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Bayesian Modeling

Bayesian Modeling

Our articles focus on the analytical foundations of sports betting - probability theory, statistical inference, market efficiency, and model validation. They are designed for readers who want to understand how betting markets work, not for those looking for quick betting picks.
Introduction to Mixed Models
Bayesian Modeling 11 min read

Introduction to Mixed Models

Translating from Wikipedia’s nomenclature to ours: µ0 is our initial estimate of M_M σ0 is our initial estimate of M_S σ is S n is the number of games we’ve obser...
15-08-2021
206
Matthew Buchalter
By Matthew Buchalter Contributor
Building a Bayesian Model: Part 1
Bayesian Modeling 6 min read

Building a Bayesian Model: Part 1

All of the data and models described in this series of articles can be downloaded here: nba-opponent-shooting-percentageDownload In this series of articles, I’m g...
14-08-2021
193
Matthew Buchalter
By Matthew Buchalter Contributor
Building a Bayesian Model: Part 2
Bayesian Modeling 4 min read

Building a Bayesian Model: Part 2

In Part 1, we built a very simple model for NBA shooting percentage defense that didn’t work very well. The underlying hypothesis was that all team-to-team varian...
14-08-2021
200
Matthew Buchalter
By Matthew Buchalter Contributor
Building a Bayesian Model: Part 3
Bayesian Modeling 4 min read

Building a Bayesian Model: Part 3

In Part 2, we introduced the concept of a “ballast model” and applied it to our NBA defensive shooting percentage data. Just one problem though…we selected our ba...
14-08-2021
206
Matthew Buchalter
By Matthew Buchalter Contributor
Building a Bayesian Model: Part 4
Bayesian Modeling 9 min read

Building a Bayesian Model: Part 4

We ended Part 3 with the Shyamalan-eque twist that the simple ballast model we’ve been building has been a Bayesian model all along. Time to take a step back and...
14-08-2021
255
Matthew Buchalter
By Matthew Buchalter Contributor
Building a Bayesian Model: Part 5
Bayesian Modeling 8 min read

Building a Bayesian Model: Part 5

In Part 4, we took our simple ballast model and re-derived it as a Bayesian model complete with priors, posteriors, hyperparameters, loglikelihoods…the whole sheb...
14-08-2021
710
Matthew Buchalter
By Matthew Buchalter Contributor

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What Our Students Say

Real feedback from bettors who apply analytics in real markets.
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The course was awesome!! Harry and Philip did a great job of laying the foundations while simultaneously providing value to more experienced bettors with advanced topics and guests. My motivation for taking the course came down to my interest in forecasting and markets in general. I think the lessons here are broadly applicable and will help me in my explorations on where to focus my time and energy on my next big project. I think regardless of whether or not I get into betting more seriously, my investment in your course is worth it. On the one hand I may decide betting is not for me and understand better my reasons why and save myself a TON of time and money. On the other hand, I may be able to legitimately find an edge in betting (or other markets perhaps) and make some profits. If anything I'm learning that the true edges are hard to find (and maintain)!
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Aaron Green
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
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
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
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
It’s been great—learned a ton of useful things so far and have some ideas marinating as a direct result of the instruction.
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Alec R.
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

Frequently Asked Questions

Common questions about our betting analytics articles, research archive, and educational resources.

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.