Player Risk in the Sports Vertical: Is player risk more accurately flagged with a vertical-specific approach?

This industry brief investigates whether sports betting-specific risk models improve the identification of at-risk players compared to general gambling risk models. Key points include:

• Player risk algorithms typically rely on behavioural data, but different gambling verticals have unique characteristics that may require tailored approaches. 

• The research tests if adding sports-specific markers (such as in-play betting, cash-outs, and seasonal adjustments) improves risk detection accuracy.

• Including sports variables alongside basic behavioural markers showed improved accuracy for sports-focused gamblers, particularly in reducing missed positive cases.

• Feature importance analysis revealed that while basic behavioural markers remain key drivers, cash-outs and in-play intensity metrics added incremental value.

• The study demonstrates that vertical-specific approaches can reduce model blindspots and improve identification of at-risk players who might otherwise be missed.

The research highlights the potential for vertical-optimised risk models while acknowledging that traditional holistic approaches remain valuable. Further work with larger samples and additional sports markers could yield further improvements. Read more