Analyzing Team Sports Data

A team sport is an organized competitive activity that involves a group of individuals playing against each other under specific rules. The most popular team sports are football, baseball and basketball.

While being a good exercise, team sport also helps your child develop valuable life skills. Working with teammates teaches them how to collaborate, share, and celebrate. Teamwork teaches children to focus on their goals and be persistent and patient. It also teaches the importance of delayed gratification. According to Janssen Sports Leadership Center, being on a team teaches athletes to be selfless and act in unselfish ways to help the entire team.

When it comes to analyzing team sport data, it is important to consider both spatial and temporal aspects of movement. Computational geometry and computational physics are excellent starting points for analyzing the movement of players from a pure spatial perspective, but it is necessary to incorporate time information as well to analyze complex phenomena such as motion patterns.

Generally, team sports are analyzed using descriptive (statistical) data. This data can be obtained manually or automatically through different sensor modalities. However, there is a growing interest in more in-depth and complex analysis of team sports data using advanced techniques such as similarity search, motion capture, and high-dimensional data analysis.

Another unique attribute of a team sport is that its internal processes are controlled to a large degree by outside controls such as the rules of the game, the league, and the coach. This is a distinct feature from other forms of groups that typically have considerable autonomy in their internal processes.