Toward Super Intelligence in Sports Science & Human Performance:
The Agentic AI Revolution
- Thursday, November 5, 2026
- 7:00 PM Eastern Time (Orlando)
- 60-minute live online masterclass
- Inaugural registration price: US$14.99
Jaime Roa, Founder and Scientific Director, SportsMedTraining
Explore how AI agents can connect sports-performance data, analytical tools, and scientific research. This live online masterclass examines the path toward superintelligence through five practical application areas, illustrative demonstrations, and a critical look at current capabilities and evidence.
Audience: sports scientists, coaches, exercise professionals, and students.
Learning objectives
- Explain what an AI agent is and how goals, tools, feedback, and human oversight shape its actions.
- Distinguish current agent workflows from the future concept of superintelligence.
- Evaluate five sports-science applications through examples and demonstrations.
- Identify the evidence, data quality, and professional review needed for a supervised pilot.
Agenda (60 minutes)
10 min — Foundations: AI agents and the path toward superintelligence. Agent definitions, tool use, feedback, and human oversight.
35 min — Five sports-science applications and demonstrations. Physiological monitoring; adaptive training; injury-risk review and rehabilitation support; biomechanics and performance; research and decision support.
10 min — Evidence, validation, and responsible implementation. What evaluations show, where uncertainty remains, and how to design a supervised pilot.
5 min — Discussion and questions. Apply the ideas to a sample weekly training-summary workflow.
Physiological monitoring
Demo: Combine a sample wearable record, perceived effort, and training history into a reviewable weekly summary.
Adaptive training
Demo: Compare training-plan options against a sample athlete profile, with professional review before changes.
Injury-risk review and rehabilitation support
Demo: Organize load and symptom information for qualified review, with clear limits on automated conclusions.
Biomechanics and performance
Demo: Use a movement-analysis example to show how an agent can coordinate calculation, plotting, and interpretation.
Research and decision support
Demo: Demonstrate a traceable literature-search and evidence-summary workflow with source checking.
The examples distinguish current capabilities from future possibilities. Clinical diagnosis, injury assessment, and return-to-sport decisions require qualified professional review.