Predictive Modelling for Football Analytics
暫譯: 足球分析的預測模型

討論足球分析領域中知名的模型和主要的計算工具。介紹 footBayes R 套件，該套件將引導讀者完成書中提出的所有範例。

Ioannis Ntzoufras is a distinguished statistician and academic, widely recognized for his contributions to statistical modeling, Bayesian analysis, and sports analytics. He is a full professor in the Department of Statistics at the Athens University of Economics and Business (AUEB). He is particularly known for his work in Bayesian statistics, including the development and application of Markov Chain Monte Carlo (MCMC) methods and Bayesian variable selection techniques. His research also addresses computational strategies and prior formulation for Objective Bayesian model comparison. These methodologies have been applied across various domains, with a strong emphasis on sports analytics--especially in football (soccer).

He served as Head of the Department of Statistics at AUEB from 2020 to 2025. He was awarded the Lefkopoulion Award by the Greek Statistical Institute in 2000 and is the author of the acclaimed book Bayesian Modeling Using WinBUGS (Wiley), which received an honorable mention in Mathematics at the 2009 PROSE Awards. In addition, he has authored a Greek-language textbook titled Introduction to Programming and Statistical Data Analysis with R, and he has served as the scientific editor for the Greek translations of two influential texts: Andy Field's Discovering Statistics with R and Bernard Rosner's Fundamentals of Biostatistics.

Professor Ntzoufras has served as an associate editor for several journals, including the Journal of the Royal Statistical Society C, Statistics, and the Journal of Quantitative Analysis in Sports. As of April 2025, Professor Ntzoufras has authored 76 peer-reviewed journal articles, accumulating over 6,100 citations and an h-index of 29 on Google Scholar. He remains actively engaged in research, with current projects focusing on Bayesian methodology, variable selection, applied statistics, biostatistics, psychometrics, and sports analytics. His contributions to sports analytics have led to the creation of models that enhance performance prediction and strategic planning in football, basketball, and volleyball.

Dimitris Karlis is a distinguished statistician and academic widely recognized for his contributions to the fields of statistical modeling, discrete valued time series analysis, model-based clustering and sports analytics. He is full professor at the Athens University of Economics and Business, where his research focuses on the development and application of advanced statistical methods for various problems and disciplines. He has served as director of the MSc in Statistics program at AUEB, (2019-today), Director of the Laboratory of Computational and Bayesian Statistics (2017 -today) and vice-President of the Research Committee of AUEB (2019 -today). Professor Karlis has made significant contributions to the statistical analysis of sports data, especially in football (soccer), basketball, handball and other team sports. His work on modeling match outcomes, player performance, and team strategies has had a substantial impact on both academic research and practical applications in the sports industry. He is known for pioneering methods such as the use of generalized linear models and mixed-effects models for analyzing sports data as well as the development of innovative model for various sports.

Leonardo Egidi is a distinguished statistician and academic, recognized for his significant contributions to the fields of Bayesian statistics, sports analytics, and statistical modeling. He is assistant professor of statistics at University of Trieste, where his research primarily focuses on applying advanced statistical methods to real-world problems, with a particular emphasis on sports data analysis, genomics, and predictive modeling.

Professor Egidi is well-known for his work in theoretical Bayesian inference and in football analytics, particularly in the development of models to predict match outcomes, assess player performance, and optimize team strategies. His research includes the application of machine learning algorithms and Bayesian methods to enhance the accuracy of predictions and provide insights into various aspects of the game. He has published extensively in leading academic journals and has collaborated with both academic researchers and sports organizations to advance the field of sports data science.

In addition to his work on football, Professor Egidi has also contributed to statistical methodology in other domains, including economics, biostatistics, and social sciences. His expertise lies in the integration of complex data structures, such as hierarchical models, into practical solutions that can drive decision-making processes.

Beyond his research, Leonardo Egidi is actively involved in teaching and mentoring, fostering the next generation of statisticians and data scientists. His work has made a substantial impact on both the academic community and the sports industry, cementing his reputation as a leading figure in the application of statistics to sports analytics.

