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ECON30580

Academic Year 2025/2026

Economics of Betting Markets (ECON30580)

Subject:
Economics
College:
Social Sciences & Law
School:
Economics
Level:
3 (Degree)
Credits:
5
Module Coordinator:
Professor Karl Whelan
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

Betting markets provide a fascinating way to see economics in action and to apply it to a fast-growing dynamic sector.

We start with the history of betting markets and how to use betting odds to estimate probabilities and bookmakers' profit margins.

We will cover the theory of decision making under uncertainty and discuss the question of why people bet since, on average, most bettors lose. We will discuss how conventional expected utility models can generally do well at explaining the behaviour of bettors once we factor in that people disagree about the probabilities of various outcomes.

We apply this model of the behaviour of bettors to see how odds and outcomes emerge from different market structures. In particular, we provide a detailed discussion of the theory and evidence relating to bookmakers. We use textbook microeconomics to explain why competitive betting markets differ from those that are imperfectly competitive and how bookmakers use elasticity of demand to price odds. Evidence from a series of big datasets is used to show when the textbook theory does well and also when it doesn't. We discuss topics like favourite-longshot bias (the pattern for losses from betting on favourites to be lower than when betting on longshots), average returns on bets in types of betting markets and the economics of multi-leg bets such as accumulators.

After bookmakers, we discuss how betting exchanges work and why they generally offer a better outcome for customers. We briefly discuss prediction markets, which have a similar structure, allowing people to agree to bilateral bets on the outcomes of non-sports events.

We conclude by discussing the evidence on the social and financial impact of gambling and issues relating to taxation and regulation of the betting sector.

Warning: The module does not offer a recipe for success in betting. The lecturer does not recommend betting. The average bettor loses money and we have no reason to assume our average student is different from the average bettor in assessing bets. However, we do provide some evidence for how some betting strategies lose less money than others.

About this Module

Learning Outcomes:

Upon completion of this module, you will
• Understand the history of betting markets and how they have changed in recent decades.
• Be able to use betting odds on an event to calculate implied probabilities and the bookmaker’s profit margin.
• Know how to use the economics of decision making under uncertainty to model decisions taken to place money in betting markets.
• Understand how different betting market structures generate different outcomes.
• Be knowledgeable about the empirical literature on outcomes in various betting markets.
• Understand why certain kinds of bets have higher average loss rates than others.
• Be able to evaluate arguments for and against "optimal betting" rules such as the Kelly criterion.
• Be aware of the economic impact of problem gambling and the policy debates about taxation and regulation of betting.

Indicative Module Content:

1. Introduction
2. The past and present of betting markets
3. Basics of betting markets: Odds, win rates, expected payouts and margins
4. Risk-taking and utility in gambling
5. Pari-mutuel betting and the favourite-longshot bias
6. Disagreement and pari-mutuel betting
7. Introduction to fixed-odds betting markets
8. Market structure and information in fixed-odds betting markets
9. A monopolistic model of fixed-odds betting markets
10. Oligopoly in fixed-odds betting markets
11. Evidence and case studies
- Favourite-longshot bias
- Spread bets versus bets on who wins
- Returns to betting on draws
- Corruption and inside information
- Betting with big fields
- Margins across different markets
- Specials and multi-leg bets
- In-play betting and cash out
- Free bets
12. Asian handicap betting on soccer
13. Betting exchanges and prediction markets
14. Ruin, risk aversion and the Kelly criterion
15. Social impacts of gambling and questions about regulation and taxation

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

80
Lectures

24
Total

104

Approaches to Teaching and Learning:
The module is based around lectures given by the module co-ordinator. Lecture slides are made available in advance of classes.

Sample chapters from a book draft by the lecturer will be made available as supplementary reading. These chapters are aimed at a general audience and they will not cover all the technical issues that will be covered in the assessments. The assessments are based on what is in the lecture notes. If you see something in the book chapters that is not in the notes, it will not be covered in the assessment.

On the use of AI.

For the assignment:

- The assignment requires you to submit a unique set of answers so generic answers from AI are unlikely to score well and may be fails.

- The language that various AI tools use to answer this question will be very similar. Remember that I can also ask AI to answer these questions and I can tell if your answers look like generic AI-generated answers.

For the exam, I know many of you think AI is of great help when preparing for exams but my experience is performance in exams is worsening in recent years and it is because of reliance on AI.

- A better strategy than relying on AI-prepared answers will be to (a) Come to class to hear me emphasise what I think are the key points (b) Reading the lecture notes and book chapters.

- Just typing the questions that I provide into an AI chatbot will produce answers that score will score badly if you repeat them in the exam. The exam is a test of the material covered in this module, not what AI picks up from scanning the internet.

Requirements, Exclusions and Recommendations
Learning Recommendations:

There are no formal pre-requisites for this module but it is strongly recommended that students have a good understanding of statistics and also that they have an understanding of intermediate microeconomics material on optimisation of utility and decision-making under uncertainty.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): An assignment that covers some basic topics in the economics of betting markets. Week 8 Alternative linear conversion grade scale 40% No
30
 No
Exam (In-person): End of trimester final exam End of trimester
Duration:
2 hr(s)
 Alternative linear conversion grade scale 40% No
70
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

The module co-ordinator will be available throughout the term to provide feedback in relation to preparing for assessments and in relation to how the assessment has been graded.

Name Role
Katharina Richter Tutor

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 31, 32, 33 Fri 11:00 - 11:50
Spring Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Wed 13:00 - 13:50
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