This is my latest project built using the Streamlit framework. The dashboard provides various statistics from Major League Soccer (MLS), including key metrics such as xG, Goal Difference, and Goals Scored.
Project Overview
Data Collection: I scraped MLS data from Sports-Reference.com using BeautifulSoup to retrieve the latest standings and team statistics. Visualizations: I created interactive visualizations with Plotly Express, displaying insights such as xG, Goal Difference, and Goals Scored. The use of Streamlit makes it easy for users to interact with these visualizations. Libraries Used: I explored multiple libraries, including Seaborn, Matplotlib, and Plotly, weighing their pros and cons. While I have extensive experience with Matplotlib, I opted for Plotly for this project due to its seamless integration with Streamlit and its visual appeal.
Key Features
User-Generated Visualizations: I implemented interactive features allowing users to customize their visualizations. With radio buttons, users can choose between the Eastern and Western conferences and select different categories to plot on the X and Y axes. Real-Time Feedback: Streamlit made it easy to see changes to the code in real time, which greatly enhanced the development process. Data Exploration: Users can explore the relationship between different statistics and gain insights from the MLS dataset.
Why Streamlit?
User-Generated Visualizations: I implemented interactive features allowing users to customize their visualizations. With radio buttons, users can choose between the Eastern and Western conferences and select different categories to plot on the X and Y axes. Real-Time Feedback: Streamlit made it easy to see changes to the code in real time, which greatly enhanced the development process. Data Exploration: Users can explore the relationship between different statistics and gain insights from the MLS dataset.
View the App
You can view the app and interact with the dashboard here: MLS Stats Dashboard