Case Study
Betfair Betting Bot &
Betfair Trading Software Development
(Bet Fair)
About BetFair Bot
A client reached out to us to build an automated betting bot on the popular BetFair application using API to maximise their profits from betting on horse racing by understanding the market trends. BetFair is an application that enables its users to bet on international sporting events. First, we understood how the betting industry works, and then we understood how BetFair works, after which we began solving the problem.
Speed of Technology
Problem
- We needed a fast technology to synchronize the source data to our system.
- We had to run our programs real time during the horse race.
- We ran our calculations on the given data, but by the time we generated an analysis of the probable winner, the market trends and positions of the race horses altered — so our result had no value.
Solution
- We used Node.js — an open-sourced JavaScript run-time environment that has the fastest libraries.
- Node.js allowed us to establish a swift and persistent connection between BetFair and our algorithm.
- We could run our program with race data and generate results using the latest trends up-to-the-second with more than 99% of the source data matching our index.
99%+
Source Data Match Accuracy
Real-time sync with BetFair via Node.js
Algorithm with Better Analysis
Problem
The client provided their own algorithm to make betting predictions using the market trend.
- We could not generate more correct results.
- Our probability was 40–50% and our formulae was not working as desired.
- We were losing money.
Solution
We used Machine Learning to analyse the real-time data of the market trend received in the Node.js libraries and received better recommendations regarding our bet.
40–50%
Before ML
85–90%
After ML
Correct bet probability
The Result
85–90%
Betting Accuracy
Achieved with Machine Learning
99%+
Data Sync Accuracy
Real-time via Node.js
This was the first time we were dealing with a client involved in the betting industry. It took a lot of effort on our part to first understand the betting process, rules, and then find a solution to the problem. We first synchronized the betting data and our index using the speed of Node.js and improved the accuracy of our predictions using Machine Learning. Thus, we were able to leverage the latest technologies and incorporate their features in the arena of betting to generate maximum profits for our clients without much hassle.
