Step into the world of baseball data science with this complete guide to using R for sabermetrics and performance analysis. Whether you’re a data science student, a baseball coach, or a stats-savvy fan, this ebook equips you with the tools to analyze players, teams, and strategies using real MLB data.
From calculating advanced statistics to building visualizations and predictive models, this book offers hands-on practice in every chapter.
📊 What You’ll Learn:
✅ Clean and structure baseball datasets (batting, pitching, fielding)
✅ Calculate and interpret key sabermetrics (wOBA, OPS, WAR, BABIP, FIP, etc.)
✅ Visualize trends by season, player, or team
✅ Compare player roles and historical performance
✅ Build regression and clustering models for predictions
✅ Create dashboards using tidyverse and ggplot2
👥 Who It’s For:
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Baseball analysts and sabermetrics enthusiasts
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R users and data scientists seeking real-world sports data projects
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MLB fans who love stats and want to go deeper into the game
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Coaches and performance staff using data to inform decisions
📦 What’s Inside:
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Over 45 pages of content with annotated R code
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Case studies using real player stats and MLB scenarios
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Practical projects and templates for immediate use
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Ideal for both beginner and intermediate R users
Whether you’re preparing your fantasy league, analyzing your favorite players, or training for a career in sports analytics, this guide will give you the edge you need to make sense of the numbers behind America’s pastime.
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