Sports analytics traces back to 1870s baseball box scores, but only recently have advanced techniques like machine learning transformed franchise operations. This shift was driven by both improved data collection and the proven competitive edge highlighted in "Moneyball".

Today, analytics critically impacts draft selections, in-game decisions, and player evaluations. Beyond teams, leagues and media use data for strategic decisions - even informing rule changes.

This course covers data quality assessment, data modeling, and data visualization using R and Python, providing students with the practical skills to apply analytics in real-world sports performance contexts.

Intensifying athlete workloads make precise load monitoring essential for optimizing performance while preventing costly injuries.

The course follows a "why to so what" framework, ensuring each module connects theory to practical application:

• Training Theory: Foundational load monitoring principles
• Load Metrics: Internal and external measurement techniques
• Athlete Response: Objective and subjective tracking methods
• Dashboard Development: Building reports in R/Python
• Data Communication: Effectively sharing insights with stakeholders

Modern basketball scouting combines traditional evaluation with cutting-edge analytics. This program covers the complete scouting ecosystem from high school prospects to professional leagues worldwide.

• Player Evaluation: Master rating systems and performance metrics
• League Scouting: NBA/WNBA/college/international comparisons
• X's & O's Playcall Terminology: Basketball Tactics and Strategy
• Tech Platforms: InStat & Synergy Sports proficiency
• Career Pathways: Build professional networks and scouting opportunities

● Research Assistance with AI Tools
Leverage modern AI platforms such as DeepSeek, Grok, and ChatGPT to support literature searches, paper analysis, and academic writing improvement, enhancing efficiency while maintaining the need for scholarly thinking.
● Bibliometric Analysis
Apply bibliometric methods to evaluate publication trends, research hotspots, and collaboration networks, using major databases such as SPORTDiscus, PubMed, Web of Science, Scopus, ScienceDirect, and Google Scholar.
● AI-Powered Literature Search & Gap Identification
Use AI-driven search platforms like Perplexity AI, Consensus, Scite, and Elicit to conduct natural language queries, filter studies by evidence strength and methodological detail, and identify gaps in existing literature for future research.

Master cutting-edge performance assessment using industry-standard tools like Catapult (movement tracking), ForceDecks (jump analysis), and GymAware (strength monitoring) to conduct evidence-based athlete evaluations.

Develop skills to interpret performance data and optimize training programs through advanced monitoring techniques.