## 6 Data Visualization (DV) in Sports Performance Analysis
### How DV Can Contribute to the Sports Performance Analysis Traditional Methodology  
DV can simplify complex data by presenting it in easily understandable visuals [160,160, 166]. Its primary objective is to extract valuable insights from a dataset, equipping coaches, athletes, and analysts with the tools to make informed decisions based on data patterns and trends [161,167, 168, 169]. While traditional statistics struggled to capture the intricacies of athletic performance, visualizations such as heatmaps, scatter plots, and motion paths have unveiled hidden insights [163,170,171]. For example, heatmaps vividly display an athlete's movements on the field, enabling coaches to identify tactics and positioning strategies.  
DV transcends numerical data to weave captivating narratives. With meticulous data preparation and modelling, it crafts visuals that grant players, coaches, officials, analysts, and fans a more profound and immersive grasp of the game and performance. As described by Perin et al. [156], various types of data can be collected, including box-score data, tracking data, and meta-data, each offering new narratives for in-depth exploration, such as dissecting tracking data, showcasing events, trajectories, and player perspectives, and further enriching them with specific information and graphical representations. Notable examples demonstrate the breadth of data collected, including court views, temporal event sequences, player shot patterns, and textual play-by-play analysis [172,173].  
The foundation of powerful DV lies in primary sports data--a goldmine sourced from wearables, tracking systems, and video recordings. These data encompass player positions, velocities, heart rates, distances covered, shot attempts, and much more. To craft effective DV, the raw data must undergo meticulous cleaning and organization to ensure accuracy and meaningful visual representations. Subsequently, various DV techniques come into play to convey specific insights. For instance, soccer tracking data translate into heatmaps that vividly depict player positions, with color-coding revealing activity levels. Sprint speeds, shot accuracies, and endurance levels emerge through scatter plots, line charts, and bar graphs. These visualizations empower coaches to grasp player performance and its evolution over time.  
DV also leverages historical data to create trend lines, allowing teams to identify strengths, weaknesses, and areas for improvement. By comparing past and present data, coaches and analysts gain profound insights into teams and individual players. Real-time statistics presented in dynamic dashboards facilitate better decision-making during games. Additionally, based on historical trends, individual player performance, and current team data, predictions about overall performance, player contributions, and team selections can be made.  
Below we have listed the main points where DV can transform current sport performance analysis:  
* **Simplified Data Interpretation:** DV simplifies complex performance data, making it more understandable.  
* **Valuable Insights:** It helps extract valuable insights from extensive datasets, enabling data-driven decision-making in sports.
* **Tactical Analysis:** Heatmaps, motion paths, and other visualizations enable coaches to analyze player movements, tactics, and positioning strategies effectively.
* **Narrative Power:** DV goes beyond numbers, crafting visual narratives that empower coaches, athletes, and analysts to uncover deeper insights.
* **Real-Time Decision-Making:** Dynamic dashboards with real-time statistics assist coaches and analysts in making better decisions during games, benefiting data-driven broadcasting.
* **Historical Data Trends:** DV helps in identifying historical trends, strengths, and weaknesses, aiding teams in strategic planning and player selection.
* **Predictive Analytics:** DV can enable predictions about overall performance, individual player contributions, and team selections based on historical and current data.