IGaming Course

Lesson 1 • Revenue Models and Business Metrics

Explains GGR, NGR, hold percentage, and margin concepts. Connects revenue models to operator profitability and investor reporting.

Lesson 2 • Defining iGaming and Its Segments

Covers the full spectrum of iGaming verticals: sports betting, casino, poker, bingo, and lottery. Establishes shared vocabulary used throughout the course.

Lesson 3 • Industry Stakeholders and Value Chain

Maps operators, suppliers, affiliates, payment providers, and regulators. Shows how value flows between each party in a typical iGaming transaction.

Lesson 1 • Advertising and Marketing Compliance

Outlines rules governing bonus terms, targeting restrictions, and prohibited claims. Connects non-compliant marketing to license risk and reputational damage.

Lesson 2 • Data Protection and Privacy Obligations

Applies data protection principles to player data collection, storage, and sharing. Highlights operator duties when handling sensitive personal information.

Lesson 3 • Anti-Money Laundering Obligations

Covers customer due diligence, source-of-funds checks, and suspicious activity reporting. Links AML failures to real-world regulatory sanctions.

Lesson 4 • Licensing Regimes and Jurisdictions

Compares licensing models by strictness, cost, and market access. Enables students to evaluate which license type suits a given business model.

Lesson 1 • Random Number Generation and Fairness

Covers certified RNG systems, return-to-player calculations, and third-party testing. Connects technical fairness to player trust and regulatory approval.

Lesson 2 • Sports Betting Technology Stack

Details odds compilation, feed management, risk management engines, and in-play systems. Shows how each component affects margin and customer experience.

Lesson 3 • Wallet, Payments, and Transaction Systems

Explains single-wallet architecture, payment gateway integration, and transaction reconciliation. Links payment infrastructure to player experience and fraud exposure.

Lesson 4 • Platform Security and Integrity

Addresses DDoS protection, encryption standards, and penetration testing. Frames security investment as a license condition and brand protection measure.

Lesson 1 • Slot Game Design and Features

Examines payline structures, bonus mechanics, and progressive jackpot systems. Connects design choices to player engagement and operator margin.

Lesson 2 • Game Mathematics and House Edge

Teaches probability, expected value, variance, and volatility as applied to casino products. Enables students to interpret maths sheets and supplier RTP claims.

Lesson 3 • Game Portfolio Management

Applies data-driven methods to lobby curation, supplier negotiation, and game retirement decisions. Connects portfolio strategy to GGR optimisation.

Lesson 4 • Core Casino Game Categories

Surveys slots, table games, live dealer, and instant-win products. Establishes product knowledge required for game mix and supplier evaluation.

Lesson 1 • Match Integrity and Fraud Detection

Addresses suspicious betting pattern detection, integrity body cooperation, and internal controls. Links integrity failures to license risk and reputational harm.

Lesson 2 • Sportsbook Structure and Markets

Introduces market types, event coverage hierarchy, and book structure. Provides the operational context for all subsequent trading and risk topics.

Lesson 3 • Odds Compilation and Pricing

Teaches probability conversion, margin application, and competitive pricing strategy. Connects accurate pricing to margin protection and customer acquisition.

Lesson 4 • In-Play Trading and Live Betting

Covers real-time odds adjustment, automated suspension triggers, and live data dependency. Highlights the speed and accuracy demands of in-play operations.

Lesson 1 • Affiliate Marketing Management

Covers CPA, revenue share, and hybrid commission models, plus affiliate compliance oversight. Positions affiliate management as a high-ROI but high-risk channel.

Lesson 2 • Acquisition Channel Overview

Maps paid search, SEO, affiliates, social, and programmatic channels to iGaming use cases. Establishes the channel mix framework used throughout the chapter.

Lesson 3 • Bonus and Promotion Strategy

Analyses welcome bonus structures, wagering requirements, and bonus abuse prevention. Connects promotion design to player quality and long-term value.

Lesson 4 • SEO and Content Marketing

Applies keyword strategy, content architecture, and link-building to iGaming organic growth. Links content investment to sustainable, low-cost player acquisition.

Lesson 1 • Loyalty Programs and VIP Management

Designs points-based, tier-based, and cashback loyalty schemes. Links programme structure to player stickiness and high-value customer retention.

Lesson 2 • Player Segmentation and Profiling

Applies RFM analysis and behavioural clustering to iGaming player databases. Segments form the foundation for all personalised retention activity.

Lesson 3 • Lifetime Value Modelling

Calculates player LTV using deposit frequency, average bet, and churn probability. Connects LTV models to acquisition budget decisions and profitability forecasting.

Lesson 4 • Churn Prediction and Win-Back Campaigns

Uses predictive models and trigger-based campaigns to reduce player churn. Balances commercial win-back goals with responsible gambling safeguards.

Lesson 1 • Core iGaming Data Infrastructure

Covers data warehouse design, event tracking schemas, and ETL pipelines for iGaming data. Establishes the technical foundation for all analytical work in the chapter.

Lesson 2 • Strategic Reporting and Stakeholder Communication

Translates analytical findings into executive presentations and board-level reports. Develops the communication skills needed to influence strategic decisions with data.

Lesson 3 • Operational KPI Dashboards

Builds real-time dashboards tracking GGR, active players, margin, and bonus costs. Connects dashboard design to daily operational decision-making.

Lesson 4 • A/B Testing and Experimentation

Applies controlled experimentation to product features, bonus offers, and UX changes. Teaches statistical significance, sample sizing, and result interpretation.