Scalable: The pipeline should scale to multiple platforms and sports with minimal additional work.
Replicable: Any data used should be public information (i.e., no subscription services, no private historical data like cash lines).
For instance, if LeBron has consistently underperformed when matched up against Kawhi, the strategy should figure this out, rather than being told-so explicitly.
Human Intervention: Zero “expert knowledge” should be required.
We should be able to validate that any changes made to any part of the pipeline lead to better performance than in the past.
Backtest-able: The strategy should be fully backtest-able.
Automated: The entire pipeline should be automated, including entering competitions.
I initially limited the scope to NBA double-up and 50/50 competitions on DraftKings. From the outset, I laid out a few requirements for the project.
0 kommentar(er)
