Advanced Basketball Data Science: With Applications in R
暫譯: 進階籃球數據科學：R 語言應用實務
Zuccolotto, Paola, Manisera, Marica, Sandri, Marco
相關主題
商品描述
Advanced Basketball Data Science: With Applications in R is the essential next step for anyone looking to push basketball analytics beyond standard metrics. Expanding on the foundation of Basketball Data Science (2020), this book takes readers into the fast-evolving world of advanced statistical modeling, machine learning, and modern computational techniques applied to the game.
From lineup optimization and clutch-performance analysis to player tracking, pose estimation, and ball-trajectory modeling, the book shows how cutting-edge data can reveal the hidden patterns that shape decision-making on and off the court. Readers learn not only what to analyze, but how to build robust, reproducible workflows using real data, fully executable R code, and a structured project environment.
Designed for analysts, coaches, researchers, and graduate students, this volume translates complex concepts into actionable tools that can immediately elevate scouting, strategy, and performance evaluation. Whether you aim to understand spatial tendencies, quantify player impact, or model scoring probabilities with machine learning, this book provides the framework to do so with clarity and confidence.
Advanced Basketball Data Science is where rigorous methodology meets practical basketball insight, an indispensable resource for anyone committed to understanding the game through the power of data.
- Combines advanced statistical methods, machine learning, and computer-vision techniques to provide a unified and cutting-edge framework for basketball analytics.
- Offers fully reproducible workflows - complete with datasets, R code, and additional functions - which enable readers to directly apply and extend all analyses.
- Integrates real-world case studies from diverse data sources (play-by-play, tracking, pose estimation, ball trajectories) to demonstrate how rigorous methodology translates into actionable basketball insights.
商品描述(中文翻譯)
《進階籃球數據科學：R語言應用》是任何希望將籃球分析推向標準指標之外的人的必備下一步。這本書在《籃球數據科學》（2020）的基礎上進一步擴展，帶領讀者進入快速發展的進階統計建模、機器學習和現代計算技術應用於籃球的世界。
從陣容優化和關鍵表現分析到球員追蹤、姿勢估計和球軌跡建模，本書展示了如何利用尖端數據揭示影響場上和場下決策的隱藏模式。讀者不僅學習分析什麼，還學習如何使用真實數據構建穩健、可重現的工作流程，並提供完整可執行的R代碼和結構化的專案環境。
本書專為分析師、教練、研究人員和研究生設計，將複雜的概念轉化為可立即提升球探、策略和表現評估的可行工具。無論您希望理解空間趨勢、量化球員影響，還是使用機器學習建模得分概率，本書都提供了清晰且自信的框架來實現這些目標。
《進階籃球數據科學》是嚴謹的方法論與實用的籃球洞察相結合的地方，是任何致力於通過數據的力量理解籃球的人的不可或缺的資源。
- 結合進階統計方法、機器學習和計算機視覺技術，提供統一且尖端的籃球分析框架。
- 提供完全可重現的工作流程 - 包含數據集、R代碼和附加函數 - 使讀者能夠直接應用和擴展所有分析。
- 整合來自多樣數據來源的真實案例研究（逐球記錄、追蹤、姿勢估計、球軌跡），展示嚴謹的方法論如何轉化為可行的籃球洞察。
作者簡介
Paola Zuccolotto is a Full Professor of Statistics at the University of Brescia, with nearly 30 years of experience in scientific research in the field of Statistical Sciences. Her research focuses on multivariate data analysis, data mining, prediction using statistical models and machine learning algorithms, and time series analysis. Her work spans a wide array of applications, with particular emphasis on finance, social sciences, genetics, and sports, especially basketball analytics.
She is the Director of the Big&Open Data Innovation Laboratory (BODaI-Lab, bodai.unibs.it) and has established extensive collaborations with international research teams. In 2016, together with Marica Manisera, she co-founded the international network Big Data Analytics in Sports (BDsports, bdsports.unibs.it). She is also a co-author of the book Basketball Data Science: With Applications in R (CRC Press). She has published numerous scientific articles in international journals and books and has been an active participant in several international conferences, including as a keynote speaker.
