TechnologyInnovationModelingin SPORTS
🚀 Elevate your expertise in sports science with a solid foundation in mathematical modeling: learn to apply models to refine research, challenge assumptions, and drive performance outcomes.
Essential definitions and the shipping service concept. Learn about variables, parameters, and relationships through interactive examples: HR_max models, muscle force-length relationships, Hill muscle model, and professional cycling performance estimation.
Master parameter estimation, RMSE optimization, and HR_max model analysis. Explore interpolation vs extrapolation with Olympic records, and understand overfitting through the bias-variance tradeoff with practical examples.
Dive into VOâ‚‚ and lactate kinetics, Banister supercompensation model, and intensity-duration relationships. Learn Critical Power, 3-min all-out tests, and the Anaerobic Power Reserve model with interactive simulations.
Introduction to differential equations with first and second-order dynamic systems. Explore VOâ‚‚ kinetics dynamics, mountain bike suspension models, and cycling power equations with numerical integration methods.
Neural network fundamentals with perceptrons, weights, and biases. Understand training vs validation, the Curse of Dimensionality, and how LLMs work through statistical pattern recognition at scale.
Real-world decision making with car crash data models, association vs causation analysis, and the universal mathematical language across disciplines. Explore ethical responsibilities and cross-disciplinary modeling techniques.
Extra Models & Advanced Topics
Beyond the core course modules, explore these advanced models and specialized topics that extend your understanding of technology and innovation in sport.
Students can use this free Google NotebookLM resource for additional study support. Please note: I cannot guarantee the accuracy of content generated by Gemini AI. This is provided to offer more learning solutions to students.