Improving Betting Accuracy and Profitability with Machine Learning
This project aims to explore potential opportunities in the Hong Kong Horse Race Betting market, utilising data from Hong Kong Jockey Club.
- Using a single-bet betting strategy where we only bet the horse with the highest probability of winning in a race, we are able to make substantial profits
- Flat betting yielded the highest absolute profits
- While using Kelly Criterion to perform bet allocation reduced absolute profits, average returns per bet consistently outperformed flat betting across all methods and target variables
- Overall, all models are able to predict the winner of a race more than 50% of the time
| Race Speed Regressors | Finish Time Regressors | Finishing Position Classifiers | |
|---|---|---|---|
| Flat Betting | $41,250 | $31,290 | $8,430 |
| Betting with Kelly Criterion | $30,360.08 | $28,419.82 | $4,914,48 |
| Prediction Accuracy | 57.3% | 55.1% | 53.9% |
