Football Analytics with Python & R: Learning Data Science Through the Lens of Sports

Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data.

Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to:

• Apply basic statistical concepts to football datasets
• Describe football data with quantitative methods
• Create efficient workflows that offer reproducible results
• Use data science skills such as web scraping, manipulating data, and plotting data
• Implement statistical models for football data
• Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny
• And more

棒球不是唯一一個使用「moneyball」的運動。美式足球的球迷、球隊和賭徒越來越多地使用數據來在競爭中取得優勢。職業和大學球隊使用數據來幫助選擇球員和確定球隊需求。球迷使用數據來指導幻想球隊的選擇和策略。體育博彩者和幻想足球玩家使用數據來幫助做出決策。這本簡明的書提供了使用統計模型分析足球數據的清晰介紹。

無論你的目標是打造一支勝利的球隊、在幻想足球聯賽中佔據主導地位、獲得初級足球分析師職位，還是僅僅通過有趣的實例案例學習 R 和 Python，這本書都是你的起點。你將學習如何：

- 將基本統計概念應用於足球數據集
- 使用定量方法描述足球數據
- 創建高效的工作流程，提供可重現的結果
- 使用數據科學技能，如網絡爬蟲、數據操作和數據繪圖
- 實施足球數據的統計模型
- 使用工具如 R Markdown 和 R Shiny 將數據摘要和模型輸出鏈接起來，創建報告或演示文稿
- 等等