency of movement and occurrence of high-speed accelerations and decelerations is also commonly tracked to assess whether these characteristics are a predictor of a sports team’s success during a match. In addition, a variety of behavioural patterns are captured through the interaction of teammates, which can be analysed via integrated team communication (ITC).