Automated Trading: Sports Markets
Developing profitable automated trading strategies that operate on sports markets
  • 2017-06-01
  • Python
  • Machine Learning
  • Data Science
  • Trading
  • Project Overview

    Trading on sports markets is an experience that shares many common aspects with trading on financial markets. Invdividuals can buy and sell sports bets on an exchange, with the opportunity to make a profit regardless of the outcome of the event.

    Since the start of 2017, I have been working on devising and implementing automated trading strategies that can operate on these markets with no human intervention. These strategies primarily work by forecasting the occurrence of specific events in football matches, with the help of machine-learning and probability theory. In September, I deployed my trading bot on live football markets, and it has been trading ever since - all day, every day.

    I started with a fund containing a number of units, where each unit was worth £10. The statistics of this fund can be seen on the homepage under the name 'DBC'. Given a scenario where individuals can invest into a fund managed by this strategy by purchasing units, the challenge is to see how the value of the units will rise over time.

    At the present moment, each unit is worth: £10 (0%).

    Phase 1

    The following are the results for the first phase of deployment:

    The aim for Phase 2 is to scale up the operation by increasing the amount of risk that can be taken per trade. More information to follow.

    Tech and Libraries