Marica Manisera is an Associate Professor of Statistics at the University of Brescia and has almost 25 years of experience in scientific research in the area of Statistical Sciences. Her main research interests include multivariate analysis, data mining techniques, and predictive modeling based on statistical approaches and machine learning methods. Her research activity covers different domains, with a strong focus on social sciences and sports, particularly basketball analytics.
She currently serves as Chair of the Special Interest Group on Sport Statistics of the International Statistical Institute and as Associate Editor of the Journal of Sports Analytics, and she has developed long-standing collaborations with international research groups. In 2016, together with Paola Zuccolotto, she co-founded the international network Big Data Analytics in Sports (BDsports, bdsports.unibs.it). She is also co-author of the book Basketball Data Science: With Applications in R (CRC Press). Her publication record includes numerous articles in international journals and book chapters, and she regularly participates in international scientific conferences.
Marco Sandri is a freelance statistician with nearly 30 years of experience in scientific research. His work spans time series analysis, machine learning, biostatistics, and sports analytics. He has collaborated extensively with international research teams in medicine and biology, with an emphasis on the modeling and prediction of complex phenomena. In parallel, he has conducted long-standing research in sports data science, analyzing performance determinants across several sports, with a particular emphasis on
basketball analytics. He is a co-developer of the BasketballAnalyzeR R package and previously authored a chapter in Basketball Data Science: With Applications in R (CRC Press). He has taught courses on statistics, machine learning, and data analysis, and has published over 300 peer-reviewed articles in international journals.
作者簡介(中文翻譯)
**Paola Zuccolotto** 是布雷西亞大學的統計學全職教授，擁有近30年的統計科學領域科學研究經驗。她的研究專注於多變量數據分析、數據挖掘、使用統計模型和機器學習算法的預測以及時間序列分析。她的工作涵蓋了廣泛的應用，特別強調金融、社會科學、遺傳學和體育，尤其是籃球分析。
她是大數據與開放數據創新實驗室（Big&Open Data Innovation Laboratory, BODaI-Lab, bodai.unibs.it）的主任，並與國際研究團隊建立了廣泛的合作關係。2016年，她與Marica Manisera共同創立了國際網絡「體育中的大數據分析」（Big Data Analytics in Sports, BDsports, bdsports.unibs.it）。她也是《籃球數據科學：R語言應用》（Basketball Data Science: With Applications in R, CRC Press）一書的共同作者。她在國際期刊和書籍上發表了大量科學文章，並積極參加多個國際會議，包括擔任主題演講者。
**Marica Manisera** 是布雷西亞大學的統計學副教授，擁有近25年的統計科學領域科學研究經驗。她的主要研究興趣包括多變量分析、數據挖掘技術以及基於統計方法和機器學習方法的預測建模。她的研究活動涵蓋不同領域，特別專注於社會科學和體育，尤其是籃球分析。
她目前擔任國際統計學會體育統計特別興趣小組的主席，以及《體育分析期刊》（Journal of Sports Analytics）的副編輯，並與國際研究團隊建立了長期合作關係。2016年，她與Paola Zuccolotto共同創立了國際網絡「體育中的大數據分析」（BDsports, bdsports.unibs.it）。她也是《籃球數據科學：R語言應用》（Basketball Data Science: With Applications in R, CRC Press）一書的共同作者。她的出版紀錄包括在國際期刊和書籍章節中發表的多篇文章，並定期參加國際科學會議。
**Marco Sandri** 是一名自由職業的統計學家，擁有近30年的科學研究經驗。他的工作涵蓋時間序列分析、機器學習、生物統計學和體育分析。他與醫學和生物學的國際研究團隊進行了廣泛的合作，重點在於複雜現象的建模和預測。與此同時，他在體育數據科學方面進行了長期研究，分析多項運動的表現決定因素，特別強調籃球分析。他是BasketballAnalyzeR R套件的共同開發者，並曾在《籃球數據科學：R語言應用》（Basketball Data Science: With Applications in R, CRC Press）一書中撰寫過一章。他教授統計學、機器學習和數據分析課程，並在國際期刊上發表了超過300篇經過同行評審的文章。
