Data Management & Engineering for Sports Betting
Leverage the power of data and code to implement, manage, automate, and execute algorithms for scalable sports betting.
Course 1: Scraping, Parsing and Databases
Data acquisition, extraction and storage, Python, Excel, SQL, CSV, XML, JSON, HTML, case study.
Rolling enrollment. Begin today.
Course 2: Automation, Execution and Bots
Github, Selenium, cron, APIs, authentication, scripts, end-to-end case study.
Rolling enrollment. Begin today.
Course 1 Scraping, Parsing and Databases
Data Acquisition
Scraping
Data Extraction
Data Management
Data Transformation
Case Study
Course 2 Automation, Execution and Bots
Building a Robust, Reliable, Scalable Operation
Automation and First Steps Toward Scaling
Data Professionalism
Data Collection Bots I
Data Collection Bots II
Guest lecture by Captain Jack Andrews
End-to-end case study with APIs and exchange trading.
Instructors

Harry Crane is Associate Professor and Chancellor’s Excellence Scholar in Statistics, Co-Director of the Graduate Program in Statistics, and Affiliated Faculty in the Graduate Program in Philosophy at Rutgers University.
He is currently Fellow at the London Mathematical Laboratory, and has previously held positions as a Visiting Scholar in Mathematics at UC Berkeley, Research Associate at the RAND Corporation, and Research Fellow at the Foreign Policy Research Institute. He is also a co-founder of Researchers.One, a platform for scholarly publication and initiative for intellectual reform.
Harry received his PhD in Statistics from the University of Chicago and BA in Mathematics, Economics and Actuarial Science from the University of Pennsylvania.
He has profitably applied statistical and other techniques to successful sports betting and other advantage gambling opportunities and has discussed these experiences on the Business of Betting podcast, the Pinnacle podcast, the Political Trade Podcast, the Artful Trader, Old Bull TV, and other media outlets.
He is the author of Probabilistic Foundations of Statistical Network Analysis.
Website: harrycrane.com
Twitter: @harrydcrane

Philip Maymin is a professor of analytics and the director of the Master of Science in Business Analytics program at the Fairfield University Dolan School of Business where among other things he teaches both an undergraduate sports analytics course and a graduate sports analytics course. He is the founding managing editor of Algorithmic Finance and the co-founder and co-editor-in-chief of the Journal of Sports Analytics. He is the Chief Technology Officer and Chief Operating Officer for Swipe.bet, an Insight Partner with Essentia Analytics, an advisor to Athletes Unlimited, and an affiliate of the Langer Mindfulness Institute, and has been an analytics consultant with several NBA teams.
He holds a PhD in Finance from the University of Chicago, a Master’s in Applied Mathematics from Harvard University, and a Bachelor’s in Computer Science from Harvard University. He also holds a J.D. and is an attorney-at-law admitted to practice in California. He has been a portfolio manager at Long-Term Capital Management, Ellington Management Group, and his own hedge fund.
He was awarded a Wolfram Innovator Award in 2015. He has won numerous coding challenges and hackathons. He was named one of the Top 50 Data and Analytics Professionals in the US and Canada in 2018. He is the only person to have won both the Grand Prize for Best Research Paper (2018) and the Hackathon (2020) at the MIT Sloan Sports Analytics Conference.
He is the author of Financial Hacking.
Website: philipmaymin.com
Twitter: @pmaymin