Real-World Pickleball Analytics with R (and Python) is a professional book in English that takes pickleball analytics from raw data to tactical decision-making. Based on real competition data, it teaches you how to explore matches, break down rallies, analyze serve and return patterns, study drops, drives, lobs, and dinks, understand court coverage, evaluate match flow, and build dashboards and coaching reports.
The focus is 100% practical: R as the main language, with optional Python examples, and reproducible code ready to apply in your work.
Ideal for: coaches, sports analysts, trainers, and data enthusiasts who want to apply advanced analytics to pickleball and turn insights into on-court results.
What You’ll Learn
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Data acquisition and cleaning of real pickleball results, rallies, shots, and positions.
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Performance exploration by player/team: point percentages, differentials, and key metrics.
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Rally analysis: length distributions, finishing types, and unforced errors.
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Serve and return: depth, placement, and their impact on rally win percentage.
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Third shot, dinks, and lobs: strategies and error rates.
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Court coverage and critical zones.
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Match flow & momentum: score progression and point streaks.
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Player comparisons with key performance metrics.
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Tactical scouting: opponent reports and practical recommendations.
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Reports and dashboards: R Markdown/Quarto and Shiny basics to deliver insights to your staff.
What’s Included
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Full R code in every chapter (with optional Python snippets).
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Examples of tables and pipelines to automate performance reports.
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Best practices for turning metrics into training and coaching decisions.
Key Benefits
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Transform raw data into actionable insights to win more points and close matches.
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Improve return depth and third-shot quality with objective evidence.
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Detect error trends and attack opportunities with clear metrics.
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Speed up your workflow with reproducible templates and ready-to-use reports for your staff.
Product Details
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Format: Professional PDF (content in English).
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Approach: Practical, designed for coaches and analysts.
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Requirements: R installed (tidyverse recommended), optional Python for some examples.
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Level: Intermediate (basic R) to advanced (modeling/analytics).
Chapter Titles (Overview)
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Introduction to Pickleball Analytics and Data Sources
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Tournament Metrics and Player Performance
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Rally Breakdown and Outcomes
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Serve and Return: Depth, Placement, and Advantage
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Shot Distribution and Success Rates (drops, drives, dinks, lobs)
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Court Coverage and Key Zones
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Match Flow & Momentum
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Dashboards and Player Comparisons
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Tactical Scouting and Opponent Preparation
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Automating Coaching Reports (R Markdown/Quarto)
Ebook Pages: 29
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