Mixed Martial Arts (UFC) Analytics with R: Fight Data and Predictive Modeling is an end-to-end, code-first guide for turning UFC fight statistics into actionable insight using the R ecosystem. Designed as a compact professional book (about 20 pages), it delivers a focused, high-signal workflow: acquiring data, preparing clean analytical tables, performing exploratory analysis, and building models that estimate fight outcomes.
Inside, you’ll work with real UFC examples and case studies while learning best practices for reproducible sports analytics: tidy data design, rigorous feature engineering, and evaluation methods that avoid common pitfalls like leakage and overfitting. You’ll build visual narratives around significant strikes, takedowns, control time, and pace—then translate those patterns into predictive models such as logistic regression and tree-based approaches.
Whether you’re an R user looking for a modern sports project, an analyst interested in combat-sports modeling, or a fight enthusiast who wants to learn data science through UFC stats, this book provides a clean, professional path from raw fight tables to interpretable, defensible predictions.
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