Use World Cup soccer (football) data to build models, explore spatial relationships, and create informative visualizations in JMP.  See how to tap JMP's capabilities for iterative visualization and data massaging to explore and understand the data.  

See how to:

• Access data using JMP Python integration. (Access the data using ChatGPT and Python.)
• Prepare and transform data to support richer visualizations.  
• See how population correlates to each country's international ranking
• Model shot quality using key variables such as distance and angle.
• Visualize results directly on a soccer field. (Explore and plot action by carries and passes.)
• Build vector plots to analyze ball movement (passes and carries) and effectively replay sequences.
• Compare expected goals to actual outcomes to identify over- and under-performing teams and players across the tournament.

This webinar covers: Fit Model, Model Screening, Prediction Profiler, Contour Profiler, Python integration, Graph Builder, and Workflow Builder.

Suggested Prerequisites:

• Familiarity with JMP data tables.
• Basic understanding of modeling.

Resources

• 2026 World Cup analysis and data on JMP Public by JMP SE Manlio Caldara.

This webinar uses publicly available soccer data and is not affiliated with or endorsed by FIFA.