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The Opportunity
Hidden signals
Subtle eye movements and decision-making cues were too complex to identify through observation alone
Uncertain decisions
High-stakes choices were driven by instinct instead of reliable, data-backed insights
Unclear patterns
Players couldn’t consistently recognize or learn bluffing behaviors across different games
The Solution
As you may have noticed, this is not a usual project compared to the others done at DareData. However, it was an opportunity for us to put our computer vision experts to the test to solve such a unique problem.
We provided our client with a model that could be applied during games to detect bluffing in their own players as well as their opponents. This allowed players to recognize opponents’ patterns and anticipate when they were bluffing.
Our solution revealed that bluffing was closely tied to the eye behavior, including blink rate, fixation rate, and gaze direction at specific moments. Additionally, the time taken to make a decision also influenced whether a player was likely bluffing.
The Impact
With our model in their games, the players are now empowered by data to support their decision-making and make better decisions. What was once a choice based on gut feeling is now supported by analytics.
From the players' perspective, they get an immersive playing experience, pushing their creativity to the limit as they find new ways to trick the model. Furthermore, the model can be used by players to learn their competitors’ signals.
In fact, during the project, we successfully analyzed the bluffing behavior of two of the highest-stakes players. If you want to learn more, check out Tiago Mota’s blog post on his experience and challenges in this project.
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