About

What you'll learn

Build a durable foundation in sports betting, from information quality and execution discipline to the modeling mindset required for long-term success.
Understand betting basics, odds formats, edge, bankroll growth, and the practical mechanics of identifying and evaluating opportunities.
Learn to apply probability, expected value, arbitrage, promos, middling, and record-keeping in a structured workflow that supports real decision-making.
Graduate with a practical toolkit for protecting and growing your bankroll, evaluating angles, and executing strategies with discipline over time.

Skills you'll gain

Betting Fundamentals
Probability & EV
Bankroll Management
Arbitrage & Middling

Details to know

Foundations of Sports Betting includes eight lectures and forty-four modules, totaling more than seven hours of professionally edited instruction. Students receive permanent access to the lecture library, bundled tools, and ongoing reference material they can apply immediately.

Curriculum

Eight lectures covering the fundamental concepts, tools, and techniques needed to build, protect, and grow a sports betting bankroll with a repeatable process.

Lecture 1: Introduction

Success in sports betting: information, execution, and modeling.

Lecture 2: Fundamental Concepts

The basics of sports betting: the ethics of sports betting, where to bet, common bet types, angles, edges, and strategies, along with American, Decimal, and Fractional odds and how to convert between them.

Lecture 3: Beating the Odds

Probability and its application in sports betting: break-even probability, vig, overround, implied probability, synthetic vig, synthetic overround, expected value, and edge.

Lecture 4: Promos and Bonuses

How to evaluate and effectively take advantage of sportsbook promotions and bonuses, including deposit bonuses, free bets, bonus money, risk-free bets, and related opportunities.

Lecture 5: Arbitrage

The key elements of arbitrage: identifying arbitrage opportunities, sizing bets correctly, working across multi-way outcomes, and practicing execution through examples and exercises.

Lecture 6: Bankroll Management

Essential components of bankroll management: accurate record-keeping, betting within your bankroll, avoiding overbetting, optimal bet sizing, the Kelly criterion, and the practical judgment needed to apply them.

Lecture 7: Middling

How to determine the value of points: middling for spreads and totals, empirical data analysis, half-middling, and practical considerations when deciding whether a middle is worth pursuing.

Lecture 8: Parting Thoughts

A review of key concepts and how they connect to the bundled suite of tools, including odds conversion, promos and bonuses, line shopping, middling, and future tools for continued education. Participants receive permanent access to these resources.

Instructors

Learn From People Who Actually Beat the Market
Harry Crane

Harry Crane

Professor of Statistics · Quantitative Betting Expert · Industry Leader

Associate Professor and Chancellor's Excellence Scholar in Statistics, Co-Director of the Graduate Program in Statistics, Member, CFTC Innovation Advisory Committee, Board Member, American Bettors' Voice, Advisor, Prediction Markets Research Consortium 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.

Philip Maymin

Philip Maymin

Professor of Analytics · Quantitative Researcher · Industry Executive

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.

What Our Students Say

Real feedback from bettors who apply analytics in real markets.
An enlightening and knowledge improving course.
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Steve S.
I have really enjoyed the course. The biggest negative I can think of is that I wish each class was 4 hours, which is definitely a compliment. Overall, great class. I went into the class thinking I needed to refresh / enhance my quant skills to continue to improve. My primary takeaway is that I need to improve my data management and efficiency more than anything.
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Tom Quinn
I really enjoyed the class. I thought you guys did a good balance of beginner to more advanced concepts. Personally, it helped me formalize some of the concepts I've been using but didn't know the official theory behind. I can see potential partnership opportunities for sets of students. One of my friends was in the class and we didn't know it until I mentioned on Twitter that I enjoyed the class.
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Tony Z.
This is extremely pertinent info and I am really grateful you decided to host the course.
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Brian Koral
Enjoyed the course - given me a lot of food for thought and opened my eyes to some different approaches to things too. I like the dynamic between Harry and Philip presenting the course, and if it weren't for the late night start/finish for me in the UK I might contribute more but it's fast-paced enough that there's plenty to digest too.
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Michelangelo Whitson
Very pleased with the content. Instructors did a great job presenting many of the theoretical concepts involved in sports betting. Thanks again for putting on this class, it's been very helpful and informative.
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Thomas
It’s been great. It’s really opened my mind about betting. I found it very amazing how the probability is associated with every aspect of the odds. The way to back test a model is also very valuable. And of course the guest lecture was amazing.
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Aldo Salomon
Very much enjoyed the course, a highlight being the multitude of case studies which began from lecture 1
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Trent S.

Frequently Asked Questions

Answers to common questions about course access, learning flow, and how Analytics.Bet training works in practice.

What We Teach

Our curriculum spans the full spectrum of sports betting mastery - from foundational bankroll-building techniques that require nothing more than basic arithmetic, to advanced regression, machine learning, closing line value, arbitrage, hedging, backtesting, and automated execution. All courses include code, data, and instructor-built tools, with lifetime access.

What You Get

Members join a professional network of students, alumni, faculty, industry leaders, and legendary sports bettors. It opens up career opportunities, and eligibility to contribute to the Analytics.Bet blog and the Journal of Sports Betting.

Our Standard

We do not sell picks or promises. We teach process - the same process professionals use to maintain an edge over time. If you are ready to bet smarter, you are in the right place.

What makes Analytics.Bet different from other betting education sites?

Analytics.Bet is built around decision-making, modeling, and repeatable process rather than hype. Students learn how to price markets, evaluate risk, track performance, and build evidence-based betting systems instead of following tip sheets.

Will this guarantee profits?

No course can guarantee profits, and any honest sports betting education platform should say that clearly. What we provide is a professional framework for improving your edge, reducing avoidable mistakes, and making better long-term betting decisions.

Are these courses beginner-friendly if I am new to betting analytics?

Yes. The curriculum is designed so motivated beginners can start with foundational concepts like probability, bankroll management, and market mechanics before moving into advanced modeling, automation, and quantitative strategy.

Do I need to know coding or advanced math before enrolling?

No. Some advanced lessons use code, data, and more technical methods, but the learning path starts with practical concepts that do not require programming. As you progress, the platform helps you build the analytical skills needed for more sophisticated work.

Who are the courses best suited for?

These courses are best for serious sports bettors, analysts, aspiring quants, and operators who want to move from intuition to structured decision-making. They are especially valuable for people who care about market efficiency, model validation, and long-term expected value.