predictive-models

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predictive-models

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A repo of the Data Scientist team's open source predictive models.

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# Predictive Models
This repo includes some of the Data Scientist team's open source predictive models, of which predictions are posted on [The Hub](https://www.betfair.com.au/hub/tools/models/). Models are produced in both R and Python.

## Aim
This repo aims to educate the Betfair community on creating your own end-to-end models to predict sport. It will be extremely informative and descriptive; the goal is for those without much coding experience to be able to read through the process and understand what is being done.

## Tutorials
* Our [Brownlow Medal Predictions Tutorials](https://github.com/betfair-datascientists/predictive-models/tree/master/brownlow) walks you through creating predictions for the Brownlow in in both R and Python.
* In our [EPL Predictions Tutorial](https://github.com/betfair-datascientists/predictive-models/tree/master/epl), we have used publically available data to model odds and create an automated betting strategy.
* Read through our [AFL Predictions Tutorial/Machine Learning Walkthrough](https://github.com/betfair-datascientists/predictive-models/tree/master/afl). This generates weekly predictions for the AFL.
* We have created [FIFA World Cup 2018 Modelling Tutorial](https://github.com/betfair-datascientists/predictive-models/tree/master/world-cup), including a Machine Learning Walkthrough and Elo Model Walkthrough.

## Links to Current Predictions
* [Greyhound Predictions Model](https://www.betfair.com.au/hub/tools/models/greyhound-ratings-model/)
* [EPL Predictions Model](https://www.betfair.com.au/hub/tools/models/epl-predictions-model/)

## Disclaimer
Note that whilst predictions are fun and rewarding to create, we can't promise that your betting strategy will be profitable. If implementing your own strategies please gamble responsibly and note that you are responsible for any winnings/losses incurred.

predictive-models

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