# Applying team strategies for dynamic coordination: A comparative study of expertise using 3-on-3 basketball

## TL;DR

This study explores how expert basketball teams use coordination strategies, making it harder for opponents to predict their movements.

## Contribution

The study introduces a novel approach to analyzing team coordination through entropy measurement in 3-on-3 basketball.

## Key findings

- High expertise teams showed higher entropy in key player movements, making them harder to anticipate.
- Tips on coordination increased complexity in expert teams compared to lower expertise teams.
- Movement dynamics in expert teams were more complex than random walk simulations.

## Abstract

Humans working as a team can achieve higher performance. Studies in sports science, network science, and machine learning have extracted dynamic physical interaction structures of such coordination in team sports. However, the information processing, such as the application of team strategies, has not been fully discussed. The purpose of this cognitive science study was to investigate the application of team strategies for dynamic coordination across different expertise levels using 3-on-3 basketball. In a field experiment, female players, who were selected as prefecture representatives in Japan (Average experience 19.33 years, SD = 4.09), repeatedly engaged in mini-games. Their previous and current affiliated teams competed in national tournaments. We analyzed the difficulty in anticipating offensive movements for the opponent defensive team, quantified as entropy, using tracking position data. This was compared with female players recorded in a previous study. They affiliated with a university team ranked in the third division of the regional league (Average experience 11.33 years, SD = 3.42). There was no such achievement as those in the high expertise condition. Using a linear mixed model with the significance level (α=0.05), the results showed that the entropy for the key player in the high expertise condition was significantly higher than that in the low expertise after the tips condition, and similar to that in the low expertise before the tips condition. The tips were concise coaching advice regarding coordination related to the crucial role of intervention decision and adjustment. This was also lower than that simulated in the random walk condition, which served as a minimal baseline for scientifically explaining the observed complexity. Our first step study suggests that the movement dynamics at the expert level may be relatively complex, making it difficult for the defensive team to anticipate, and related to the application of team strategies.