He is associate editor for the Journal of Quantitative Analysis in Sports and the creator and the maintainer of the CRAN R package footBayes.

Ioannis Ntzoufras 是一位傑出的統計學家和學者，因其在統計建模、貝葉斯分析和體育分析方面的貢獻而廣受認可。他是雅典經濟與商業大學（AUEB）統計系的全職教授。他特別以在貝葉斯統計方面的工作而聞名，包括馬可夫鏈蒙地卡羅（MCMC）方法和貝葉斯變數選擇技術的開發與應用。他的研究還涉及目標貝葉斯模型比較的計算策略和先驗公式化。這些方法已應用於各個領域，特別強調體育分析，尤其是足球（soccer）。

他於2020年至2025年擔任AUEB統計系主任。2000年，他獲得希臘統計學會頒發的Lefkopoulion獎，並且是備受推崇的書籍Bayesian Modeling Using WinBUGS（Wiley）的作者，該書在2009年PROSE獎中獲得數學類的榮譽提名。此外，他還撰寫了一本希臘語教科書，名為Introduction to Programming and Statistical Data Analysis with R，並擔任兩本影響力文本的希臘語翻譯的科學編輯：Andy Field的Discovering Statistics with R和Bernard Rosner的Fundamentals of Biostatistics。

Ntzoufras教授曾擔任多本期刊的副編輯，包括Journal of the Royal Statistical Society C、Statistics和Journal of Quantitative Analysis in Sports。截至2025年4月，Ntzoufras教授已發表76篇經過同行評審的期刊文章，累積超過6,100次引用，Google Scholar的h-index為29。他仍然積極參與研究，目前的項目專注於貝葉斯方法、變數選擇、應用統計、生物統計、心理測量學和體育分析。他對體育分析的貢獻促成了增強足球、籃球和排球的表現預測和戰略規劃的模型的創建。

Dimitris Karlis 是一位傑出的統計學家和學者，因其在統計建模、離散值時間序列分析、基於模型的聚類和體育分析領域的貢獻而廣受認可。他是雅典經濟與商業大學的全職教授，研究重點是為各種問題和學科開發和應用先進的統計方法。他曾擔任AUEB統計碩士課程的主任（2019年至今）、計算與貝葉斯統計實驗室主任（2017年至今）以及AUEB研究委員會的副主席（2019年至今）。Karlis教授在體育數據的統計分析方面做出了重要貢獻，特別是在足球（soccer）、籃球、手球和其他團隊運動方面。他在比賽結果、球員表現和團隊策略建模方面的工作對學術研究和體育產業的實際應用產生了重大影響。他以開創性的方法而聞名，例如使用廣義線性模型和混合效應模型來分析體育數據，以及為各種體育項目開發創新模型。

Leonardo Egidi 是一位傑出的統計學家和學者，因其在貝葉斯統計、體育分析和統計建模領域的重大貢獻而受到認可。他是的的Trieste大學的助理教授，研究主要集中在將先進的統計方法應用於現實世界問題，特別強調體育數據分析、基因組學和預測建模。

Egidi教授以其在理論貝葉斯推斷和足球分析方面的工作而聞名，特別是在開發預測比賽結果、評估球員表現和優化團隊策略的模型方面。他的研究包括應用機器學習算法和貝葉斯方法來提高預測的準確性，並提供對比賽各個方面的見解。他在領先的學術期刊上發表了大量文章，並與學術研究人員和體育組織合作，推進體育數據科學的發展。

除了在足球方面的工作外，Egidi教授還對其他領域的統計方法學做出了貢獻，包括經濟學、生物統計學和社會科學。他的專業知識在於將複雜數據結構（如層級模型）整合到可以推動決策過程的實用解決方案中。

除了研究外，Leonardo Egidi還積極參與教學和指導，培養下一代統計學家和數據科學家。他的工作對學術界和體育產業產生了重大影響，鞏固了他在將統計應用於體育分析方面的領導地位。

他是Journal of Quantitative Analysis in Sports的副編輯，並且是CRAN R套件footBayes的創建者和維護者。